Package: a4 Version: 1.12.0 Depends: a4Base, a4Preproc, a4Classif, a4Core, a4Reporting Suggests: MLP, nlcv, ALL, Cairo License: GPL-3 MD5sum: d40e5248bd26b817b36e78ecbe3351dd NeedsCompilation: no Title: Automated Affymetrix Array Analysis Umbrella Package Description: Automated Affymetrix Array Analysis Umbrella Package biocViews: Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4_1.12.0.tgz vignettes: vignettes/a4/inst/doc/a4vignette.pdf vignetteTitles: a4vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/a4/inst/doc/a4vignette.R Package: a4Base Version: 1.12.0 Depends: methods, graphics, grid, Biobase, AnnotationDbi, annaffy, mpm, genefilter, limma, multtest, glmnet, a4Preproc, a4Core, gplots Suggests: Cairo, ALL Enhances: gridSVG, JavaGD License: GPL-3 MD5sum: c5e70813cb82c0725c68c7a97b202142 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Base Package Description: Automated Affymetrix Array Analysis biocViews: Microarray Author: Willem Talloen, Tobias Verbeke, Tine Casneuf, An De Bondt, Steven Osselaer and Hinrich Goehlmann, Willem Ligtenberg Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Base_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4Base_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4Base_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4Base_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4Base_1.12.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Classif Version: 1.12.0 Depends: methods, a4Core, a4Preproc, MLInterfaces, ROCR, pamr, glmnet, varSelRF Imports: a4Core Suggests: ALL License: GPL-3 MD5sum: 55dfad638644d6ee70ca7d3c9e3df346 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Classification Package Description: Automated Affymetrix Array Analysis Classification Package biocViews: Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Classif_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4Classif_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4Classif_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4Classif_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4Classif_1.12.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Core Version: 1.12.0 Depends: methods, Biobase, glmnet License: GPL-3 MD5sum: 3c415b2dfc7667c30815047cb3ece4f9 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Core Package Description: Automated Affymetrix Array Analysis Core Package biocViews: Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Core_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4Core_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4Core_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4Core_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4Core_1.12.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif importsMe: a4Classif Package: a4Preproc Version: 1.12.0 Depends: methods, AnnotationDbi Suggests: ALL, hgu95av2.db License: GPL-3 MD5sum: 1e7c4fd08f2de55ec95fb4dda9a974be NeedsCompilation: no Title: Automated Affymetrix Array Analysis Preprocessing Package Description: Automated Affymetrix Array Analysis Preprocessing Package biocViews: Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Preproc_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4Preproc_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4Preproc_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4Preproc_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4Preproc_1.12.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif Package: a4Reporting Version: 1.12.0 Depends: methods, annaffy Imports: xtable, utils License: GPL-3 MD5sum: d8decf685f92393f2948e1674c8f247f NeedsCompilation: no Title: Automated Affymetrix Array Analysis Reporting Package Description: Automated Affymetrix Array Analysis Reporting Package biocViews: Microarray Author: Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Reporting_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/a4Reporting_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/a4Reporting_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/a4Reporting_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/a4Reporting_1.12.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: ABarray Version: 1.32.0 Imports: Biobase, graphics, grDevices, methods, multtest, stats, tcltk, utils Suggests: limma, LPE License: GPL MD5sum: 9d4f2bfb6dd7be6c1128a4f359c93c3d NeedsCompilation: no Title: Microarray QA and statistical data analysis for Applied Biosystems Genome Survey Microrarray (AB1700) gene expression data. Description: Automated pipline to perform gene expression analysis for Applied Biosystems Genome Survey Microarray (AB1700) data format. Functions include data preprocessing, filtering, control probe analysis, statistical analysis in one single function. A GUI interface is also provided. The raw data, processed data, graphics output and statistical results are organized into folders according to the analysis settings used. biocViews: Microarray, OneChannel, Preprocessing Author: Yongming Andrew Sun Maintainer: Yongming Andrew Sun source.ver: src/contrib/ABarray_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ABarray_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ABarray_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ABarray_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ABarray_1.32.0.tgz vignettes: vignettes/ABarray/inst/doc/ABarrayGUI.pdf, vignettes/ABarray/inst/doc/ABarray.pdf vignetteTitles: ABarray gene expression GUI interface, ABarray gene expression hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ABarray/inst/doc/ABarrayGUI.R, vignettes/ABarray/inst/doc/ABarray.R Package: ABSSeq Version: 1.0.1 Depends: R (>= 2.10), methods Imports: Rcpp LinkingTo: Rcpp License: GPL (>= 3) Archs: i386, x64 MD5sum: 59b203b19932d2b2352c1a55bb756151 NeedsCompilation: yes Title: ABSSeq: a new RNA-Seq analysis method based on absolute expression differences and generalized Poisson model Description: Inferring differential expression genes by absolute expression differences between two groups, utilizing generalized Poisson model to account for over-dispersion across samples and heterogeneity of differential expression across genes. biocViews: DifferentialExpression Author: Wentao Yang Maintainer: Wentao Yang source.ver: src/contrib/ABSSeq_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/ABSSeq_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/ABSSeq_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/ABSSeq_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ABSSeq_1.0.1.tgz vignettes: vignettes/ABSSeq/inst/doc/ABSSeq.pdf vignetteTitles: ABSSeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ABSSeq/inst/doc/ABSSeq.R Package: aCGH Version: 1.42.0 Depends: R (>= 2.10), cluster, survival, multtest Imports: Biobase, cluster, grDevices, graphics, methods, multtest, stats, survival, splines, utils License: GPL-2 Archs: i386, x64 MD5sum: 2d3185ce9535212fc5fb92528347d194 NeedsCompilation: yes Title: Classes and functions for Array Comparative Genomic Hybridization data. Description: Functions for reading aCGH data from image analysis output files and clone information files, creation of aCGH S3 objects for storing these data. Basic methods for accessing/replacing, subsetting, printing and plotting aCGH objects. biocViews: CopyNumberVariation, DataImport, Genetics Author: Jane Fridlyand , Peter Dimitrov Maintainer: Peter Dimitrov source.ver: src/contrib/aCGH_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/aCGH_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/aCGH_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/aCGH_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/aCGH_1.42.0.tgz vignettes: vignettes/aCGH/inst/doc/aCGH.pdf vignetteTitles: aCGH Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/aCGH/inst/doc/aCGH.R dependsOnMe: CRImage importsMe: ADaCGH2, snapCGH suggestsMe: beadarraySNP Package: ACME Version: 2.20.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), methods Imports: graphics, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: 0133d78c91040dfec94e80ff3cf6640e NeedsCompilation: yes Title: Algorithms for Calculating Microarray Enrichment (ACME) Description: ACME (Algorithms for Calculating Microarray Enrichment) is a set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing "enrichment". It does not rely on a specific array technology (although the array should be a "tiling" array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory. biocViews: Technology, Microarray, Normalization Author: Sean Davis Maintainer: Sean Davis URL: http://watson.nci.nih.gov/~sdavis source.ver: src/contrib/ACME_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ACME_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ACME_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ACME_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ACME_2.20.0.tgz vignettes: vignettes/ACME/inst/doc/ACME.pdf vignetteTitles: ACME hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ACME/inst/doc/ACME.R Package: ADaCGH2 Version: 2.4.0 Depends: R (>= 2.15.0), parallel, ff Imports: bit, ffbase, DNAcopy, tilingArray, GLAD, waveslim, cluster, aCGH, snapCGH Suggests: CGHregions, Cairo, limma Enhances: Rmpi License: GPL (>= 3) Archs: i386, x64 MD5sum: e3d8f3746d3dd9065976ab1ae4bf4e13 NeedsCompilation: yes Title: Analysis of big data from aCGH experiments using parallel computing and ff objects Description: Analysis and plotting of array CGH data. Allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data. biocViews: Microarray, CopyNumberVariation Author: Ramon Diaz-Uriarte and Oscar M. Rueda . Wavelet-based aCGH smoothing code from Li Hsu and Douglas Grove . Imagemap code from Barry Rowlingson . HaarSeg code from Erez Ben-Yaacov; downloaded from . Maintainer: Ramon Diaz-Uriarte source.ver: src/contrib/ADaCGH2_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ADaCGH2_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ADaCGH2_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ADaCGH2_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ADaCGH2_2.4.0.tgz vignettes: vignettes/ADaCGH2/inst/doc/ADaCGH2-long-examples.pdf, vignettes/ADaCGH2/inst/doc/ADaCGH2.pdf, vignettes/ADaCGH2/inst/doc/benchmarks.pdf vignetteTitles: ADaCGH2-long-examples.pdf, ADaCGH2 Overview, benchmarks.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ADaCGH2/inst/doc/ADaCGH2.R Package: adSplit Version: 1.34.0 Depends: R (>= 2.1.0), methods (>= 2.1.0) Imports: AnnotationDbi, Biobase (>= 1.5.12), cluster (>= 1.9.1), GO.db (>= 1.8.1), graphics, grDevices, KEGG.db (>= 1.8.1), methods, multtest (>= 1.6.0), stats (>= 2.1.0) Suggests: golubEsets (>= 1.0), vsn (>= 1.5.0), hu6800.db (>= 1.8.1) License: GPL (>= 2) Archs: i386, x64 MD5sum: ddd955fb91a6d9907a24341e40281d1f NeedsCompilation: yes Title: Annotation-Driven Clustering Description: This package implements clustering of microarray gene expression profiles according to functional annotations. For each term genes are annotated to, splits into two subclasses are computed and a significance of the supporting gene set is determined. biocViews: Microarray, Clustering Author: Claudio Lottaz, Joern Toedling Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/adSplit_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/adSplit_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/adSplit_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/adSplit_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/adSplit_1.34.0.tgz vignettes: vignettes/adSplit/inst/doc/tr_2005_02.pdf vignetteTitles: Annotation-Driven Clustering hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/adSplit/inst/doc/tr_2005_02.R Package: affxparser Version: 1.36.0 Depends: R (>= 2.6.0) Suggests: R.utils (>= 1.29.8), AffymetrixDataTestFiles License: LGPL (>= 2) Archs: i386, x64 MD5sum: 962b5d52adae87e1027b07135085e975 NeedsCompilation: yes Title: Affymetrix File Parsing SDK Description: Package for parsing Affymetrix files (CDF, CEL, CHP, BPMAP, BAR). It provides methods for fast and memory efficient parsing of Affymetrix files using the Affymetrix' Fusion SDK. Both ASCII- and binary-based files are supported. Currently, there are methods for reading chip definition file (CDF) and a cell intensity file (CEL). These files can be read either in full or in part. For example, probe signals from a few probesets can be extracted very quickly from a set of CEL files into a convenient list structure. biocViews: Infrastructure, DataImport Author: Henrik Bengtsson [aut], James Bullard [aut], Robert Gentleman [ctb], Kasper Daniel Hansen [aut, cre], Martin Morgan [ctb] Maintainer: Kasper Daniel Hansen source.ver: src/contrib/affxparser_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affxparser_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affxparser_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affxparser_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affxparser_1.36.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: ITALICS, pdInfoBuilder, rMAT, Starr importsMe: affyILM, AffyTiling, cn.farms, GeneRegionScan, ITALICS, oligo, rMAT Package: affy Version: 1.42.3 Depends: R (>= 2.8.0), BiocGenerics (>= 0.1.12), Biobase (>= 2.5.5) Imports: affyio (>= 1.13.3), BiocInstaller, graphics, grDevices, methods, preprocessCore, stats, utils, zlibbioc LinkingTo: preprocessCore Suggests: tkWidgets (>= 1.19.0), affydata, widgetTools License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: e9dbe1e70f27fab2378db2266ac473c7 NeedsCompilation: yes Title: Methods for Affymetrix Oligonucleotide Arrays Description: The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it. biocViews: Microarray, OneChannel, Preprocessing Author: Rafael A. Irizarry , Laurent Gautier , Benjamin Milo Bolstad , and Crispin Miller with contributions from Magnus Astrand , Leslie M. Cope , Robert Gentleman, Jeff Gentry, Conrad Halling , Wolfgang Huber, James MacDonald , Benjamin I. P. Rubinstein, Christopher Workman , John Zhang Maintainer: Rafael A. Irizarry source.ver: src/contrib/affy_1.42.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/affy_1.42.3.zip win64.binary.ver: bin/windows64/contrib/3.1/affy_1.42.3.zip mac.binary.ver: bin/macosx/contrib/3.1/affy_1.42.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affy_1.42.3.tgz vignettes: vignettes/affy/inst/doc/affy.pdf, vignettes/affy/inst/doc/builtinMethods.pdf, vignettes/affy/inst/doc/customMethods.pdf, vignettes/affy/inst/doc/vim.pdf vignetteTitles: 1. Primer, 2. Built-in Processing Methods, 3. Custom Processing Methods, 4. Import Methods hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affy/inst/doc/affy.R, vignettes/affy/inst/doc/builtinMethods.R, vignettes/affy/inst/doc/customMethods.R, vignettes/affy/inst/doc/vim.R dependsOnMe: affyContam, affycoretools, AffyExpress, affylmGUI, affyPara, affypdnn, affyPLM, affyQCReport, AffyRNADegradation, altcdfenvs, arrayMvout, ArrayTools, bgx, Cormotif, DrugVsDisease, dualKS, ExiMiR, farms, frmaTools, gcrma, LMGene, logitT, maskBAD, MLP, panp, plw, prebs, puma, qpcrNorm, ReadqPCR, RefPlus, rHVDM, Risa, RPA, SCAN.UPC, simpleaffy, sscore, Starr, webbioc importsMe: affyILM, affyQCReport, AffyTiling, ArrayExpress, arrayQualityMetrics, ArrayTools, CAFE, ChIPXpress, Cormotif, farms, ffpe, frma, gcrma, GEOsubmission, Harshlight, HTqPCR, lumi, LVSmiRNA, makecdfenv, MSnbase, PECA, plier, plw, puma, pvac, simpleaffy, tilingArray, TurboNorm, virtualArray, vsn, waveTiling suggestsMe: AnnotationForge, beadarray, beadarraySNP, BiocCaseStudies, BiocGenerics, Biostrings, BufferedMatrixMethods, categoryCompare, ecolitk, ExpressionView, factDesign, gCMAPWeb, GeneRegionScan, limma, made4, MLSeq, oneChannelGUI, piano, PREDA, qcmetrics, siggenes Package: affycomp Version: 1.40.0 Depends: R (>= 2.13.0), methods, Biobase (>= 2.3.3) Suggests: splines, affycompData License: GPL (>= 2) MD5sum: 120b21b8b8335547c30130c1310b32f1 NeedsCompilation: no Title: Graphics Toolbox for Assessment of Affymetrix Expression Measures Description: The package contains functions that can be used to compare expression measures for Affymetrix Oligonucleotide Arrays. biocViews: OneChannel, Microarray, Preprocessing Author: Rafael A. Irizarry and Zhijin Wu with contributions from Simon Cawley Maintainer: Rafael A. Irizarry source.ver: src/contrib/affycomp_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affycomp_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affycomp_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affycomp_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affycomp_1.40.0.tgz vignettes: vignettes/affycomp/inst/doc/affycomp.pdf vignetteTitles: affycomp primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affycomp/inst/doc/affycomp.R Package: AffyCompatible Version: 1.24.1 Depends: R (>= 2.7.0), XML (>= 2.8-1), RCurl (>= 0.8-1), methods Imports: Biostrings License: Artistic-2.0 MD5sum: 3032330233df58ac263609cf1f476979 NeedsCompilation: no Title: Affymetrix GeneChip software compatibility Description: This package provides an interface to Affymetrix chip annotation and sample attribute files. The package allows an easy way for users to download and manage local data bases of Affynmetrix NetAffx annotation files. The package also provides access to GeneChip Operating System (GCOS) and GeneChip Command Console (AGCC)-compatible sample annotation files. biocViews: Infrastructure, Microarray, OneChannel Author: Martin Morgan, Robert Gentleman Maintainer: Martin Morgan source.ver: src/contrib/AffyCompatible_1.24.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/AffyCompatible_1.24.1.zip win64.binary.ver: bin/windows64/contrib/3.1/AffyCompatible_1.24.1.zip mac.binary.ver: bin/macosx/contrib/3.1/AffyCompatible_1.24.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AffyCompatible_1.24.1.tgz vignettes: vignettes/AffyCompatible/inst/doc/MAGEAndARR.pdf, vignettes/AffyCompatible/inst/doc/NetAffxResource.pdf vignetteTitles: Retrieving MAGE and ARR sample attributes, Annotation retrieval with NetAffxResource hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyCompatible/inst/doc/MAGEAndARR.R, vignettes/AffyCompatible/inst/doc/NetAffxResource.R importsMe: IdMappingRetrieval Package: affyContam Version: 1.22.0 Depends: R (>= 2.7.0), tools, methods, utils, Biobase, affy, affydata License: Artistic-2.0 MD5sum: 475d228526821f44365f28962cd2ab13 NeedsCompilation: no Title: structured corruption of affymetrix cel file data Description: structured corruption of cel file data to demonstrate QA effectiveness biocViews: Infrastructure Author: V. Carey Maintainer: V. Carey source.ver: src/contrib/affyContam_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyContam_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affyContam_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affyContam_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyContam_1.22.0.tgz vignettes: vignettes/affyContam/inst/doc/affyContam.pdf vignetteTitles: affy contamination tools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyContam/inst/doc/affyContam.R Package: affycoretools Version: 1.36.1 Depends: affy, Biobase, GO.db Imports: biomaRt, limma, GOstats, annotate, annaffy, genefilter, gcrma, splines, xtable, AnnotationDbi, lattice, gplots, R2HTML, oligoClasses, ReportingTools, hwriter Suggests: affydata, hgfocuscdf, rgl, BiocStyle, knitr License: Artistic-2.0 MD5sum: eab3e820b940176e1f7378a47468cfe9 NeedsCompilation: no Title: Functions useful for those doing repetitive analyses with Affymetrix GeneChips. Description: Various wrapper functions that have been written to streamline the more common analyses that a core Biostatistician might see. biocViews: ReportWriting, Microarray, OneChannel, GeneExpression Author: James W. MacDonald Maintainer: James W. MacDonald VignetteBuilder: knitr source.ver: src/contrib/affycoretools_1.36.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/affycoretools_1.36.1.zip win64.binary.ver: bin/windows64/contrib/3.1/affycoretools_1.36.1.zip mac.binary.ver: bin/macosx/contrib/3.1/affycoretools_1.36.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affycoretools_1.36.1.tgz vignettes: vignettes/affycoretools/inst/doc/affycoretools_biomaRt.pdf, vignettes/affycoretools/inst/doc/affycoretools.pdf vignetteTitles: affycoretools biomaRt Integration, affycoretools Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affycoretools/inst/doc/affycoretools_biomaRt.R, vignettes/affycoretools/inst/doc/affycoretools.R Package: AffyExpress Version: 1.30.0 Depends: R (>= 2.10), affy (>= 1.23.4), limma Suggests: simpleaffy, R2HTML, affyPLM, hgu95av2cdf, hgu95av2, test3cdf, genefilter, estrogen, annaffy, gcrma License: LGPL MD5sum: efd76f30ef400c49b912a58f6708f9bd NeedsCompilation: no Title: Affymetrix Quality Assessment and Analysis Tool Description: The purpose of this package is to provide a comprehensive and easy-to-use tool for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data. biocViews: Microarray, OneChannel, QualityControl, Preprocessing, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu , Xuejun Arthur Li Maintainer: Xuejun Arthur Li source.ver: src/contrib/AffyExpress_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AffyExpress_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AffyExpress_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AffyExpress_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AffyExpress_1.30.0.tgz vignettes: vignettes/AffyExpress/inst/doc/AffyExpress.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyExpress/inst/doc/AffyExpress.R Package: affyILM Version: 1.16.0 Depends: R (>= 2.10.0), methods, gcrma Imports: affxparser (>= 1.16.0), affy, graphics, methods, Biobase Suggests: AffymetrixDataTestFiles License: GPL version 3 MD5sum: 18a3237b1c47fcc221a24158e03d3d70 NeedsCompilation: no Title: Linear Model of background subtraction and the Langmuir isotherm Description: affyILM is a preprocessing tool which estimates gene expression levels for Affymetrix Gene Chips. Input from physical chemistry is employed to first background subtract intensities before calculating concentrations on behalf of the Langmuir model. biocViews: Microarray, OneChannel, Preprocessing Author: K. Myriam Kroll, Fabrice Berger, Gerard Barkema, Enrico Carlon Maintainer: Myriam Kroll and Fabrice Berger source.ver: src/contrib/affyILM_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyILM_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affyILM_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affyILM_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyILM_1.16.0.tgz vignettes: vignettes/affyILM/inst/doc/affyILM.pdf vignetteTitles: affyILM1.3.0 hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyILM/inst/doc/affyILM.R Package: affyio Version: 1.32.0 Depends: R (>= 2.6.0) Imports: zlibbioc License: LGPL (>= 2) Archs: i386, x64 MD5sum: e6e6fe070e62d108461904c0a9b9b737 NeedsCompilation: yes Title: Tools for parsing Affymetrix data files Description: Routines for parsing Affymetrix data files based upon file format information. Primary focus is on accessing the CEL and CDF file formats. biocViews: Microarray, DataImport, Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/affyio_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyio_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affyio_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affyio_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyio_1.32.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE dependsOnMe: affylmGUI, affyPara, makecdfenv, SCAN.UPC, sscore importsMe: affy, crlmm, ExiMiR, gcrma, oligo, oligoClasses, puma suggestsMe: BufferedMatrixMethods Package: affylmGUI Version: 1.38.0 Depends: limma, tcltk, affy, BiocInstaller, affyio, affy, tkrplot, affyPLM, R2HTML, xtable, gcrma, affyPLM, AnnotationDbi License: LGPL MD5sum: 5ae23cd86e6215feed863adfee44de6f NeedsCompilation: no Title: GUI for affy analysis using limma package Description: A Graphical User Interface for affy analysis using the limma Microarray package biocViews: Microarray, OneChannel, DataImport, QualityControl, Preprocessing, DifferentialExpression, MultipleComparison, GUI Author: James Wettenhall and Ken Simpson Division of Genetics and Bioinformatics, WEHI. Maintainer: Keith Satterley URL: http://bioinf.wehi.edu.au/affylmGUI/ source.ver: src/contrib/affylmGUI_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affylmGUI_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affylmGUI_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affylmGUI_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affylmGUI_1.38.0.tgz vignettes: vignettes/affylmGUI/inst/doc/affylmGUI.pdf, vignettes/affylmGUI/inst/doc/extract.pdf vignetteTitles: affylmGUI Vignette, Extracting affy and limma objects from affylmGUI files hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affylmGUI/inst/doc/affylmGUI.R, vignettes/affylmGUI/inst/doc/extract.R htmlDocs: vignettes/affylmGUI/inst/doc/about.html, vignettes/affylmGUI/inst/doc/CustMenu.html, vignettes/affylmGUI/inst/doc/index.html, vignettes/affylmGUI/inst/doc/windowsFocus.html htmlTitles: "About affylmGUI", "Customizing the menus in affylmGUI (for Advanced users)", "affylmGUI Documentation", "Troubleshooting Window Focus Problems" dependsOnMe: oneChannelGUI Package: affyPara Version: 1.24.0 Depends: R (>= 2.5.0), methods, affy (>= 1.20.0), snow (>= 0.2-3), vsn (>= 3.6.0), aplpack (>= 1.1.1), affyio Suggests: affydata Enhances: affy License: GPL-3 MD5sum: 4e3b596ea7c616b5985f0582302f0549 NeedsCompilation: no Title: Parallelized preprocessing methods for Affymetrix Oligonucleotide Arrays Description: The package contains parallelized functions for exploratory oligonucleotide array analysis. The package is designed for large numbers of microarray data. biocViews: Microarray, Preprocessing Author: Markus Schmidberger , Esmeralda Vicedo , Ulrich Mansmann Maintainer: Markus Schmidberger URL: http://www.ibe.med.uni-muenchen.de source.ver: src/contrib/affyPara_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyPara_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affyPara_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affyPara_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyPara_1.24.0.tgz vignettes: vignettes/affyPara/inst/doc/affyPara.pdf, vignettes/affyPara/inst/doc/vsnStudy.pdf vignetteTitles: Parallelized affy functions for preprocessing, Simulation Study for VSN Add-On Normalization and Subsample Size hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyPara/inst/doc/affyPara.R, vignettes/affyPara/inst/doc/vsnStudy.R Package: affypdnn Version: 1.38.0 Depends: R (>= 2.13.0), affy (>= 1.5) Suggests: affydata, hgu95av2probe License: LGPL MD5sum: 056436588b4a9e72b3c9d7750b47f51e NeedsCompilation: no Title: Probe Dependent Nearest Neighbours (PDNN) for the affy package Description: The package contains functions to perform the PDNN method described by Li Zhang et al. biocViews: OneChannel, Microarray, Preprocessing Author: H. Bjorn Nielsen and Laurent Gautier (Many thanks to Li Zhang early communications about the existence of the PDNN program and related publications). Maintainer: Laurent Gautier source.ver: src/contrib/affypdnn_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affypdnn_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affypdnn_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affypdnn_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affypdnn_1.38.0.tgz vignettes: vignettes/affypdnn/inst/doc/affypdnn.pdf vignetteTitles: affypdnn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affypdnn/inst/doc/affypdnn.R Package: affyPLM Version: 1.40.1 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), affy (>= 1.11.0), Biobase (>= 2.17.8), gcrma, stats, preprocessCore (>= 1.5.1) Imports: BiocGenerics, zlibbioc, graphics, grDevices, methods LinkingTo: preprocessCore Suggests: affydata, MASS License: GPL (>= 2) Archs: i386, x64 MD5sum: cd6ceb1c0b88c263bc54c90f741b8fbb NeedsCompilation: yes Title: Methods for fitting probe-level models Description: A package that extends and improves the functionality of the base affy package. Routines that make heavy use of compiled code for speed. Central focus is on implementation of methods for fitting probe-level models and tools using these models. PLM based quality assessment tools. biocViews: Microarray, OneChannel, Preprocessing, QualityControl Author: Ben Bolstad Maintainer: Ben Bolstad URL: http://bmbolstad.com source.ver: src/contrib/affyPLM_1.40.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyPLM_1.40.1.zip win64.binary.ver: bin/windows64/contrib/3.1/affyPLM_1.40.1.zip mac.binary.ver: bin/macosx/contrib/3.1/affyPLM_1.40.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyPLM_1.40.1.tgz vignettes: vignettes/affyPLM/inst/doc/AffyExtensions.pdf, vignettes/affyPLM/inst/doc/MAplots.pdf, vignettes/affyPLM/inst/doc/QualityAssess.pdf, vignettes/affyPLM/inst/doc/ThreeStep.pdf vignetteTitles: affyPLM: Fitting Probe Level Models, affyPLM: Advanced use of the MAplot function, affyPLM: Model Based QC Assessment of Affymetrix GeneChips, affyPLM: the threestep function hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyPLM/inst/doc/AffyExtensions.R, vignettes/affyPLM/inst/doc/MAplots.R, vignettes/affyPLM/inst/doc/QualityAssess.R, vignettes/affyPLM/inst/doc/ThreeStep.R dependsOnMe: affylmGUI, RefPlus importsMe: affyQCReport, arrayQualityMetrics, virtualArray suggestsMe: AffyExpress, arrayMvout, ArrayTools, BiocCaseStudies, BiocGenerics, ELBOW, frmaTools, metahdep, oneChannelGUI, piano Package: affyQCReport Version: 1.42.0 Depends: Biobase (>= 1.13.16), affy, lattice Imports: affy, affyPLM, Biobase, genefilter, graphics, grDevices, lattice, RColorBrewer, simpleaffy, stats, utils, xtable Suggests: tkWidgets (>= 1.5.23), affydata (>= 1.4.1) License: LGPL (>= 2) MD5sum: f81381923a16728fef43afe59c9574a9 NeedsCompilation: no Title: QC Report Generation for affyBatch objects Description: This package creates a QC report for an AffyBatch object. The report is intended to allow the user to quickly assess the quality of a set of arrays in an AffyBatch object. biocViews: Microarray,OneChannel,QualityControl Author: Craig Parman , Conrad Halling , Robert Gentleman Maintainer: Craig Parman source.ver: src/contrib/affyQCReport_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/affyQCReport_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/affyQCReport_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/affyQCReport_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/affyQCReport_1.42.0.tgz vignettes: vignettes/affyQCReport/inst/doc/affyQCReport.pdf vignetteTitles: affyQCReport: Methods for Generating Affymetrix QC Reports hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/affyQCReport/inst/doc/affyQCReport.R suggestsMe: BiocCaseStudies Package: AffyRNADegradation Version: 1.10.0 Depends: R (>= 2.9.0), methods, affy Suggests: AmpAffyExample License: GPL-2 MD5sum: e8ddb7c3cf2044b95b771359957d8927 NeedsCompilation: no Title: Analyze and correct probe positional bias in microarray data due to RNA degradation Description: The package helps with the assessment and correction of RNA degradation effects in Affymetrix 3' expression arrays. The parameter d gives a robust and accurate measure of RNA integrity. The correction removes the probe positional bias, and thus improves comparability of samples that are affected by RNA degradation. biocViews: GeneExpression, Microarray, OneChannel, Preprocessing, QualityControl Author: Mario Fasold Maintainer: Mario Fasold source.ver: src/contrib/AffyRNADegradation_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AffyRNADegradation_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AffyRNADegradation_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AffyRNADegradation_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AffyRNADegradation_1.10.0.tgz vignettes: vignettes/AffyRNADegradation/inst/doc/vignette.pdf vignetteTitles: AffyRNADegradation Example hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyRNADegradation/inst/doc/vignette.R Package: AffyTiling Version: 1.22.1 Depends: R (>= 2.6) Imports: affxparser, affy (>= 1.16), stats, utils, preprocessCore License: GPL (>= 2) Archs: i386, x64 MD5sum: 4dac7c2f837807f6abd43e3bf5aea3e5 NeedsCompilation: yes Title: Easy extraction of individual probes in Affymetrix tiling arrays Description: This package provides easy, fast functions for the extraction and annotation of individual probes from Affymetrix tiling arrays. biocViews: Microarray, Preprocessing Author: Charles G. Danko Maintainer: Charles G. Danko source.ver: src/contrib/AffyTiling_1.22.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/AffyTiling_1.22.1.zip win64.binary.ver: bin/windows64/contrib/3.1/AffyTiling_1.22.1.zip mac.binary.ver: bin/macosx/contrib/3.1/AffyTiling_1.22.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AffyTiling_1.22.1.tgz vignettes: vignettes/AffyTiling/inst/doc/AffyTiling.pdf vignetteTitles: AffyTiling hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AffyTiling/inst/doc/AffyTiling.R Package: AGDEX Version: 1.12.0 Depends: R (>= 2.10), Biobase, GSEABase Imports: stats License: GPL Version 2 or later MD5sum: fc311880979c4406f5070cb72daf4ad5 NeedsCompilation: no Title: Agreement of Differential Expression Analysis Description: A tool to evaluate agreement of differential expression for cross-species genomics biocViews: Microarray, Genetics, GeneExpression Author: Stan Pounds ; Cuilan Lani Gao Maintainer: Cuilan lani Gao source.ver: src/contrib/AGDEX_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AGDEX_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AGDEX_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AGDEX_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AGDEX_1.12.0.tgz vignettes: vignettes/AGDEX/inst/doc/AGDEX.pdf vignetteTitles: AGDEX.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AGDEX/inst/doc/AGDEX.R Package: agilp Version: 3.6.0 Depends: R (>= 2.14.0) License: GPL-3 MD5sum: 6cca7b88945acdb07d2f2b56a3696897 NeedsCompilation: no Title: Agilent expression array processing package Description: provides a pipeline for the low-level analysis of gene expression microarray data, primarily Agilent data biocViews: StatisticalMethod Author: Benny Chain Maintainer: Benny Chain source.ver: src/contrib/agilp_3.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/agilp_3.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/agilp_3.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/agilp_3.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/agilp_3.6.0.tgz vignettes: vignettes/agilp/inst/doc/agilp_manual.pdf vignetteTitles: An R Package for processing expression microarray data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/agilp/inst/doc/agilp_manual.R Package: AgiMicroRna Version: 2.14.0 Depends: R (>= 2.10),methods,Biobase,limma,affy (>= 1.22),preprocessCore,affycoretools Imports: Biobase Suggests: geneplotter,marray,gplots,gtools,gdata,codelink License: GPL-3 MD5sum: d69cc567992e3856070e4eb5bd629162 NeedsCompilation: no Title: Processing and Differential Expression Analysis of Agilent microRNA chips Description: Processing and Analysis of Agilent microRNA data biocViews: Microarray, AgilentChip, OneChannel, Preprocessing, DifferentialExpression Author: Pedro Lopez-Romero Maintainer: Pedro Lopez-Romero source.ver: src/contrib/AgiMicroRna_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AgiMicroRna_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AgiMicroRna_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AgiMicroRna_2.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AgiMicroRna_2.14.0.tgz vignettes: vignettes/AgiMicroRna/inst/doc/AgiMicroRna.pdf vignetteTitles: AgiMicroRna hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AgiMicroRna/inst/doc/AgiMicroRna.R Package: AllelicImbalance Version: 1.2.0 Depends: GenomicAlignments, GenomicRanges, R (>= 3.0.0) Imports: methods, BiocGenerics, IRanges, Biostrings, Rsamtools, GenomicFeatures, AnnotationDbi Suggests: RUnit, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene,SNPlocs.Hsapiens.dbSNP.20120608 License: GPL-3 MD5sum: 1d6cea0d4b48453132057ab73f726754 NeedsCompilation: no Title: Investigates allele specific expression Description: Provides a framework for allelic specific expression investigation using RNA-seq data biocViews: Genetics, Infrastructure, Allelic Imbalance, AI, ASE, Sequencing Author: Jesper R Gadin, Lasse Folkersen Maintainer: Jesper R Gadin URL: https://github.com/pappewaio/AllelicImbalance source.ver: src/contrib/AllelicImbalance_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AllelicImbalance_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AllelicImbalance_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AllelicImbalance_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AllelicImbalance_1.2.0.tgz vignettes: vignettes/AllelicImbalance/inst/doc/AllelicImbalance.pdf vignetteTitles: AllelicImbalance hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AllelicImbalance/inst/doc/AllelicImbalance.R Package: alsace Version: 1.0.0 Depends: R (>= 2.10), ALS, ptw (>= 1.0.6) Suggests: lattice License: GPL (>= 2) MD5sum: 7c4c5c3ab04b68a2a2d9038d78c7e9bd NeedsCompilation: no Title: ALS for the Automatic Chemical Exploration of mixtures Description: Alternating Least Squares (or Multivariate Curve Resolution) for analytical chemical data, in particular hyphenated data where the first direction is a retention time axis, and the second a spectral axis. Package builds on the basic als function from the ALS package and adds functionality for high-throughput analysis, including definition of time windows, clustering of profiles, retention time correction, etcetera. Author: Ron Wehrens Maintainer: Ron Wehrens source.ver: src/contrib/alsace_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/alsace_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/alsace_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/alsace_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/alsace_1.0.0.tgz vignettes: vignettes/alsace/inst/doc/alsace.pdf vignetteTitles: alsace hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/alsace/inst/doc/alsace.R Package: altcdfenvs Version: 2.26.0 Depends: R (>= 2.7), methods, BiocGenerics (>= 0.1.0), Biobase (>= 2.15.1), affy, makecdfenv, Biostrings, hypergraph Suggests: plasmodiumanophelescdf, hgu95acdf, hgu133aprobe, hgu133a.db, hgu133acdf, Rgraphviz, RColorBrewer License: GPL (>= 2) MD5sum: 41254fd73605d81eb0d6c30fc28642c9 NeedsCompilation: no Title: alternative CDF environments (aka probeset mappings) Description: Convenience data structures and functions to handle cdfenvs biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Annotation, ProprietaryPlatforms, Transcription Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/altcdfenvs_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/altcdfenvs_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/altcdfenvs_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/altcdfenvs_2.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/altcdfenvs_2.26.0.tgz vignettes: vignettes/altcdfenvs/inst/doc/altcdfenvs.pdf, vignettes/altcdfenvs/inst/doc/modify.pdf, vignettes/altcdfenvs/inst/doc/ngenomeschips.pdf vignetteTitles: altcdfenvs, affy primer, affy primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/altcdfenvs/inst/doc/altcdfenvs.R, vignettes/altcdfenvs/inst/doc/modify.R, vignettes/altcdfenvs/inst/doc/ngenomeschips.R importsMe: Harshlight Package: ampliQueso Version: 1.2.0 Depends: R (>= 2.15.0), rnaSeqMap (>= 2.17.1), knitr, rgl, ggplot2, gplots, parallel, doParallel, foreach, VariantAnnotation,genefilter,statmod,xtable Imports: edgeR, DESeq, samr License: GPL-2 MD5sum: 30a4d48956775a298cee8210ca594bf5 NeedsCompilation: no Title: Analysis of amplicon enrichment panels Description: The package provides tools and reports for the analysis of amplicon sequencing panels, such as AmpliSeq biocViews: ReportWriting, Transcription, GeneExpression, DifferentialExpression, Sequencing, RNASeq, Visualization Author: Alicja Szabelska ; Marek Wiewiorka ; Michal Okoniewski Maintainer: Michal Okoniewski source.ver: src/contrib/ampliQueso_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ampliQueso_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ampliQueso_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ampliQueso_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ampliQueso_1.2.0.tgz vignettes: vignettes/ampliQueso/inst/doc/ampliQueso.pdf vignetteTitles: ampliQueso primer hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ampliQueso/inst/doc/ampliQueso.R Package: annaffy Version: 1.36.0 Depends: R (>= 2.5.0), methods, Biobase, GO.db, KEGG.db Imports: AnnotationDbi (>= 0.1.15) Suggests: hgu95av2.db, multtest, tcltk License: LGPL MD5sum: 443a2bd7d54ab5225294cc95baab10e6 NeedsCompilation: no Title: Annotation tools for Affymetrix biological metadata Description: Functions for handling data from Bioconductor Affymetrix annotation data packages. Produces compact HTML and text reports including experimental data and URL links to many online databases. Allows searching biological metadata using various criteria. biocViews: OneChannel, Microarray, Annotation, GO, Pathways, ReportWriting Author: Colin A. Smith Maintainer: Colin A. Smith source.ver: src/contrib/annaffy_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/annaffy_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/annaffy_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/annaffy_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/annaffy_1.36.0.tgz vignettes: vignettes/annaffy/inst/doc/annaffy.pdf vignetteTitles: annaffy Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annaffy/inst/doc/annaffy.R dependsOnMe: a4Base, a4Reporting, PGSEA, webbioc importsMe: affycoretools suggestsMe: AffyExpress, ArrayTools, BiocCaseStudies Package: annmap Version: 1.6.0 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: DBI, RMySQL (>= 0.6-0), digest, Biobase, grid, lattice, Rsamtools, genefilter, IRanges, BiocGenerics Suggests: RUnit, rjson, Gviz License: GPL-2 MD5sum: 85535baf6521033c7246d48a6f8cf0c6 NeedsCompilation: no Title: Genome annotation and visualisation package pertaining to Affymetrix arrays and NGS analysis. Description: annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided. Underlying data are from Ensembl. biocViews: Annotation, Microarray, OneChannel, ReportWriting, Transcription, Visualization Author: Tim Yates Maintainer: Tim Yates URL: http://annmap.cruk.manchester.ac.uk source.ver: src/contrib/annmap_1.6.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/annmap_1.6.0.tgz vignettes: vignettes/annmap/inst/doc/annmap.pdf, vignettes/annmap/inst/doc/cookbook.pdf, vignettes/annmap/inst/doc/INSTALL.pdf vignetteTitles: annmap primer, The Annmap Cookbook, annmap installation instruction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annmap/inst/doc/annmap.R, vignettes/annmap/inst/doc/cookbook.R, vignettes/annmap/inst/doc/INSTALL.R Package: annotate Version: 1.42.1 Depends: R (>= 2.10), AnnotationDbi (>= 0.1.15) Imports: Biobase, AnnotationDbi, DBI, xtable, graphics, utils, stats, methods, XML (>= 0.92-2), BiocGenerics (>= 0.1.13) Suggests: Biobase, hgu95av2.db, genefilter, Biostrings (>= 2.25.10), rae230a.db, rae230aprobe, tkWidgets, GO.db, org.Hs.eg.db, XML (>= 0.92-2), org.Mm.eg.db, hom.Hs.inp.db, humanCHRLOC, Rgraphviz, RUnit, License: Artistic-2.0 MD5sum: b772f65c2b792e8297a3b233b23f2304 NeedsCompilation: no Title: Annotation for microarrays Description: Using R enviroments for annotation. biocViews: Annotation, Pathways, GO Author: R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/annotate_1.42.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/annotate_1.42.1.zip win64.binary.ver: bin/windows64/contrib/3.1/annotate_1.42.1.zip mac.binary.ver: bin/macosx/contrib/3.1/annotate_1.42.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/annotate_1.42.1.tgz vignettes: vignettes/annotate/inst/doc/annotate.pdf, vignettes/annotate/inst/doc/chromLoc.pdf, vignettes/annotate/inst/doc/GOusage.pdf, vignettes/annotate/inst/doc/prettyOutput.pdf, vignettes/annotate/inst/doc/query.pdf, vignettes/annotate/inst/doc/useDataPkgs.pdf, vignettes/annotate/inst/doc/useHomology.pdf, vignettes/annotate/inst/doc/useProbeInfo.pdf vignetteTitles: Annotation Overview, HowTo: use chromosomal information, Basic GO Usage, HowTo: Get HTML Output, HOWTO: Use the online query tools, Using Data Packages, Using the homology package, Using Affymetrix Probe Level Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annotate/inst/doc/annotate.R, vignettes/annotate/inst/doc/chromLoc.R, vignettes/annotate/inst/doc/GOusage.R, vignettes/annotate/inst/doc/prettyOutput.R, vignettes/annotate/inst/doc/query.R, vignettes/annotate/inst/doc/useDataPkgs.R, vignettes/annotate/inst/doc/useHomology.R, vignettes/annotate/inst/doc/useProbeInfo.R dependsOnMe: ChromHeatMap, GeneAnswers, geneplotter, GOSim, GSEABase, idiogram, macat, MineICA, MLInterfaces, PCpheno, phenoTest, PREDA, RpsiXML, ScISI importsMe: affycoretools, CAFE, Category, categoryCompare, codelink, DrugVsDisease, gCMAP, gCMAPWeb, GeneAnswers, genefilter, GlobalAncova, globaltest, GOstats, lumi, methyAnalysis, methylumi, phenoTest, qpgraph, ScISI, splicegear, tigre suggestsMe: BiocCaseStudies, biomaRt, GlobalAncova, globaltest, GOstats, GSEAlm, maigesPack, metagenomeSeq, MLP, oneChannelGUI, siggenes Package: AnnotationDbi Version: 1.26.1 Depends: R (>= 2.7.0), methods, utils, BiocGenerics (>= 0.5.4), Biobase (>= 1.17.0), GenomeInfoDb(>= 0.99.17) Imports: methods, utils, DBI, RSQLite, BiocGenerics, Biobase, IRanges Suggests: DBI (>= 0.2-4), RSQLite (>= 0.6-4), hgu95av2.db, GO.db, org.Sc.sgd.db, org.At.tair.db, KEGG.db, RUnit, TxDb.Hsapiens.UCSC.hg19.knownGene, hom.Hs.inp.db, org.Hs.eg.db, seqnames.db, reactome.db, AnnotationForge, graph, org.TguttataTestingSubset.eg.db, BiocStyle, knitr License: Artistic-2.0 MD5sum: b545c34faf86540d18faacb46aef0fa1 NeedsCompilation: no Title: Annotation Database Interface Description: Provides user interface and database connection code for annotation data packages using SQLite data storage. biocViews: Annotation, Infrastructure Author: Herve Pages, Marc Carlson, Seth Falcon, Nianhua Li Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/AnnotationDbi_1.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/AnnotationDbi_1.26.1.zip win64.binary.ver: bin/windows64/contrib/3.1/AnnotationDbi_1.26.1.zip mac.binary.ver: bin/macosx/contrib/3.1/AnnotationDbi_1.26.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AnnotationDbi_1.26.1.tgz vignettes: vignettes/AnnotationDbi/inst/doc/AnnotationDbi.pdf, vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.pdf vignetteTitles: How to use bimaps from the ".db" annotation packages, AnnotationDbi: Introduction To Bioconductor Annotation Packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationDbi/inst/doc/AnnotationDbi.R, vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.R dependsOnMe: a4Base, a4Preproc, affylmGUI, annotate, AnnotationForge, AnnotationFuncs, attract, Category, chimera, ChromHeatMap, customProDB, eisa, ExpressionView, GenomicFeatures, GOFunction, goProfiles, MLP, OrganismDbi, PADOG, PAnnBuilder, pathRender, PGSEA, Resourcerer, RpsiXML, safe, topGO importsMe: adSplit, affycoretools, AllelicImbalance, annaffy, annotate, AnnotationHub, attract, beadarray, biomaRt, BioNet, biovizBase, CancerMutationAnalysis, Category, categoryCompare, ChIPpeakAnno, ChIPseeker, clusterProfiler, CoCiteStats, customProDB, domainsignatures, DOSE, ExpressionView, FunciSNP, gage, gCMAP, gCMAPWeb, genefilter, geneplotter, GGBase, GGtools, GlobalAncova, globaltest, GOFunction, GOSemSim, goseq, GOSim, GOstats, goTools, graphite, GSEABase, Gviz, HTSanalyzeR, interactiveDisplay, lumi, MeSHDbi, methyAnalysis, methylumi, MineICA, MiRaGE, OrganismDbi, PADOG, PAnnBuilder, pathview, pcaGoPromoter, PCpheno, phenoTest, qpgraph, ReactomePA, REDseq, rTRM, ScISI, SLGI, tigre, topGO, UniProt.ws, VariantAnnotation, VariantFiltering, virtualArray suggestsMe: BiocCaseStudies, BiocGenerics, GeneAnswers, GeneRegionScan, GenomicRanges, limma, MmPalateMiRNA, neaGUI, oneChannelGUI, qcmetrics, sigPathway Package: AnnotationForge Version: 1.6.1 Depends: R (>= 2.7.0), methods, utils, BiocGenerics (>= 0.1.13), Biobase (>= 1.17.0), AnnotationDbi (>= 1.19.15), org.Hs.eg.db Imports: methods, utils, DBI, RSQLite, BiocGenerics, Biobase Suggests: DBI (>= 0.2-4), RSQLite (>= 0.6-4), XML, RCurl, hgu95av2.db, human.db0, affy, Homo.sapiens, hom.Hs.inp.db, GO.db, BiocStyle, knitr License: Artistic-2.0 MD5sum: 554e98263800ff11db321231e01b29e2 NeedsCompilation: no Title: Code for Building Annotation Database Packages Description: Provides code for generating Annotation packages and their databases. Packages produced are intended to be used with AnnotationDbi. biocViews: Annotation, Infrastructure Author: Marc Carlson, Herve Pages Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/AnnotationForge_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/AnnotationForge_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/AnnotationForge_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/AnnotationForge_1.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AnnotationForge_1.6.1.tgz vignettes: vignettes/AnnotationForge/inst/doc/makeProbePackage.pdf, vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.pdf, vignettes/AnnotationForge/inst/doc/SQLForge.pdf vignetteTitles: Creating probe packages, AnnotationForge: Creating select Interfaces for custom Annotation resources, SQLForge: An easy way to create a new annotation package with a standard database schema. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationForge/inst/doc/makeProbePackage.R, vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.R, vignettes/AnnotationForge/inst/doc/MakingNewOrganismPackages.R, vignettes/AnnotationForge/inst/doc/SQLForge.R htmlDocs: vignettes/AnnotationForge/inst/doc/MakingNewOrganismPackages.html htmlTitles: "Making New Organism Packages" importsMe: GOstats suggestsMe: AnnotationDbi Package: AnnotationFuncs Version: 1.14.0 Depends: R (>= 2.7.0), AnnotationDbi Suggests: org.Bt.eg.db, GO.db, org.Hs.eg.db, hom.Hs.inp.db License: GPL-2 MD5sum: 4054060855e9b31f0fe4b3dd67f5b181 NeedsCompilation: no Title: Annotation translation functions Description: Functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g. org.Bt.eg.db). biocViews: AnnotationData, Software Author: Stefan McKinnon Edwards Maintainer: Stefan McKinnon Edwards URL: http://www.iysik.com/index.php?page=annotation-functions source.ver: src/contrib/AnnotationFuncs_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AnnotationFuncs_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AnnotationFuncs_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AnnotationFuncs_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AnnotationFuncs_1.14.0.tgz vignettes: vignettes/AnnotationFuncs/inst/doc/AnnotationFuncsUserguide.pdf vignetteTitles: Annotation mapping functions hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: AnnotationHub Version: 1.4.0 Depends: IRanges Imports: methods, stats, utils, rjson, BiocGenerics, httr, BiocInstaller (>= 1.11.0), AnnotationDbi, GenomicRanges, interactiveDisplay (>= 1.0.23) Suggests: RUnit, RCurl, Rsamtools License: Artistic-2.0 MD5sum: 9e92963a275f507a6e0885b76a0aadd0 NeedsCompilation: no Title: A client for retrieving Bioconductor objects from AnnotationHub Description: A client for retrieving data from the Bioconductor AnnotationHub online services. biocViews: Annotation, Infrastructure Author: Marc Carlson, Sonali Arora Maintainer: Marc Carlson source.ver: src/contrib/AnnotationHub_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AnnotationHub_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AnnotationHub_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AnnotationHub_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AnnotationHub_1.4.0.tgz vignettes: vignettes/AnnotationHub/inst/doc/AnnotationHub.pdf, vignettes/AnnotationHub/inst/doc/AnnotationHubRecipes.pdf vignetteTitles: AnnotationHub: A client package for retrieving data from the AnnotationHub web service, How to write recipes for new resources for the AnnotationHub hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationHub/inst/doc/AnnotationHub.R, vignettes/AnnotationHub/inst/doc/AnnotationHubRecipes.R dependsOnMe: RefNet suggestsMe: GenomicRanges Package: annotationTools Version: 1.38.0 Imports: Biobase, stats License: GPL MD5sum: f58b1cbc1bbfb5fc5c44b49de41be31c NeedsCompilation: no Title: Annotate microarrays and perform cross-species gene expression analyses using flat file databases. Description: Functions to annotate microarrays, find orthologs, and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file database (plain text files). biocViews: Microarray, Annotation Author: Alexandre Kuhn Maintainer: Alexandre Kuhn source.ver: src/contrib/annotationTools_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/annotationTools_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/annotationTools_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/annotationTools_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/annotationTools_1.38.0.tgz vignettes: vignettes/annotationTools/inst/doc/annotationTools.pdf vignetteTitles: annotationTools Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/annotationTools/inst/doc/annotationTools.R Package: anota Version: 1.12.0 Depends: qvalue Imports: multtest, qvalue License: GPL-3 MD5sum: 14a525729ef94974cf33ee993becc955 NeedsCompilation: no Title: ANalysis Of Translational Activity (ANOTA). Description: Genome wide studies of translational control is emerging as a tool to study verious biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the levl of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e. differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallell the library performs a number of tests to assure that the data set is suitable for such analysis. biocViews: GeneExpression, DifferentialExpression, Microarray, Sequencing Author: Ola Larsson , Nahum Sonenberg , Robert Nadon Maintainer: Ola Larsson source.ver: src/contrib/anota_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/anota_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/anota_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/anota_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/anota_1.12.0.tgz vignettes: vignettes/anota/inst/doc/anota.pdf vignetteTitles: ANalysis Of Translational Activity (anota) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/anota/inst/doc/anota.R dependsOnMe: tRanslatome Package: antiProfiles Version: 1.4.0 Depends: R (>= 3.0), matrixStats (>= 0.5), methods (>= 2.14), Suggests: antiProfilesData, RColorBrewer License: Artistic-2.0 MD5sum: 62ece6721f49ea2e528e16a8f14c401c NeedsCompilation: no Title: Implementation of gene expression anti-profiles Description: Implements gene expression anti-profiles as described in Corrada Bravo et al., BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272. biocViews: GeneExpression,Classification Author: Hector Corrada Bravo, Rafael A. Irizarry and Jeffrey T. Leek Maintainer: Hector Corrada Bravo source.ver: src/contrib/antiProfiles_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/antiProfiles_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/antiProfiles_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/antiProfiles_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/antiProfiles_1.4.0.tgz vignettes: vignettes/antiProfiles/inst/doc/antiProfiles.pdf vignetteTitles: Introduction to antiProfiles hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/antiProfiles/inst/doc/antiProfiles.R Package: apComplex Version: 2.30.0 Depends: R (>= 2.10), graph, RBGL Imports: Rgraphviz, stats, org.Sc.sgd.db License: LGPL MD5sum: 84e8444bdac1d802f1fd8a66fd174e6e NeedsCompilation: no Title: Estimate protein complex membership using AP-MS protein data Description: Functions to estimate a bipartite graph of protein complex membership using AP-MS data. biocViews: NetworkInference, MassSpectrometry, GraphAndNetwork Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/apComplex_2.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/apComplex_2.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/apComplex_2.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/apComplex_2.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/apComplex_2.30.0.tgz vignettes: vignettes/apComplex/inst/doc/apComplex.pdf vignetteTitles: apComplex hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/apComplex/inst/doc/apComplex.R dependsOnMe: ScISI suggestsMe: BiocCaseStudies Package: aroma.light Version: 2.0.0 Depends: R (>= 2.14.0), matrixStats (>= 0.8.14) Imports: R.methodsS3 (>= 1.6.1), R.oo (>= 1.18.0) Suggests: R.utils (>= 1.29.8), princurve (>= 1.1-12) License: GPL (>= 2) MD5sum: ab88ff1a6b9d146b786dd5ac7037ac47 NeedsCompilation: no Title: Light-weight methods for normalization and visualization of microarray data using only basic R data types Description: Methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes. biocViews: Infrastructure, Microarray, OneChannel, TwoChannel, MultiChannel, Visualization, Preprocessing Author: Henrik Bengtsson [aut, cre, cph], Pierre Neuvial [ctb] Maintainer: Henrik Bengtsson URL: http://www.aroma-project.org/ source.ver: src/contrib/aroma.light_2.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/aroma.light_2.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/aroma.light_2.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/aroma.light_2.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/aroma.light_2.0.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: EDASeq Package: ArrayExpress Version: 1.24.0 Depends: R (>= 2.9.0), Biobase (>= 2.4.0) Imports: XML, affy, limma License: Artistic-2.0 MD5sum: a31431a506fca555ed23e0d36516366b NeedsCompilation: no Title: Access the ArrayExpress Microarray Database at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet Description: Access the ArrayExpress Repository at EBI and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet biocViews: Microarray, DataImport, OneChannel, TwoChannel Author: Audrey Kauffmann, Ibrahim Emam Maintainer: Ibrahim Emam source.ver: src/contrib/ArrayExpress_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ArrayExpress_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ArrayExpress_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ArrayExpress_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ArrayExpress_1.24.0.tgz vignettes: vignettes/ArrayExpress/inst/doc/ArrayExpress.pdf vignetteTitles: ArrayExpress: Import and convert ArrayExpress data sets into R object hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayExpress/inst/doc/ArrayExpress.R dependsOnMe: DrugVsDisease suggestsMe: gCMAPWeb Package: ArrayExpressHTS Version: 1.14.0 Depends: sampling, Rsamtools (>= 1.3.32), snow Imports: Biobase, BiocGenerics, Biostrings, DESeq, GenomicRanges, Hmisc, IRanges, R2HTML, RColorBrewer, Rsamtools, ShortRead, XML, biomaRt, edgeR, grDevices, graphics, methods, rJava, stats, svMisc, utils, sendmailR, bitops LinkingTo: Rsamtools License: Artistic License 2.0 MD5sum: ad6ea9809ffcc28aebd49aa91cad43cb NeedsCompilation: yes Title: ArrayExpress High Throughput Sequencing Processing Pipeline Description: RNA-Seq processing pipeline for public ArrayExpress experiments or local datasets biocViews: RNASeq, Sequencing Author: Angela Goncalves, Andrew Tikhonov Maintainer: Angela Goncalves , Andrew Tikhonov source.ver: src/contrib/ArrayExpressHTS_1.14.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/ArrayExpressHTS_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ArrayExpressHTS_1.14.0.tgz vignettes: vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.pdf vignetteTitles: ArrayExpressHTS: RNA-Seq Pipeline for transcription profiling experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayExpressHTS/inst/doc/ArrayExpressHTS.R Package: arrayMvout Version: 1.22.0 Depends: R (>= 2.6.0), tools, methods, utils, parody, Biobase, affy, lumi Imports: simpleaffy, mdqc, affyContam, Suggests: MAQCsubset, mvoutData, lumiBarnes, affyPLM, affydata, hgu133atagcdf License: Artistic-2.0 MD5sum: a5f605cc6b68ad4b8b803b12e0c110ff NeedsCompilation: no Title: multivariate outlier detection for expression array QA Description: This package supports the application of diverse quality metrics to AffyBatch instances, summarizing these metrics via PCA, and then performing parametric outlier detection on the PCs to identify aberrant arrays with a fixed Type I error rate biocViews: Infrastructure, Microarray, QualityControl Author: Z. Gao, A. Asare, R. Wang, V. Carey Maintainer: V. Carey source.ver: src/contrib/arrayMvout_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/arrayMvout_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/arrayMvout_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/arrayMvout_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/arrayMvout_1.22.0.tgz vignettes: vignettes/arrayMvout/inst/doc/arrayMvout.pdf vignetteTitles: arrayMvout -- multivariate outlier algorithm for expression arrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/arrayMvout/inst/doc/arrayMvout.R Package: arrayQuality Version: 1.42.0 Depends: R (>= 2.2.0) Imports: graphics, grDevices, grid, gridBase, hexbin, limma, marray, methods, RColorBrewer, stats, utils Suggests: mclust, MEEBOdata, HEEBOdata License: LGPL MD5sum: b55bca21ba9fbb9f581bfd0457b9ded1 NeedsCompilation: no Title: Assessing array quality on spotted arrays Description: Functions for performing print-run and array level quality assessment. biocViews: Microarray,TwoChannel,QualityControl,Visualization Author: Agnes Paquet and Jean Yee Hwa Yang Maintainer: Agnes Paquet URL: http://arrays.ucsf.edu/ source.ver: src/contrib/arrayQuality_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/arrayQuality_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/arrayQuality_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/arrayQuality_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/arrayQuality_1.42.0.tgz vignettes: vignettes/arrayQuality/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE htmlDocs: vignettes/arrayQuality/inst/doc/basicQuality.html, vignettes/arrayQuality/inst/doc/customQuality.html, vignettes/arrayQuality/inst/doc/index.html, vignettes/arrayQuality/inst/doc/print-runQC.html htmlTitles: "arrayQuality User Manual", "customQuality", "arrayQuality User's guide", "print-run qc" Package: arrayQualityMetrics Version: 3.20.0 Imports: affy, affyPLM (>= 1.27.3), beadarray, Biobase, Cairo (>= 1.4-6), genefilter, graphics, grDevices, grid, gridSVG, Hmisc, hwriter, lattice, latticeExtra, limma, methods, RColorBrewer, setRNG, stats, SVGAnnotation (>= 0.9-0), utils, vsn (>= 3.23.3), XML Suggests: ALLMLL, CCl4, BiocStyle, knitr License: LGPL (>= 2) MD5sum: 9fa5dda756ca31e8ee88f9f8ec23ca1a NeedsCompilation: no Title: Quality metrics on microarray data sets Description: This package generates microarray quality metrics reports for data in Bioconductor microarray data containers (ExpressionSet, NChannelSet, AffyBatch). Report contain both general and platform-specific sections. Both one and two color array platforms are supported. biocViews: Microarray, QualityControl, OneChannel, TwoChannel, ReportWriting Author: Audrey Kauffmann, Wolfgang Huber Maintainer: Audrey Kauffmann VignetteBuilder: knitr source.ver: src/contrib/arrayQualityMetrics_3.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/arrayQualityMetrics_3.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/arrayQualityMetrics_3.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/arrayQualityMetrics_3.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/arrayQualityMetrics_3.20.0.tgz vignettes: vignettes/arrayQualityMetrics/inst/doc/aqm.pdf, vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.pdf vignetteTitles: Advanced topics: Customizing arrayQualityMetrics reports and programmatic processing of the output, Introduction: microarray quality assessment with arrayQualityMetrics hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/arrayQualityMetrics/inst/doc/aqm.R, vignettes/arrayQualityMetrics/inst/doc/arrayQualityMetrics.R Package: ArrayTools Version: 1.24.0 Depends: R (>= 2.7.0), affy (>= 1.23.4), Biobase (>= 2.5.5), methods Imports: affy, Biobase, graphics, grDevices, limma, methods, stats, utils, xtable Suggests: simpleaffy, R2HTML, affydata, affyPLM, genefilter, annaffy, gcrma, hugene10sttranscriptcluster.db License: LGPL (>= 2.0) MD5sum: 68301cbca67a5ef64687afd415475303 NeedsCompilation: no Title: geneChip Analysis Package Description: This package is designed to provide solutions for quality assessment and to detect differentially expressed genes for the Affymetrix GeneChips, including both 3' -arrays and gene 1.0-ST arrays. The package generates comprehensive analysis reports in HTML format. Hyperlinks on the report page will lead to a series of QC plots, processed data, and differentially expressed gene lists. Differentially expressed genes are reported in tabular format with annotations hyperlinked to online biological databases. biocViews: Microarray, OneChannel, QualityControl, Preprocessing, StatisticalMethod, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu, Arthur Li Maintainer: Arthur Li source.ver: src/contrib/ArrayTools_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ArrayTools_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ArrayTools_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ArrayTools_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ArrayTools_1.24.0.tgz vignettes: vignettes/ArrayTools/inst/doc/ArrayTools.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayTools/inst/doc/ArrayTools.R Package: ArrayTV Version: 1.2.0 Depends: R (>= 2.14) Imports: foreach, DNAcopy, methods, oligoClasses (>= 1.21.3) Suggests: RColorBrewer, crlmm, ff, BSgenome.Hsapiens.UCSC.hg18,BSgenome.Hsapiens.UCSC.hg19, lattice, latticeExtra, RUnit, BiocGenerics Enhances: doMC, doSNOW, doParallel License: GPL (>= 2) MD5sum: 9e413984bd302cbc8d78d9c5587357b6 NeedsCompilation: no Title: Implementation of wave correction for arrays Description: Wave correction for genotyping and copy number arrays biocViews: CopyNumberVariation Author: Eitan Halper-Stromberg Maintainer: Eitan Halper-Stromberg source.ver: src/contrib/ArrayTV_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ArrayTV_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ArrayTV_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ArrayTV_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ArrayTV_1.2.0.tgz vignettes: vignettes/ArrayTV/inst/doc/ArrayTV.pdf vignetteTitles: ArrayTV Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ArrayTV/inst/doc/ArrayTV.R Package: ARRmNormalization Version: 1.4.0 Depends: R (>= 2.15.1), ARRmData License: Artistic-2.0 MD5sum: 36ca5059f4a8fe1629c7e7c333e3f49e NeedsCompilation: no Title: Adaptive Robust Regression normalization for Illumina methylation data Description: Perform the Adaptive Robust Regression method (ARRm) for the normalization of methylation data from the Illumina Infinium HumanMethylation 450k assay. biocViews: DNAMethylation, TwoChannel, Preprocessing, Microarray Author: Jean-Philippe Fortin, Celia M.T. Greenwood, Aurelie Labbe. Maintainer: Jean-Philippe Fortin source.ver: src/contrib/ARRmNormalization_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ARRmNormalization_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ARRmNormalization_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ARRmNormalization_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ARRmNormalization_1.4.0.tgz vignettes: vignettes/ARRmNormalization/inst/doc/ARRmNormalization.pdf vignetteTitles: ARRmNormalization hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ARRmNormalization/inst/doc/ARRmNormalization.R Package: ASEB Version: 1.8.1 Depends: R (>= 2.8.0), methods Imports: graphics, methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: 239d740699ad2d3074576ec04c863bfb NeedsCompilation: yes Title: Predict Acetylated Lysine Sites Description: ASEB is an R package to predict lysine sites that can be acetylated by a specific KAT-family. biocViews: Proteomics Author: Likun Wang and Tingting Li . Maintainer: Likun Wang source.ver: src/contrib/ASEB_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/ASEB_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/ASEB_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/ASEB_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ASEB_1.8.1.tgz vignettes: vignettes/ASEB/inst/doc/ASEB.pdf vignetteTitles: ASEB hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ASEB/inst/doc/ASEB.R Package: asmn Version: 1.0.0 Depends: R (>= 3.0.2) Imports: methylumi, stats, Biobase Suggests: TCGAMethylation450k, IlluminaHumanMethylation450k.db License: GPL-3 MD5sum: 96487834b418e12335cc2515c8abe3f1 NeedsCompilation: no Title: All sample mean normalization. Description: Performs all sample mean normalization using raw data output from BeadStudio and MethyLumiM data. biocViews: DNAMethylation, TwoChannel, Preprocessing, QualityControl Author: 'Anna Decker [aut,cre], Paul Yousefi [aut,cre]' Maintainer: Anna Decker source.ver: src/contrib/asmn_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/asmn_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/asmn_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/asmn_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/asmn_1.0.0.tgz vignettes: vignettes/asmn/inst/doc/asmn-vignette.pdf vignetteTitles: Vignette for R package asmn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/asmn/inst/doc/asmn-vignette.R Package: ASSET Version: 1.2.0 Depends: MASS, msm, rmeta Suggests: RUnit, BiocGenerics License: GPL-2 + file LICENSE MD5sum: 4761c40ec41b6208d7a64c42b81b32c8 NeedsCompilation: no Title: An R package for subset-based association analysis of heterogeneous traits and subtypes Description: An R package for subset-based analysis of heterogeneous traits and subtypes biocViews: Software Author: Samsiddhi Bhattacharjee, Nilanjan Chatterjee and William Wheeler Maintainer: William Wheeler source.ver: src/contrib/ASSET_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ASSET_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ASSET_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ASSET_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ASSET_1.2.0.tgz vignettes: vignettes/ASSET/inst/doc/vignette.pdf vignetteTitles: ASSET Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ASSET/inst/doc/vignette.R Package: ASSIGN Version: 1.0.0 Depends: Rlab, msm, gplots Imports: graphics, grDevices, stats, utils License: MIT MD5sum: a1b84b80903034b4af85d891219f2697 NeedsCompilation: no Title: Adaptive Signature Selection and InteGratioN (ASSIGN) Description: ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literatures or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature. biocViews: Software, GeneExpression, Pathways, Bayesian Author: Ying Shen, Andrea H. Bild, and W. Evan Johnson Maintainer: Ying Shen source.ver: src/contrib/ASSIGN_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ASSIGN_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ASSIGN_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ASSIGN_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ASSIGN_1.0.0.tgz vignettes: vignettes/ASSIGN/inst/doc/ASSIGN.vignette.pdf vignetteTitles: Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ASSIGN/inst/doc/ASSIGN.vignette.R Package: AtlasRDF Version: 1.0.0 Depends: R (>= 2.10), hash, SPARQL, methods License: Apache License 2.0 MD5sum: 1281c90baa4c00f62212eedb2a614e03 NeedsCompilation: no Title: Gene Expression Atlas query and gene set enrichment package. Description: Query the Gene Expression Atlas RDF data at the European Bioinformatics Institute using genes, experimental factors (such as disease, cell type, compound treatments), pathways and proteins. Also contains a function to perform an enrichment of your gene list across Experimental Factor Ontology (EFO) using the Atlas background set. biocViews: Microarray, DataImport, GeneSetEnrichment, GeneExpression, DifferentialExpression, DataRepresentation Author: James Malone, Simon Jupp, Maryam Soleimani Maintainer: James Malone source.ver: src/contrib/AtlasRDF_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/AtlasRDF_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/AtlasRDF_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/AtlasRDF_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/AtlasRDF_1.0.0.tgz vignettes: vignettes/AtlasRDF/inst/doc/AtlasRDF_vignette.pdf vignetteTitles: An introduction to the AtlasRDF-R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AtlasRDF/inst/doc/AtlasRDF_vignette.R Package: attract Version: 1.16.0 Depends: R (>= 2.10.0), AnnotationDbi, KEGG.db, limma, cluster, GOstats, graphics, methods, stats Imports: Biobase, AnnotationDbi, KEGG.db, limma, cluster, GOstats, graphics, methods, stats Suggests: illuminaHumanv1.db License: LGPL (>= 2.0) MD5sum: b40a084440cfd31fb8c7ba0d8cf929be NeedsCompilation: no Title: Methods to Find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape Description: This package contains the functions to find the gene expression modules that represent the drivers of Kauffman's attractor landscape. The modules are the core attractor pathways that discriminate between different cell types of groups of interest. Each pathway has a set of synexpression groups, which show transcriptionally-coordinated changes in gene expression. biocViews: StatisticalMethod, GeneExpression Author: Jessica Mar Maintainer: Jessica Mar source.ver: src/contrib/attract_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/attract_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/attract_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/attract_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/attract_1.16.0.tgz vignettes: vignettes/attract/inst/doc/attract.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/attract/inst/doc/attract.R Package: BAC Version: 1.24.0 Depends: R (>= 2.10) License: Artistic-2.0 Archs: i386, x64 MD5sum: fa067de427b9b404623081c43651ddb9 NeedsCompilation: yes Title: Bayesian Analysis of Chip-chip experiment Description: This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments biocViews: Microarray, Transcription Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/BAC_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BAC_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BAC_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BAC_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BAC_1.24.0.tgz vignettes: vignettes/BAC/inst/doc/BAC.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BAC/inst/doc/BAC.R Package: BADER Version: 1.2.0 Suggests: pasilla (>= 0.2.10) License: GPL-2 Archs: i386, x64 MD5sum: 1bd107c0ac38679d55faf21f435a3424 NeedsCompilation: yes Title: Bayesian Analysis of Differential Expression in RNA Sequencing Data Description: For RNA sequencing count data, BADER fits a Bayesian hierarchical model. The algorithm returns the posterior probability of differential expression for each gene between two groups A and B. The joint posterior distribution of the variables in the model can be returned in the form of posterior samples, which can be used for further down-stream analyses such as gene set enrichment. biocViews: Sequencing, RNASeq, DifferentialExpression, Software, SAGE Author: Andreas Neudecker, Matthias Katzfuss Maintainer: Andreas Neudecker source.ver: src/contrib/BADER_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BADER_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BADER_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BADER_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BADER_1.2.0.tgz vignettes: vignettes/BADER/inst/doc/BADER.pdf vignetteTitles: Analysing RNA-Seq data with the "BADER" package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BADER/inst/doc/BADER.R Package: BAGS Version: 2.4.0 Depends: R (>= 2.10), breastCancerVDX, Biobase License: Artistic-2.0 Archs: i386, x64 MD5sum: 0962740b95b0733a69fa39890065777e NeedsCompilation: yes Title: A Bayesian Approach for Geneset Selection Description: R package providing functions to perform geneset significance analysis over simple cross-sectional data between 2 and 5 phenotypes of interest. biocViews: Bayesian Author: Alejandro Quiroz-Zarate Maintainer: Alejandro Quiroz-Zarate source.ver: src/contrib/BAGS_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BAGS_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BAGS_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BAGS_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BAGS_2.4.0.tgz vignettes: vignettes/BAGS/inst/doc/BAGS.pdf vignetteTitles: BAGS: A Bayesian Approach for Geneset Selection. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BAGS/inst/doc/BAGS.R Package: BaseSpaceR Version: 1.8.0 Depends: R (>= 2.15.0), RCurl, RJSONIO Imports: methods Suggests: RUnit, IRanges, Rsamtools License: Apache License 2.0 MD5sum: 097088390af1f01583ee67bee859d54d NeedsCompilation: no Title: R SDK for BaseSpace RESTful API Description: A rich R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualisation tools. biocViews: Infrastructure, DataRepresentation, ConnectTools, Software, DataImport, HighThroughputSequencing, Sequencing, Genetics Author: Adrian Alexa Maintainer: Adrian Alexa source.ver: src/contrib/BaseSpaceR_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BaseSpaceR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BaseSpaceR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BaseSpaceR_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BaseSpaceR_1.8.0.tgz vignettes: vignettes/BaseSpaceR/inst/doc/BaseSpaceR.pdf vignetteTitles: BaseSpaceR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BaseSpaceR/inst/doc/BaseSpaceR.R Package: Basic4Cseq Version: 1.0.2 Depends: R (>= 3.0.0), Biostrings, ShortRead, caTools, GenomicRanges Imports: methods, RCircos, BSgenome.Ecoli.NCBI.20080805 Suggests: BSgenome.Hsapiens.UCSC.hg19 License: LGPL-3 MD5sum: 943eda6304f5a6f10046a5c1a42c859a NeedsCompilation: no Title: Basic4Cseq: an R/Bioconductor package for analyzing 4C-seq data Description: Basic4Cseq is an R/Bioconductor package for basic filtering, analysis and subsequent visualization of 4C-seq data. Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile. biocViews: Visualization, QualityControl Author: Carolin Walter Maintainer: Carolin Walter source.ver: src/contrib/Basic4Cseq_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/Basic4Cseq_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/Basic4Cseq_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/Basic4Cseq_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Basic4Cseq_1.0.2.tgz vignettes: vignettes/Basic4Cseq/inst/doc/vignette.pdf vignetteTitles: Basic4Cseq: an R/Bioconductor package for the analysis of 4C-seq data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Basic4Cseq/inst/doc/vignette.R Package: BayesPeak Version: 1.16.0 Depends: R (>= 2.14), IRanges Imports: IRanges, graphics Suggests: BiocStyle License: GPL (>= 2) Archs: i386, x64 MD5sum: f0eea9bff8476acae8c6443e31fdafcb NeedsCompilation: yes Title: Bayesian Analysis of ChIP-seq Data Description: This package is an implementation of the BayesPeak algorithm for peak-calling in ChIP-seq data. biocViews: ChIPSeq Author: Christiana Spyrou, Jonathan Cairns, Rory Stark, Andy Lynch, Simon Tavar\\'{e}, Maintainer: Jonathan Cairns source.ver: src/contrib/BayesPeak_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BayesPeak_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BayesPeak_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BayesPeak_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BayesPeak_1.16.0.tgz vignettes: vignettes/BayesPeak/inst/doc/BayesPeak.pdf vignetteTitles: BayesPeak Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BayesPeak/inst/doc/BayesPeak.R Package: baySeq Version: 1.18.0 Depends: R (>= 2.3.0), methods, GenomicRanges Suggests: snow, edgeR License: GPL-3 MD5sum: 24f82d1b6234e0145887a6748c56c71c NeedsCompilation: no Title: Empirical Bayesian analysis of patterns of differential expression in count data Description: This package identifies differential expression in high-throughput 'count' data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods. biocViews: Bioinformatics, HighThroughputSequencing, DifferentialExpression, MultipleComparisons, SAGE Author: Thomas J. Hardcastle Maintainer: Thomas J. Hardcastle source.ver: src/contrib/baySeq_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/baySeq_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/baySeq_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/baySeq_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/baySeq_1.18.0.tgz vignettes: vignettes/baySeq/inst/doc/baySeq.pdf vignetteTitles: baySeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/baySeq/inst/doc/baySeq.R dependsOnMe: Rcade, segmentSeq, TCC importsMe: EDDA, metaseqR, segmentSeq suggestsMe: compcodeR, oneChannelGUI Package: BCRANK Version: 1.26.0 Depends: methods Imports: Biostrings Suggests: seqLogo License: GPL-2 Archs: i386, x64 MD5sum: 82fe8a926186573a6022be8741ef53eb NeedsCompilation: yes Title: Predicting binding site consensus from ranked DNA sequences Description: Functions and classes for de novo prediction of transcription factor binding consensus by heuristic search biocViews: MotifDiscovery, GeneRegulation Author: Adam Ameur Maintainer: Adam Ameur source.ver: src/contrib/BCRANK_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BCRANK_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BCRANK_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BCRANK_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BCRANK_1.26.0.tgz vignettes: vignettes/BCRANK/inst/doc/BCRANK.pdf vignetteTitles: BCRANK hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BCRANK/inst/doc/BCRANK.R Package: beadarray Version: 2.14.1 Depends: R (>= 2.13.0), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), methods, ggplot2 Imports: BeadDataPackR, limma, AnnotationDbi, stats4, reshape2, GenomicRanges, IRanges, illuminaio Suggests: lumi, vsn, affy, hwriter, beadarrayExampleData, illuminaHumanv3.db, gridExtra, BiocStyle, TxDb.Hsapiens.UCSC.hg19.knownGene, ggbio, Nozzle.R1, knitr License: GPL-2 Archs: i386, x64 MD5sum: 798cadef4221d19195dab23957a276bc NeedsCompilation: yes Title: Quality assessment and low-level analysis for Illumina BeadArray data Description: The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided. biocViews: Microarray, OneChannel, QualityControl, Preprocessing Author: Mark Dunning, Mike Smith, Jonathan Cairns, Andy Lynch, Matt Ritchie Maintainer: Mark Dunning VignetteBuilder: knitr source.ver: src/contrib/beadarray_2.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/beadarray_2.14.1.zip win64.binary.ver: bin/windows64/contrib/3.1/beadarray_2.14.1.zip mac.binary.ver: bin/macosx/contrib/3.1/beadarray_2.14.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/beadarray_2.14.1.tgz vignettes: vignettes/beadarray/inst/doc/beadarray.pdf, vignettes/beadarray/inst/doc/beadlevel.pdf, vignettes/beadarray/inst/doc/beadsummary.pdf, vignettes/beadarray/inst/doc/ImageProcessing.pdf vignetteTitles: beadarray.pdf, beadlevel.pdf, beadsummary.pdf, ImageProcessing.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/beadarray/inst/doc/beadarray.R, vignettes/beadarray/inst/doc/beadlevel.R, vignettes/beadarray/inst/doc/beadsummary.R, vignettes/beadarray/inst/doc/ImageProcessing.R importsMe: arrayQualityMetrics, epigenomix suggestsMe: beadarraySNP, lumi Package: beadarraySNP Version: 1.30.0 Depends: methods, Biobase (>= 2.5.5), quantsmooth Suggests: aCGH, affy, limma, snapCGH, beadarray, DNAcopy License: GPL-2 MD5sum: 8c672233e176c9e01a314ad0e6153e9e NeedsCompilation: no Title: Normalization and reporting of Illumina SNP bead arrays Description: Importing data from Illumina SNP experiments and performing copy number calculations and reports. biocViews: CopyNumberVariation, SNP, GeneticVariability, TwoChannel, Preprocessing, DataImport Author: Jan Oosting Maintainer: Jan Oosting source.ver: src/contrib/beadarraySNP_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/beadarraySNP_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/beadarraySNP_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/beadarraySNP_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/beadarraySNP_1.30.0.tgz vignettes: vignettes/beadarraySNP/inst/doc/beadarraySNP.pdf vignetteTitles: beadarraySNP.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/beadarraySNP/inst/doc/beadarraySNP.R Package: BeadDataPackR Version: 1.16.0 License: GPL-2 Archs: i386, x64 MD5sum: 11e8249d15838811a2f6d4855029b1b5 NeedsCompilation: yes Title: Compression of Illumina BeadArray data Description: Provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform biocViews: Microarray Author: Mike Smith, Andy Lynch Maintainer: Mike Smith source.ver: src/contrib/BeadDataPackR_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BeadDataPackR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BeadDataPackR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BeadDataPackR_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BeadDataPackR_1.16.0.tgz vignettes: vignettes/BeadDataPackR/inst/doc/BeadDataPackR.pdf vignetteTitles: BeadDataPackR.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BeadDataPackR/inst/doc/BeadDataPackR.R importsMe: beadarray Package: BEAT Version: 1.2.0 Depends: R (>= 2.13.0) Imports: GenomicRanges, ShortRead, Biostrings, BSgenome License: LGPL (>= 3.0) MD5sum: 542c203c132ab2dd4386dcb03304fb16 NeedsCompilation: no Title: BEAT - BS-Seq Epimutation Analysis Toolkit Description: Model-based analysis of single-cell methylation data biocViews: Genetics, MethylSeq, Software, DNAMethylation, Epigenetics Author: Kemal Akman Maintainer: Kemal Akman source.ver: src/contrib/BEAT_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BEAT_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BEAT_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BEAT_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BEAT_1.2.0.tgz vignettes: vignettes/BEAT/inst/doc/BEAT.pdf vignetteTitles: Analysing single-cell BS-Seq data with the "BEAT" package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BEAT/inst/doc/BEAT.R Package: betr Version: 1.20.0 Depends: R(>= 2.6.0) Imports: Biobase (>= 2.5.5), limma, mvtnorm, methods, stats Suggests: Biobase License: LGPL MD5sum: 8b4b927d51647b171e36a7ae4b6dc546 NeedsCompilation: no Title: Identify differentially expressed genes in microarray time-course data Description: The betr package implements the BETR (Bayesian Estimation of Temporal Regulation) algorithm to identify differentially expressed genes in microarray time-course data. biocViews: Microarray, DifferentialExpression, TimeCourse Author: Martin Aryee Maintainer: Martin Aryee source.ver: src/contrib/betr_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/betr_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/betr_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/betr_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/betr_1.20.0.tgz vignettes: vignettes/betr/inst/doc/betr.pdf vignetteTitles: BETR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/betr/inst/doc/betr.R Package: bgafun Version: 1.26.0 Depends: made4, seqinr,ade4 License: Artistic-2.0 MD5sum: 86f7dc6078c4e35f78f2c1bd926e85bb NeedsCompilation: no Title: BGAfun A method to identify specifity determining residues in protein families Description: A method to identify specifity determining residues in protein families using Between Group Analysis biocViews: Classification Author: Iain Wallace Maintainer: Iain Wallace source.ver: src/contrib/bgafun_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bgafun_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bgafun_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bgafun_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bgafun_1.26.0.tgz vignettes: vignettes/bgafun/inst/doc/bgafun.pdf vignetteTitles: bgafun.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bgafun/inst/doc/bgafun.R Package: BGmix Version: 1.24.0 Depends: R (>= 2.3.1), KernSmooth License: GPL-2 MD5sum: 19dd57ac8d7f81bed60b3604efdeb936 NeedsCompilation: yes Title: Bayesian models for differential gene expression Description: Fully Bayesian mixture models for differential gene expression biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Alex Lewin, Natalia Bochkina Maintainer: Alex Lewin source.ver: src/contrib/BGmix_1.24.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/BGmix_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BGmix_1.24.0.tgz vignettes: vignettes/BGmix/inst/doc/BGmix.pdf vignetteTitles: BGmix Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BGmix/inst/doc/BGmix.R Package: bgx Version: 1.30.0 Depends: R (>= 2.0.1), Biobase, affy (>= 1.5.0), gcrma (>= 2.4.1) Suggests: affydata, hgu95av2cdf License: GPL-2 Archs: i386, x64 MD5sum: 505446ea8a8ae86c6b1eb5152b71e72a NeedsCompilation: yes Title: Bayesian Gene eXpression Description: Bayesian integrated analysis of Affymetrix GeneChips biocViews: Microarray, DifferentialExpression Author: Ernest Turro, Graeme Ambler, Anne-Mette K Hein Maintainer: Ernest Turro source.ver: src/contrib/bgx_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bgx_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bgx_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bgx_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bgx_1.30.0.tgz vignettes: vignettes/bgx/inst/doc/bgx.pdf vignetteTitles: HowTo BGX hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bgx/inst/doc/bgx.R Package: BHC Version: 1.16.0 License: GPL-3 Archs: i386, x64 MD5sum: 2f300b519f9ba6c2361049863306950b NeedsCompilation: yes Title: Bayesian Hierarchical Clustering Description: The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture) to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. This avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric. This implementation accepts multinomial (i.e. discrete, with 2+ categories) or time-series data. This version also includes a randomised algorithm which is more efficient for larger data sets. biocViews: Microarray, Clustering Author: Rich Savage, Emma Cooke, Robert Darkins, Yang Xu Maintainer: Rich Savage source.ver: src/contrib/BHC_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BHC_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BHC_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BHC_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BHC_1.16.0.tgz vignettes: vignettes/BHC/inst/doc/bhc.pdf vignetteTitles: Bayesian Hierarchical Clustering hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BHC/inst/doc/bhc.R Package: BicARE Version: 1.22.0 Depends: R (>= 1.8.0), Biobase (>= 2.5.5), multtest, GSEABase License: GPL-2 Archs: i386, x64 MD5sum: b77fa255f4d26319fefd74b26e4f3b60 NeedsCompilation: yes Title: Biclustering Analysis and Results Exploration Description: Biclustering Analysis and Results Exploration biocViews: Microarray, Transcription, Clustering Author: Pierre Gestraud Maintainer: Pierre Gestraud URL: http://bioinfo.curie.fr source.ver: src/contrib/BicARE_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BicARE_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BicARE_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BicARE_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BicARE_1.22.0.tgz vignettes: vignettes/BicARE/inst/doc/BicARE.pdf vignetteTitles: BicARE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BicARE/inst/doc/BicARE.R Package: BiGGR Version: 1.2.0 Depends: R (>= 2.14.0), rsbml, hyperdraw, LIM Imports: hypergraph License: file LICENSE MD5sum: 57ea5a89c76647da0718835356c697dc NeedsCompilation: no Title: Constraint based modeling in R using metabolic reconstruction databases. Description: This package provides an interface to simulate metabolic reconstruction from the BiGG database(http://bigg.ucsd.edu/) and other metabolic reconstruction databases. The package aids in performing flux balance analysis (FBA). Metabolic networks and estimated fluxes can be visualized using hypergraphs. biocViews: Network, Visualization, Metabolomics Author: Anand K. Gavai, Hannes Hettling Maintainer: Anand K. Gavai , Hannes Hettling URL: http://www.bioconductor.org/ source.ver: src/contrib/BiGGR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiGGR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BiGGR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BiGGR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiGGR_1.2.0.tgz vignettes: vignettes/BiGGR/inst/doc/BiGGR.pdf vignetteTitles: BiGGR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/BiGGR/inst/doc/BiGGR.R Package: bigmemoryExtras Version: 1.8.0 Depends: R (>= 2.12), bigmemory (>= 4.3) Imports: bigmemory, biganalytics, methods, BiocGenerics, Biobase Suggests: RUnit, BiocGenerics (>= 0.1.0) License: Artistic-2.0 OS_type: unix MD5sum: 59041a1b943a00beb613d138592c8eb4 NeedsCompilation: no Title: An extension of the bigmemory package with added safety, convenience, and a factor class. Description: This package defines a "BigMatrix" ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data and it also protects against accidental data modification with a filesystem-based permissions system. We provide utilities for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a "BigMatrixFactor" class, a file-backed matrix with factor properties. biocViews: Infrastructure, DataRepresentation Author: Peter M. Haverty Maintainer: Peter M. Haverty source.ver: src/contrib/bigmemoryExtras_1.8.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/bigmemoryExtras_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bigmemoryExtras_1.8.0.tgz vignettes: vignettes/bigmemoryExtras/inst/doc/bigmemoryExtras.pdf vignetteTitles: bigmemoryExtras hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bigmemoryExtras/inst/doc/bigmemoryExtras.R Package: bioassayR Version: 1.2.0 Depends: R (>= 3.0.1), DBI, RSQLite, methods Imports: XML Suggests: BiocStyle, RCurl, ape, ChemmineR License: Artistic-2.0 MD5sum: 16bd0bfc304b65891833686abd6677ac NeedsCompilation: no Title: R library for Bioactivity analysis Description: bioassayR provides tools for statistical analysis of small molecule bioactivity data biocViews: MicrotitrePlateAssay, CellBasedAssays, Visualization, Infrastructure, DataImport, Proteomics Author: Tyler Backman, Ronly Schlenk, Thomas Girke Maintainer: Tyler Backman source.ver: src/contrib/bioassayR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bioassayR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bioassayR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bioassayR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bioassayR_1.2.0.tgz vignettes: vignettes/bioassayR/inst/doc/bioassayR.pdf vignetteTitles: bioassayR Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bioassayR/inst/doc/bioassayR.R Package: Biobase Version: 2.24.0 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), utils Imports: methods Suggests: tools, tkWidgets, ALL, RUnit, golubEsets License: Artistic-2.0 Archs: i386, x64 MD5sum: 76d14ec2ecba9bc90433998538fa9f83 NeedsCompilation: yes Title: Biobase: Base functions for Bioconductor Description: Functions that are needed by many other packages or which replace R functions. biocViews: Infrastructure Author: R. Gentleman, V. Carey, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Biobase_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Biobase_2.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Biobase_2.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Biobase_2.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Biobase_2.24.0.tgz vignettes: vignettes/Biobase/inst/doc/BiobaseDevelopment.pdf, vignettes/Biobase/inst/doc/Bioconductor.pdf, vignettes/Biobase/inst/doc/esApply.pdf, vignettes/Biobase/inst/doc/ExpressionSetIntroduction.pdf, vignettes/Biobase/inst/doc/HowTo.pdf, vignettes/Biobase/inst/doc/Qviews.pdf vignetteTitles: Notes for eSet developers, Bioconductor Overview, esApply Introduction, An introduction to Biobase and ExpressionSets, Notes for writing introductory 'how to' documents, quick views of eSet instances hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Biobase/inst/doc/BiobaseDevelopment.R, vignettes/Biobase/inst/doc/Bioconductor.R, vignettes/Biobase/inst/doc/esApply.R, vignettes/Biobase/inst/doc/ExpressionSetIntroduction.R, vignettes/Biobase/inst/doc/HowTo.R, vignettes/Biobase/inst/doc/Qviews.R dependsOnMe: a4Base, a4Core, ACME, affy, affycomp, affyContam, affycoretools, affyPLM, affyQCReport, AGDEX, altcdfenvs, annaffy, AnnotationDbi, AnnotationForge, ArrayExpress, arrayMvout, ArrayTools, BAGS, beadarray, beadarraySNP, bgx, BicARE, BiocCaseStudies, BioMVCClass, BioNet, birta, BrainStars, CAMERA, cancerclass, casper, Category, categoryCompare, cellHTS, cellHTS2, CGHbase, CGHcall, CGHregions, charm, chimera, chroGPS, clippda, clusterStab, CMA, cn.farms, cn.mops, codelink, convert, copa, CopyNumber450k, ddCt, DESeq, DEXSeq, DFP, DSS, dualKS, dyebias, EBarrays, EDASeq, eisa, epigenomix, epivizr, ExiMiR, fabia, factDesign, fastseg, flowBeads, flowClust, frma, gaga, GeneAnswers, GeneExpressionSignature, GeneMeta, geneplotter, geneRecommender, GeneRegionScan, GeneSelectMMD, 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methods, utils, Biobase Suggests: affy (>= 1.17.3), affyPLM (>= 1.15.1), affyQCReport (>= 1.17.0), ALL (>= 1.4.3), annaffy (>= 1.11.1), annotate (>= 1.17.3), AnnotationDbi (>= 1.1.6), apComplex (>= 2.5.0), Biobase (>= 1.17.5), bioDist (>= 1.11.3), biocGraph (>= 1.1.1), biomaRt (>= 1.13.5), CCl4 (>= 1.0.6), CLL (>= 1.2.4), Category (>= 2.5.0), class (>= 7.2-38), cluster (>= 1.11.9), convert (>= 1.15.0), gcrma (>= 2.11.1), genefilter (>= 1.17.6), geneplotter (>= 1.17.2), GO.db (>= 2.0.2), GOstats (>= 2.5.0), graph (>= 1.17.4), GSEABase (>= 1.1.13), hgu133a.db (>= 2.0.2), hgu95av2.db, hgu95av2cdf (>= 2.0.0), hgu95av2probe (>= 2.0.0), hopach (>= 1.13.0), KEGG.db (>= 2.0.2), kohonen (>= 2.0.2), lattice (>= 0.17.2), latticeExtra (>= 0.3-1), limma (>= 2.13.1), MASS (>= 7.2-38), MLInterfaces (>= 1.13.17), multtest (>= 1.19.0), org.Hs.eg.db (>= 2.0.2), ppiStats (>= 1.5.4), randomForest (>= 4.5-20), RBGL (>= 1.15.6), RColorBrewer (>= 1.0-2), Rgraphviz (>= 1.17.11), vsn (>= 3.4.0), weaver (>= 1.5.0), xtable (>= 1.5-2), yeastExpData (>= 0.9.11) License: Artistic-2.0 MD5sum: 860c3024867c8c193e4853705ec187ea NeedsCompilation: no Title: BiocCaseStudies: Support for the Case Studies Monograph Description: Software and data to support the case studies. biocViews: Infrastructure Author: R. Gentleman, W. Huber, F. Hahne, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocCaseStudies_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocCaseStudies_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocCaseStudies_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocCaseStudies_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocCaseStudies_1.26.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: BiocCheck Version: 1.0.2 Depends: R (>= 3.1.0) Imports: biocViews (>= 1.31.9), BiocInstaller, graph, devtools (>= 1.4.1), httr, knitr, tools, optparse, codetools, methods Suggests: RUnit, BiocGenerics, Biobase, RJSONIO, knitrBootstrap Enhances: codetoolsBioC License: Artistic-2.0 MD5sum: 21a9272651e6f1be626e1e9c5da95c6e NeedsCompilation: no Title: Bioconductor-specific package checks Description: Bioconductor-specific package checks biocViews: Infrastructure Author: Bioconductor Package Maintainer [aut, cre] Maintainer: Bioconductor Package Maintainer URL: https://github.com/Bioconductor/BiocCheck/issues VignetteBuilder: knitr source.ver: src/contrib/BiocCheck_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocCheck_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocCheck_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocCheck_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocCheck_1.0.2.tgz vignettes: vignettes/BiocCheck/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiocCheck/inst/doc/BiocCheck.R htmlDocs: vignettes/BiocCheck/inst/doc/BiocCheck.html htmlTitles: "BiocCheck" Package: BiocGenerics Version: 0.10.0 Depends: methods, utils, graphics, stats, parallel Imports: methods, utils, graphics, stats, parallel Suggests: Biobase, IRanges, GenomicRanges, AnnotationDbi, oligoClasses, oligo, affyPLM, flowClust, affy, RUnit, DESeq2 License: Artistic-2.0 MD5sum: 431e30b3dee2add008b552c6598e1ead NeedsCompilation: no Title: S4 generic functions for Bioconductor Description: S4 generic functions needed by many Bioconductor packages. biocViews: Infrastructure Author: The Bioconductor Dev Team Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocGenerics_0.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocGenerics_0.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocGenerics_0.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocGenerics_0.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocGenerics_0.10.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affy, affyPLM, altcdfenvs, AnnotationDbi, AnnotationForge, beadarray, Biobase, Biostrings, BSgenome, bsseq, Category, categoryCompare, chipseq, ChIPseqR, ChromHeatMap, cleanUpdTSeq, cn.mops, codelink, copynumber, CopyNumber450k, CRISPRseek, cummeRbund, DESeq, dexus, EDASeq, ensemblVEP, flowQ, geneplotter, genomeIntervals, GenomicAlignments, GenomicFeatures, GenomicFiles, GenomicRanges, Genominator, genoset, ggbio, GSEABase, Gviz, htSeqTools, interactiveDisplay, IRanges, meshr, minfi, MotIV, MSnbase, nucleR, oligo, PICS, PSICQUIC, PWMEnrich, REDseq, Repitools, rMAT, rsbml, rSFFreader, scsR, ShortRead, simpleaffy, SplicingGraphs, TEQC, tigre, TSSi, UNDO, VariantAnnotation, VariantFiltering, virtualArray, xcms, XVector importsMe: affyPLM, AllelicImbalance, annmap, annotate, AnnotationDbi, AnnotationForge, AnnotationHub, ArrayExpressHTS, bigmemoryExtras, biocGraph, BiocParallel, Biostrings, biosvd, biovizBase, BiSeq, BSgenome, bumphunter, casper, Category, cghMCR, ChemmineOB, ChemmineR, ChIPpeakAnno, ChIPQC, ChIPseeker, chipseq, cn.farms, cn.mops, crlmm, cummeRbund, DESeq2, DEXSeq, DrugVsDisease, easyRNASeq, EBImage, EDASeq, eiR, eisa, epigenomix, fastseg, ffpe, flowBin, flowClust, flowCore, flowFP, flowQ, flowStats, flowWorkspace, frma, gCMAP, gCMAPWeb, GenomicAlignments, GenomicRanges, GGBase, GGtools, GOTHiC, graph, GSVA, gwascat, hopach, HTSeqGenie, intansv, IRanges, KCsmart, LVSmiRNA, metaMS, methylumi, MinimumDistance, MiRaGE, MotifDb, npGSEA, nucleR, oligo, oligoClasses, OrganismDbi, pcaMethods, PING, plrs, prada, ProCoNA, pRoloc, QuasR, R453Plus1Toolbox, RCytoscape, REDseq, RefNet, ReportingTools, RGalaxy, Ringo, rMAT, Rsamtools, rsbml, rtracklayer, simpleaffy, SLGI, snpStats, spliceSites, SplicingGraphs, Streamer, triform, TSSi, unifiedWMWqPCR, UniProt.ws, VariantTools, XDE, XVector suggestsMe: ArrayTV, ASSET, bigmemoryExtras, BiocCheck, BiocInstaller, BiocStyle, BiRewire, bumphunter, CAFE, CAMERA, ccrepe, CellNOptR, CexoR, ChIPXpress, clipper, clonotypeR, CNEr, CNORfeeder, CNORfuzzy, cobindR, dagLogo, DBChIP, DMRcate, DNaseR, FGNet, flowCL, GENE.E, GeneNetworkBuilder, GeneOverlap, geneRxCluster, geNetClassifier, GenomeInfoDb, GOstats, GraphPAC, GWASTools, iClusterPlus, illuminaio, INPower, inSilicoMerging, KEGGREST, massiR, MeSHDbi, metaseqR, Mirsynergy, motifStack, NetSAM, nondetects, PathNet, pathview, PhenStat, plethy, rBiopaxParser, Rcade, Rcpi, Rgraphviz, roar, ROntoTools, rpx, RTN, rTRM, sangerseqR, SANTA, sapFinder, SeqArray, SeqVarTools, SpacePAC, STRINGdb, TCC, TFBSTools, trackViewer Package: biocGraph Version: 1.26.0 Depends: Rgraphviz, graph Imports: Rgraphviz, geneplotter, graph, BiocGenerics, methods Suggests: fibroEset, geneplotter, hgu95av2.db License: Artistic-2.0 MD5sum: f4b0deb14a00c762364fae69d194c631 NeedsCompilation: no Title: Graph examples and use cases in Bioinformatics Description: This package provides examples and code that make use of the different graph related packages produced by Bioconductor. biocViews: Visualization, GraphAndNetwork Author: Li Long , Robert Gentleman , Seth Falcon Florian Hahne Maintainer: Florian Hahne source.ver: src/contrib/biocGraph_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/biocGraph_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/biocGraph_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/biocGraph_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biocGraph_1.26.0.tgz vignettes: vignettes/biocGraph/inst/doc/biocGraph.pdf, vignettes/biocGraph/inst/doc/layingOutPathways.pdf vignetteTitles: Examples of plotting graphs Using Rgraphviz, HOWTO layout pathways hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biocGraph/inst/doc/biocGraph.R, vignettes/biocGraph/inst/doc/layingOutPathways.R suggestsMe: BiocCaseStudies Package: BiocInstaller Version: 1.14.3 Depends: R (>= 3.1.0) Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 1bcf919334a89dbd67e0c60707780a06 NeedsCompilation: no Title: Install/Update Bioconductor and CRAN Packages Description: Installs/updates Bioconductor and CRAN packages biocViews: Software Author: Dan Tenenbaum and Biocore Team Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocInstaller_1.14.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocInstaller_1.14.3.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocInstaller_1.14.3.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocInstaller_1.14.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocInstaller_1.14.3.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affylmGUI importsMe: affy, AnnotationHub, BiocCheck, gcrma, oligoClasses, QuasR, webbioc suggestsMe: BSgenome, GOSemSim, pkgDepTools Package: BiocParallel Version: 0.6.1 Imports: methods, parallel, foreach, tools, BatchJobs, BBmisc, BiocGenerics Suggests: doParallel, snow, Rmpi, RUnit, BiocStyle, knitr License: GPL-2 | GPL-3 MD5sum: c3bda325c9136eadc138bbf0b951af2c NeedsCompilation: no Title: Bioconductor facilities for parallel evaluation Description: This package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects. biocViews: Infrastructure Author: Bioconductor Package Maintainer [cre], Martin Morgan [aut], Michel Lang [aut], Ryan Thompson [aut] Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/BiocParallel_0.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocParallel_0.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocParallel_0.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocParallel_0.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocParallel_0.6.1.tgz vignettes: vignettes/BiocParallel/inst/doc/Overview.pdf vignetteTitles: Introduction to BiocParallel hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiocParallel/inst/doc/Overview.R dependsOnMe: DEXSeq, GenomicFiles, pRoloc, ShortRead importsMe: ChIPQC, GenomicAlignments, h5vc, HTSeqGenie, synapter, TFBSTools, VariantFiltering, VariantTools suggestsMe: chimera Package: BiocStyle Version: 1.2.0 Suggests: knitr, BiocGenerics, RUnit License: Artistic-2.0 MD5sum: 178320cf980369efe9617e6a758c67e5 NeedsCompilation: no Title: Standard styles for vignettes and other Bioconductor documents Description: Provides standard formatting styles for Bioconductor documents. The vignette illustrates use and functionality. biocViews: Software Author: Martin Morgan, Andrzej Oles, Wolfgang Huber Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocStyle_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiocStyle_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BiocStyle_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BiocStyle_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiocStyle_1.2.0.tgz vignettes: vignettes/BiocStyle/inst/doc/LatexStyle.pdf vignetteTitles: Bioconductor LaTeX Style hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiocStyle/inst/doc/LatexStyle.R suggestsMe: affycoretools, AnnotationDbi, AnnotationForge, arrayQualityMetrics, BayesPeak, beadarray, bioassayR, BiocParallel, CAFE, ccrepe, CexoR, ChIPQC, cleaver, clipper, compcodeR, CRISPRseek, dagLogo, DESeq2, DEXSeq, DiffBind, easyRNASeq, EBImage, flowMap, GeneOverlap, GenomeInfoDb, GenomicAlignments, GenomicFeatures, GenomicFiles, GenomicRanges, ggbio, graphite, Gviz, HiTC, illuminaio, imageHTS, messina, motifStack, NarrowPeaks, nondetects, npGSEA, omicade4, plethy, qpgraph, QuasR, Rariant, Rcade, RefNet, ReQON, rfPred, rols, rpx, Rsamtools, sangerseqR, sapFinder, ShortRead, SigFuge, SomaticSignatures, SSPA, trackViewer, TurboNorm, VariantAnnotation, VariantFiltering Package: biocViews Version: 1.32.1 Depends: R (>= 2.4.0) Imports: Biobase, graph (>= 1.9.26), methods, RBGL (>= 1.13.5), tools, utils, XML, RCurl, RUnit, knitr Suggests: Biobase License: Artistic-2.0 MD5sum: 9bd5bf6b9d440cf9029001c67e018a2c NeedsCompilation: no Title: Categorized views of R package repositories Description: structures for vocabularies and narratives of views biocViews: Infrastructure Author: VJ Carey , BJ Harshfield , S Falcon Maintainer: Bioconductor Package Maintainer URL: http://www.bioconductor.org/packages/release/BiocViews.html source.ver: src/contrib/biocViews_1.32.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/biocViews_1.32.1.zip win64.binary.ver: bin/windows64/contrib/3.1/biocViews_1.32.1.zip mac.binary.ver: bin/macosx/contrib/3.1/biocViews_1.32.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biocViews_1.32.1.tgz vignettes: vignettes/biocViews/inst/doc/createReposHtml.pdf, vignettes/biocViews/inst/doc/HOWTO-BCV.pdf vignetteTitles: biocViews-CreateRepositoryHTML, biocViews-HOWTO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biocViews/inst/doc/createReposHtml.R, vignettes/biocViews/inst/doc/HOWTO-BCV.R dependsOnMe: Risa importsMe: BiocCheck Package: bioDist Version: 1.36.0 Depends: R (>= 2.0), methods, Biobase,KernSmooth Suggests: locfit License: Artistic-2.0 MD5sum: 8ef8a957e42051da61b6b95f62a12c3b NeedsCompilation: no Title: Different distance measures Description: A collection of software tools for calculating distance measures. biocViews: Software Author: B. Ding, R. Gentleman and Vincent Carey Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/bioDist_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bioDist_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bioDist_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bioDist_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bioDist_1.36.0.tgz vignettes: vignettes/bioDist/inst/doc/bioDist.pdf vignetteTitles: bioDist Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bioDist/inst/doc/bioDist.R dependsOnMe: flowQ suggestsMe: BiocCaseStudies Package: biomaRt Version: 2.20.0 Depends: methods Imports: utils, XML, RCurl, AnnotationDbi Suggests: annotate License: Artistic-2.0 MD5sum: ad5e7c7b1d28ef5396838ae223b264ed NeedsCompilation: no Title: Interface to BioMart databases (e.g. Ensembl, COSMIC ,Wormbase and Gramene) Description: In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining. biocViews: Annotation Author: Steffen Durinck , Wolfgang Huber Maintainer: Steffen Durinck source.ver: src/contrib/biomaRt_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/biomaRt_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/biomaRt_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/biomaRt_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biomaRt_2.20.0.tgz vignettes: vignettes/biomaRt/inst/doc/biomaRt.pdf vignetteTitles: The biomaRt users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biomaRt/inst/doc/biomaRt.R dependsOnMe: ChIPpeakAnno, customProDB, dagLogo, domainsignatures, DrugVsDisease, genefu, GenomeGraphs, MineICA, PSICQUIC, Roleswitch, VegaMC importsMe: affycoretools, ArrayExpressHTS, cobindR, customProDB, DEXSeq, easyRNASeq, GenomicFeatures, Gviz, HTSanalyzeR, IdMappingRetrieval, MEDIPS, metaseqR, methyAnalysis, phenoTest, R453Plus1Toolbox, RNAither, SeqGSEA suggestsMe: BiocCaseStudies, DESeq2, GeneAnswers, Genominator, isobar, massiR, MineICA, MiRaGE, oneChannelGUI, piano, Rcade, RIPSeeker, rTANDEM, rTRM, ShortRead, SIM, trackViewer Package: BioMVCClass Version: 1.32.0 Depends: R (>= 2.1.0), methods, MVCClass, Biobase, graph, Rgraphviz License: LGPL MD5sum: 431c84d9c5358c0cf73f9b5d5c4e0444 NeedsCompilation: no Title: Model-View-Controller (MVC) Classes That Use Biobase Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphAndNetwork Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/BioMVCClass_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BioMVCClass_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BioMVCClass_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BioMVCClass_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BioMVCClass_1.32.0.tgz vignettes: vignettes/BioMVCClass/inst/doc/BioMVCClass.pdf vignetteTitles: BioMVCClass hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioMVCClass/inst/doc/BioMVCClass.R Package: biomvRCNS Version: 1.4.0 Depends: IRanges, GenomicRanges, Gviz Imports: methods, mvtnorm Suggests: cluster, parallel, GenomicFeatures, dynamicTreeCut, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene License: GPL (>= 2) Archs: i386, x64 MD5sum: 2965a79c98141e72c6f9d3c83db7b11a NeedsCompilation: yes Title: Copy Number study and Segmentation for multivariate biological data Description: In this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing. biocViews: aCGH, CopyNumberVariation, Microarray, Sequencing, Sequencing, Visualization, Genetics Author: Yang Du Maintainer: Yang Du source.ver: src/contrib/biomvRCNS_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/biomvRCNS_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/biomvRCNS_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/biomvRCNS_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biomvRCNS_1.4.0.tgz vignettes: vignettes/biomvRCNS/inst/doc/biomvRCNS.pdf vignetteTitles: biomvRCNS package introduction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biomvRCNS/inst/doc/biomvRCNS.R Package: BioNet Version: 1.24.1 Depends: R (>= 2.10.0), Biobase, graph, RBGL Imports: igraph (>= 0.7), AnnotationDbi Suggests: rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML License: GPL (>= 2) MD5sum: 56e8b102902a1b406e28ed924183f07f NeedsCompilation: no Title: Routines for the functional analysis of biological networks Description: This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork. biocViews: Microarray, DataImport, GraphAndNetwork, Network, NetworkEnrichment, GeneExpression, DifferentialExpression Author: Marcus Dittrich and Daniela Beisser Maintainer: Marcus Dittrich URL: http://bionet.bioapps.biozentrum.uni-wuerzburg.de/ source.ver: src/contrib/BioNet_1.24.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/BioNet_1.24.1.zip win64.binary.ver: bin/windows64/contrib/3.1/BioNet_1.24.1.zip mac.binary.ver: bin/macosx/contrib/3.1/BioNet_1.24.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BioNet_1.24.1.tgz vignettes: vignettes/BioNet/inst/doc/Tutorial.pdf vignetteTitles: BioNet Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioNet/inst/doc/Tutorial.R importsMe: HTSanalyzeR Package: BioSeqClass Version: 1.22.0 Depends: R (>= 2.10), scatterplot3d Imports: Biostrings, ipred, e1071, klaR, randomForest, class, tree, nnet, rpart, party, foreign, Biobase, utils, stats, grDevices Suggests: scatterplot3d License: LGPL (>= 2.0) MD5sum: b257d005150304aab84d9b9894c802fe NeedsCompilation: no Title: Classification for Biological Sequences Description: Extracting Features from Biological Sequences and Building Classification Model biocViews: Classification Author: Li Hong sysptm@gmail.com Maintainer: Li Hong source.ver: src/contrib/BioSeqClass_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BioSeqClass_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BioSeqClass_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BioSeqClass_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BioSeqClass_1.22.0.tgz vignettes: vignettes/BioSeqClass/inst/doc/BioSeqClass.pdf vignetteTitles: Using the BioSeqClass Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioSeqClass/inst/doc/BioSeqClass.R Package: Biostrings Version: 2.32.1 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.5.4), IRanges (>= 1.21.35), XVector (>= 0.3.6) Imports: graphics, methods, stats, utils, BiocGenerics, IRanges, XVector, zlibbioc LinkingTo: IRanges, XVector Suggests: BSgenome (>= 1.13.14), BSgenome.Celegans.UCSC.ce2 (>= 1.3.11), BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg18, drosophila2probe, hgu95av2probe, hgu133aprobe, GenomicFeatures (>= 1.3.14), hgu95av2cdf, affy (>= 1.41.3), affydata (>= 1.11.5), RUnit Enhances: Rmpi License: Artistic-2.0 Archs: i386, x64 MD5sum: eaaf4742709dcae91caa7966a696f5fe NeedsCompilation: yes Title: String objects representing biological sequences, and matching algorithms Description: Memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences. biocViews: SequenceMatching, Genetics, Sequencing, Infrastructure, DataImport, DataRepresentation Author: H. Pages, P. Aboyoun, R. Gentleman, and S. DebRoy Maintainer: H. Pages source.ver: src/contrib/Biostrings_2.32.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Biostrings_2.32.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Biostrings_2.32.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Biostrings_2.32.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Biostrings_2.32.1.tgz vignettes: vignettes/Biostrings/inst/doc/Biostrings2Classes.pdf, vignettes/Biostrings/inst/doc/BiostringsQuickOverview.pdf, vignettes/Biostrings/inst/doc/matchprobes.pdf, vignettes/Biostrings/inst/doc/MultipleAlignments.pdf, vignettes/Biostrings/inst/doc/PairwiseAlignments.pdf vignetteTitles: A short presentation of the basic classes defined in Biostrings 2, Biostrings Quick Overview, Handling probe sequence information, Multiple Alignments, Pairwise Sequence Alignments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Biostrings/inst/doc/Biostrings2Classes.R, vignettes/Biostrings/inst/doc/BiostringsQuickOverview.R, vignettes/Biostrings/inst/doc/matchprobes.R, vignettes/Biostrings/inst/doc/MultipleAlignments.R, vignettes/Biostrings/inst/doc/PairwiseAlignments.R dependsOnMe: altcdfenvs, Basic4Cseq, BRAIN, BSgenome, ChIPpeakAnno, ChIPsim, cleaver, CRISPRseek, DASiR, DECIPHER, deepSNV, GeneRegionScan, genomes, GenomicAlignments, GOTHiC, iPAC, methVisual, minfi, MotifDb, motifRG, oligo, oneChannelGUI, qrqc, R453Plus1Toolbox, REDseq, rGADEM, Roleswitch, Rsamtools, rSFFreader, RSVSim, sangerseqR, SCAN.UPC, scsR, seqbias, ShortRead, triplex, waveTiling importsMe: AffyCompatible, AllelicImbalance, ArrayExpressHTS, BCRANK, BEAT, BioSeqClass, biovizBase, BSgenome, charm, ChIPseqR, ChIPsim, CNEr, cobindR, customProDB, dagLogo, easyRNASeq, ensemblVEP, gcrma, GeneRegionScan, GenomicAlignments, GenomicFeatures, ggbio, GGtools, girafe, gmapR, Gviz, gwascat, h5vc, HiTC, HTSeqGenie, KEGGREST, MEDIPS, MEDME, methVisual, microRNA, MotIV, oligoClasses, OTUbase, pdInfoBuilder, phyloseq, qrqc, QuasR, Rcpi, REDseq, Repitools, rGADEM, Rolexa, rSFFreader, rtracklayer, SeqArray, SomaticSignatures, synapter, TFBSTools, VariantAnnotation, VariantFiltering, VariantTools suggestsMe: annotate, CSAR, exomeCopy, GenomicRanges, genoset, methylumi, microRNA, MiRaGE, pcaGoPromoter, procoil, rpx, rTRM, XVector Package: biosvd Version: 1.0.0 Depends: R (>= 3.0.0) Imports: gplots, BiocGenerics, Biobase, methods, grid, hwriter, ReportingTools, graphics License: Artistic-2.0 MD5sum: c7f8434cbdb62e45f3a20db16aa559db NeedsCompilation: no Title: Package for high-throughput data processing, outlier detection, noise removal and dynamic modeling Description: The biosvd package contains functions to reduce the input data set from the feature x assay space to the reduced diagonalized eigenfeature x eigenassay space, with the eigenfeatures and eigenassays unique orthonormal superpositions of the features and assays, respectively. Results of SVD applied to the data can subsequently be inspected based on generated graphs, such as a heatmap of the eigenfeature x assay matrix and a bar plot with the eigenexpression fractions of all eigenfeatures. These graphs aid in deciding which eigenfeatures and eigenassays to filter out (i.e., eigenfeatures representing steady state, noise, or experimental artifacts; or when applied to the variance in the data, eigenfeatures representing steady-scale variance). After possible removal of steady state expression, steady-scale variance, noise and experimental artifacts, and after re-applying SVD to the normalized data, a summary html report of the eigensystem is generated, containing among others polar plots of the assays and features, a table with the list of features sortable according to their coordinates, radius and phase in the polar plot, and a visualization of the data sorted according to the two selected eigenfeatures and eigenassays with colored feature/assay annotation information when provided. This gives a global picture of the dynamics of expression/intensity levels, in which individual features and assays are classified in groups of similar regulation and function or similar cellular state and biological phenotype. biocViews: TimeCourse, Visualization Author: Anneleen Daemen , Matthew Brauer Maintainer: Anneleen Daemen , Matthew Brauer source.ver: src/contrib/biosvd_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/biosvd_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/biosvd_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/biosvd_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biosvd_1.0.0.tgz vignettes: vignettes/biosvd/inst/doc/biosvd.pdf vignetteTitles: biosvd hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biosvd/inst/doc/biosvd.R Package: biovizBase Version: 1.12.3 Depends: R (>= 2.10), methods Imports: methods, grDevices, stats, scales, Hmisc, RColorBrewer, dichromat, BiocGenerics, IRanges, GenomicRanges (>= 1.13.3), Biostrings, Rsamtools (>= 1.13.1), GenomicAlignments, GenomicFeatures, AnnotationDbi, VariantAnnotation Suggests: BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome, rtracklayer License: Artistic-2.0 Archs: i386, x64 MD5sum: 38c3862b0a4f3b7255220d58f2e59c1f NeedsCompilation: yes Title: Basic graphic utilities for visualization of genomic data. Description: The biovizBase package is designed to provide a set of utilities, color schemes and conventions for genomic data. It serves as the base for various high-level packages for biological data visualization. This saves development effort and encourages consistency. biocViews: Infrastructure, Visualization, Preprocessing Author: Tengfei Yin, Michael Lawrence, Dianne Cook Maintainer: Tengfei Yin source.ver: src/contrib/biovizBase_1.12.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/biovizBase_1.12.3.zip win64.binary.ver: bin/windows64/contrib/3.1/biovizBase_1.12.3.zip mac.binary.ver: bin/macosx/contrib/3.1/biovizBase_1.12.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/biovizBase_1.12.3.tgz vignettes: vignettes/biovizBase/inst/doc/intro.pdf vignetteTitles: An Introduction to biovizBase hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biovizBase/inst/doc/intro.R dependsOnMe: CAFE, qrqc importsMe: ggbio, Gviz, qrqc suggestsMe: Rariant Package: BiRewire Version: 1.6.5 Depends: igraph Suggests: RUnit, BiocGenerics License: GPL-3 Archs: i386, x64 MD5sum: 94b2c3d5dcd0846daaeb67f7d04cd415 NeedsCompilation: yes Title: High-performing routines for the randomization of a bipartite graph (or a binary event matrix) preserving degree distribution (or marginal totals). Description: Fast functions for bipartite network rewiring through N consecutive switching steps (See References) and for the computation of the minimal number of switching steps to be performed in order to maximise the dissimilarity with respect to the original network. Includes function for the analysis of the introduced randomness across the switching and several other routines to analyse the resulting networks and their natural projections. Extension to undirected networks (not bipartite) is also provided. biocViews: Network Author: Andrea Gobbi [aut], Davide Albanese [cbt], Francesco Iorio [cbt], Giuseppe Jurman [cbt], Julio Saez-Rodriguez [cbt] . Maintainer: Andrea Gobbi URL: http://www.ebi.ac.uk/~iorio/BiRewire source.ver: src/contrib/BiRewire_1.6.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiRewire_1.6.5.zip win64.binary.ver: bin/windows64/contrib/3.1/BiRewire_1.6.5.zip mac.binary.ver: bin/macosx/contrib/3.1/BiRewire_1.6.5.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiRewire_1.6.5.tgz vignettes: vignettes/BiRewire/inst/doc/BiRewire.pdf vignetteTitles: BiRewire hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiRewire/inst/doc/BiRewire.R Package: birta Version: 1.8.0 Depends: limma, MASS, R(>= 2.10), Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: f4e38d2b3cf8125f12e12059f41eb3b0 NeedsCompilation: yes Title: Bayesian Inference of Regulation of Transcriptional Activity Description: Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. birta (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of TFs and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states. biocViews: Microarray, Sequencing, GeneExpression, Transcription, GraphAndNetwork Author: Benedikt Zacher, Khalid Abnaof, Stephan Gade, Erfan Younesi, Achim Tresch, Holger Froehlich Maintainer: Benedikt Zacher , Holger Froehlich source.ver: src/contrib/birta_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/birta_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/birta_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/birta_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/birta_1.8.0.tgz vignettes: vignettes/birta/inst/doc/birta.pdf vignetteTitles: Bayesian Inference of Regulation of Transcriptional Activity hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/birta/inst/doc/birta.R Package: BiSeq Version: 1.4.2 Depends: R (>= 2.15.2), methods, IRanges (>= 1.17.24), GenomicRanges, Formula Imports: methods, BiocGenerics, Biobase, IRanges, GenomicRanges, rtracklayer, parallel, betareg, lokern, Formula, globaltest License: LGPL-3 MD5sum: 3cb9af6e3b9adb4a618ce5c63e8fcf16 NeedsCompilation: no Title: Processing and analyzing bisulfite sequencing data Description: The BiSeq package provides useful classes and functions to handle and analyze targeted bisulfite sequencing (BS) data such as reduced-representation bisulfite sequencing (RRBS) data. In particular, it implements an algorithm to detect differentially methylated regions (DMRs). The package takes already aligned BS data from one or multiple samples. biocViews: Genetics, Sequencing, MethylSeq, DNAMethylation Author: Katja Hebestreit, Hans-Ulrich Klein Maintainer: Katja Hebestreit source.ver: src/contrib/BiSeq_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/BiSeq_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/BiSeq_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/BiSeq_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BiSeq_1.4.2.tgz vignettes: vignettes/BiSeq/inst/doc/BiSeq.pdf vignetteTitles: An Introduction to BiSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BiSeq/inst/doc/BiSeq.R Package: BitSeq Version: 1.8.0 Depends: Rsamtools, zlibbioc Imports: IRanges LinkingTo: Rsamtools, zlibbioc Suggests: edgeR, DESeq License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: e2e041f1949775738c732a60dfbebc1d NeedsCompilation: yes Title: Transcript expression inference and differential expression analysis for RNA-seq data Description: The BitSeq package is targeted for transcript expression analysis and differential expression analysis of RNA-seq data in two stage process. In the first stage it uses Bayesian inference methodology to infer expression of individual transcripts from individual RNA-seq experiments. The second stage of BitSeq embraces the differential expression analysis of transcript expression. Providing expression estimates from replicates of multiple conditions, Log-Normal model of the estimates is used for inferring the condition mean transcript expression and ranking the transcripts based on the likelihood of differential expression. biocViews: GeneExpression, DifferentialExpression, Sequencing, RNASeq Author: Peter Glaus, Antti Honkela and Magnus Rattray Maintainer: Peter Glaus source.ver: src/contrib/BitSeq_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BitSeq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BitSeq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BitSeq_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BitSeq_1.8.0.tgz vignettes: vignettes/BitSeq/inst/doc/BitSeq.pdf vignetteTitles: BitSeq User Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/BitSeq/inst/doc/BitSeq.R Package: BRAIN Version: 1.10.1 Depends: R (>= 2.8.1), PolynomF, Biostrings, lattice License: GPL-2 MD5sum: cdbe172993da16f7d96103d8f798ed07 NeedsCompilation: no Title: Baffling Recursive Algorithm for Isotope distributioN calculations Description: Package for calculating aggregated isotopic distribution and exact center-masses for chemical substances (in this version composed of C, H, N, O and S). This is an implementation of the BRAIN algorithm described in the paper by J. Claesen, P. Dittwald, T. Burzykowski and D. Valkenborg. biocViews: MassSpectrometry, Proteomics Author: Piotr Dittwald, with contributions of Dirk Valkenborg and Jurgen Claesen Maintainer: Piotr Dittwald source.ver: src/contrib/BRAIN_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/BRAIN_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/BRAIN_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/BRAIN_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BRAIN_1.10.1.tgz vignettes: vignettes/BRAIN/inst/doc/BRAIN-vignette.pdf vignetteTitles: BRAIN Usage hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BRAIN/inst/doc/BRAIN-vignette.R suggestsMe: cleaver Package: BrainStars Version: 1.8.0 Depends: RCurl, Biobase, methods Imports: RJSONIO, Biobase License: Artistic-2.0 MD5sum: b5a1a37bc86da506da5924c31e677d91 NeedsCompilation: no Title: query gene expression data and plots from BrainStars (B*) Description: This package can search and get gene expression data and plots from BrainStars (B*). BrainStars is a quantitative expression database of the adult mouse brain. The database has genome-wide expression profile at 51 adult mouse CNS regions. biocViews: Microarray, OneChannel, DataImport Author: Itoshi NIKAIDO Maintainer: Itoshi NIKAIDO source.ver: src/contrib/BrainStars_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BrainStars_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BrainStars_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BrainStars_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BrainStars_1.8.0.tgz vignettes: vignettes/BrainStars/inst/doc/BrainStars.pdf vignetteTitles: BrainStars hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BrainStars/inst/doc/BrainStars.R Package: bridge Version: 1.28.0 Depends: R (>= 1.9.0), rama License: GPL (>= 2) Archs: i386, x64 MD5sum: ca2fbbaf31d72656b722f3335a007132 NeedsCompilation: yes Title: Bayesian Robust Inference for Differential Gene Expression Description: Test for differentially expressed genes with microarray data. This package can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. biocViews: Microarray,OneChannel,TwoChannel,DifferentialExpression Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/bridge_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bridge_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bridge_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bridge_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bridge_1.28.0.tgz vignettes: vignettes/bridge/inst/doc/bridge.pdf vignetteTitles: bridge Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bridge/inst/doc/bridge.R Package: BSgenome Version: 1.32.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.1.2), IRanges (>= 1.13.6), GenomicRanges (>= 1.15.9), Biostrings (>= 2.23.3) Imports: methods, BiocGenerics, IRanges, GenomicRanges, XVector, Biostrings, Rsamtools Suggests: BiocInstaller, BSgenome.Celegans.UCSC.ce2 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg19.masked, SNPlocs.Hsapiens.dbSNP.20100427, hgu95av2probe, Biobase, GenomeInfoDb, RUnit License: Artistic-2.0 MD5sum: ed71b9d8b23ea959e29487f6bd688e41 NeedsCompilation: no Title: Infrastructure for Biostrings-based genome data packages Description: Infrastructure shared by all the Biostrings-based genome data packages biocViews: Genetics, Infrastructure, DataRepresentation, SequenceMatching, Annotation, SNP Author: Herve Pages Maintainer: H. Pages source.ver: src/contrib/BSgenome_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BSgenome_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BSgenome_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BSgenome_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BSgenome_1.32.0.tgz vignettes: vignettes/BSgenome/inst/doc/BSgenomeForge.pdf, vignettes/BSgenome/inst/doc/GenomeSearching.pdf vignetteTitles: How to forge a BSgenome data package, Efficient genome searching with Biostrings and the BSgenome data packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BSgenome/inst/doc/BSgenomeForge.R, vignettes/BSgenome/inst/doc/GenomeSearching.R dependsOnMe: CAGEr, chipseq, cleanUpdTSeq, CRISPRseek, GenomicAlignments, GOTHiC, htSeqTools, MEDIPS, motifRG, REDseq, rGADEM importsMe: BEAT, charm, ChIPpeakAnno, chipseq, cobindR, ggbio, girafe, gmapR, Gviz, MEDIPS, MethylSeekR, PING, QuasR, R453Plus1Toolbox, Repitools, rtracklayer, TFBSTools, VariantAnnotation, VariantFiltering suggestsMe: Biostrings, biovizBase, easyRNASeq, GeneRegionScan, GenomeInfoDb, GenomicFeatures, GenomicRanges, genoset, MEDIPS, MiRaGE, oneChannelGUI, QDNAseq, spliceR, waveTiling Package: bsseq Version: 1.0.0 Depends: R (>= 2.15), methods, BiocGenerics, IRanges, GenomicRanges, parallel, matrixStats Imports: scales, stats, graphics, Biobase, locfit Suggests: RUnit, bsseqData License: Artistic-2.0 MD5sum: 6dd6ca0dcbc603503655981bbcec4d7c NeedsCompilation: no Title: Analyze, manage and store bisulfite sequencing data Description: Tools for analyzing and visualizing bisulfite sequencing data biocViews: DNAMethylation Author: Kasper Daniel Hansen [aut, cre] Maintainer: Kasper Daniel Hansen source.ver: src/contrib/bsseq_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/bsseq_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/bsseq_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/bsseq_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bsseq_1.0.0.tgz vignettes: vignettes/bsseq/inst/doc/bsseq_analysis.pdf, vignettes/bsseq/inst/doc/bsseq.pdf vignetteTitles: Analyzing WGBS with bsseq, The bsseq user's guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bsseq/inst/doc/bsseq_analysis.R, vignettes/bsseq/inst/doc/bsseq.R Package: BufferedMatrix Version: 1.28.0 Depends: R (>= 2.6.0), methods License: LGPL (>= 2) Archs: i386, x64 MD5sum: 53e92954768ef94395a152dcc2b1c6a5 NeedsCompilation: yes Title: A matrix data storage object held in temporary files Description: A tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data. biocViews: Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/BufferedMatrix_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BufferedMatrix_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BufferedMatrix_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BufferedMatrix_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BufferedMatrix_1.28.0.tgz vignettes: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.pdf vignetteTitles: BufferedMatrix: Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.R dependsOnMe: BufferedMatrixMethods Package: BufferedMatrixMethods Version: 1.28.0 Depends: R (>= 2.6.0), BufferedMatrix (>= 1.3.0), methods LinkingTo: BufferedMatrix Suggests: affyio, affy License: GPL (>= 2) Archs: i386, x64 MD5sum: 67b8c355750e35c6ee507cd36bb5248d NeedsCompilation: yes Title: Microarray Data related methods that utlize BufferedMatrix objects Description: Microarray analysis methods that use BufferedMatrix objects biocViews: Infrastructure Author: B. M. Bolstad Maintainer: B. M. Bolstad URL: http://www.bmbolstad.com source.ver: src/contrib/BufferedMatrixMethods_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BufferedMatrixMethods_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BufferedMatrixMethods_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BufferedMatrixMethods_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BufferedMatrixMethods_1.28.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: bumphunter Version: 1.4.2 Depends: R (>= 2.10), IRanges, GenomicRanges, foreach, iterators, methods, parallel, locfit Imports: matrixStats, limma, doRNG, BiocGenerics, utils Suggests: RUnit, BiocGenerics, doParallel, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: be66ffbeabfbdeccda9b8d0f31eff06f NeedsCompilation: no Title: Bump Hunter Description: Tools for finding bumps in genomic data biocViews: DNAMethylation, Epigenetics, Infrastructure, MultipleComparison Author: Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen, Harris A. Jaffee Maintainer: Rafael A. Irizarry source.ver: src/contrib/bumphunter_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/bumphunter_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/bumphunter_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/bumphunter_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/bumphunter_1.4.2.tgz vignettes: vignettes/bumphunter/inst/doc/bumphunter.pdf vignetteTitles: The bumphunter user's guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/bumphunter/inst/doc/bumphunter.R dependsOnMe: minfi Package: BUS Version: 1.20.0 Depends: R (>= 2.3.0), minet Imports: stats, infotheo License: GPL-3 Archs: i386, x64 MD5sum: db4b54b388e72220c23c365391d737e9 NeedsCompilation: yes Title: Gene network reconstruction Description: This package can be used to compute associations among genes (gene-networks) or between genes and some external traits (i.e. clinical). biocViews: Preprocessing Author: Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini Maintainer: Yuanhua Liu source.ver: src/contrib/BUS_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/BUS_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/BUS_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/BUS_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/BUS_1.20.0.tgz vignettes: vignettes/BUS/inst/doc/bus.pdf vignetteTitles: bus.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BUS/inst/doc/bus.R Package: CAFE Version: 1.0.0 Depends: R (>= 2.10), biovizBase, GenomicRanges, IRanges, ggbio Imports: affy, ggplot2, annotate, grid, gridExtra, tcltk, Biobase Suggests: RUnit, BiocGenerics, BiocStyle License: GPL-3 MD5sum: 5c5332085d6d21508e82c9dc2ac00de9 NeedsCompilation: no Title: Chromosmal Aberrations Finder in Expression data Description: Detection and visualizations of gross chromosomal aberrations using Affymetrix expression microarrays as input biocViews: GeneExpression, Microarray, OneChannel, GeneSetEnrichment Author: Sander Bollen Maintainer: Sander Bollen source.ver: src/contrib/CAFE_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CAFE_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CAFE_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CAFE_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CAFE_1.0.0.tgz vignettes: vignettes/CAFE/inst/doc/CAFE-manual.pdf vignetteTitles: Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CAFE/inst/doc/CAFE-manual.R Package: CAGEr Version: 1.6.1 Depends: methods, R (>= 2.15.0), BSgenome Imports: Rsamtools, GenomicRanges, IRanges, data.table, beanplot, rtracklayer, som, VGAM Suggests: BSgenome.Drerio.UCSC.danRer7, FANTOM3and4CAGE Enhances: parallel License: GPL-3 MD5sum: cdd6cadb628495c7451d679004bc9268 NeedsCompilation: no Title: Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining Description: Preprocessing of CAGE sequencing data, identification and normalization of transcription start sites and downstream analysis of transcription start sites clusters (promoters). biocViews: Preprocessing, Sequencing, HighThroughputSequencing, Transcription, Clustering, Visualization Author: Vanja Haberle, Department of Biology, University of Bergen, Norway Maintainer: Vanja Haberle source.ver: src/contrib/CAGEr_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/CAGEr_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/CAGEr_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/CAGEr_1.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CAGEr_1.6.1.tgz vignettes: vignettes/CAGEr/inst/doc/CAGEr.pdf vignetteTitles: CAGEr hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CAGEr/inst/doc/CAGEr.R Package: CALIB Version: 1.30.0 Depends: R (>= 2.10), limma, methods Imports: limma, methods, graphics, stats, utils License: LGPL Archs: i386, x64 MD5sum: 302065a505e87241ccd002214f4a33de NeedsCompilation: yes Title: Calibration model for estimating absolute expression levels from microarray data Description: This package contains functions for normalizing spotted microarray data, based on a physically motivated calibration model. The model parameters and error distributions are estimated from external control spikes. biocViews: Microarray,TwoChannel,Preprocessing Author: Hui Zhao, Kristof Engelen, Bart De Moor and Kathleen Marchal Maintainer: Hui Zhao source.ver: src/contrib/CALIB_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CALIB_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CALIB_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CALIB_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CALIB_1.30.0.tgz vignettes: vignettes/CALIB/inst/doc/quickstart.pdf vignetteTitles: CALIB Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CALIB/inst/doc/quickstart.R Package: CAMERA Version: 1.20.0 Depends: R (>= 2.1.0), methods, Biobase, xcms (>= 1.13.5), igraph Imports: methods, xcms, RBGL, graph, graphics, grDevices, stats, utils, Hmisc, igraph Suggests: faahKO, RUnit, BiocGenerics Enhances: Rmpi, snow License: GPL (>= 2) Archs: i386, x64 MD5sum: 03c0613339814dd9b707a9a12b424f10 NeedsCompilation: yes Title: Collection of annotation related methods for mass spectrometry data Description: Annotation of peaklists generated by xcms, rule based annotation of isotopes and adducts, EIC correlation based tagging of unknown adducts and fragments biocViews: MassSpectrometry Author: Carsten Kuhl, Ralf Tautenhahn, Steffen Neumann {ckuhl|sneumann}@ipb-halle.de, rtautenh@scripps.edu Maintainer: Carsten Kuhl URL: http://msbi.ipb-halle.de/msbi/CAMERA/ source.ver: src/contrib/CAMERA_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CAMERA_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CAMERA_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CAMERA_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CAMERA_1.20.0.tgz vignettes: vignettes/CAMERA/inst/doc/CAMERA.pdf vignetteTitles: Molecule Identification with CAMERA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CAMERA/inst/doc/CAMERA.R dependsOnMe: metaMS suggestsMe: RMassBank Package: cancerclass Version: 1.8.0 Depends: R (>= 2.14.0), Biobase, binom, methods, stats Suggests: cancerdata License: GPL 3 Archs: i386, x64 MD5sum: 62ce4046506899fa9c94ac54f2dc2a73 NeedsCompilation: yes Title: Development and validation of diagnostic tests from high-dimensional molecular data Description: The classification protocol starts with a feature selection step and continues with nearest-centroid classification. The accurarcy of the predictor can be evaluated using training and test set validation, leave-one-out cross-validation or in a multiple random validation protocol. Methods for calculation and visualization of continuous prediction scores allow to balance sensitivity and specificity and define a cutoff value according to clinical requirements. biocViews: Cancer, Microarray, Classification, Visualization Author: Jan Budczies, Daniel Kosztyla Maintainer: Daniel Kosztyla source.ver: src/contrib/cancerclass_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cancerclass_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cancerclass_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cancerclass_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cancerclass_1.8.0.tgz vignettes: vignettes/cancerclass/inst/doc/vignette_cancerclass.pdf vignetteTitles: Cancerclass: An R package for development and validation of diagnostic tests from high-dimensional molecular data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cancerclass/inst/doc/vignette_cancerclass.R Package: CancerMutationAnalysis Version: 1.8.0 Depends: R (>= 2.10.0), qvalue Imports: AnnotationDbi, limma, methods, stats Suggests: KEGG.db License: GPL (>= 2) + file LICENSE Archs: i386, x64 MD5sum: 361bef79df30357a32d6e1341691bc29 NeedsCompilation: yes Title: Cancer mutation analysis Description: This package implements gene and gene-set level analysis methods for somatic mutation studies of cancer. The gene-level methods distinguish between driver genes (which play an active role in tumorigenesis) and passenger genes (which are mutated in tumor samples, but have no role in tumorigenesis) and incorporate a two-stage study design. The gene-set methods implement a patient-oriented approach, which calculates gene-set scores for each sample, then combines them across samples; a gene-oriented approach which uses the Wilcoxon test is also provided for comparison. biocViews: Genetics, Software Author: Giovanni Parmigiani, Simina M. Boca Maintainer: Simina M. Boca source.ver: src/contrib/CancerMutationAnalysis_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CancerMutationAnalysis_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CancerMutationAnalysis_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CancerMutationAnalysis_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CancerMutationAnalysis_1.8.0.tgz vignettes: vignettes/CancerMutationAnalysis/inst/doc/CancerMutationAnalysis.pdf vignetteTitles: CancerMutationAnalysisTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Package: casper Version: 1.9.0 Depends: R (>= 2.14.1), Biobase, IRanges, methods, GenomicRanges Imports: BiocGenerics, EBarrays, gaga, gtools, GenomicFeatures, mgcv, Rsamtools, rtracklayer, sqldf, survival, VGAM Enhances: parallel License: GPL (>=2) Archs: i386, x64 MD5sum: d8f26bb4428ccf13b720347f6b993443 NeedsCompilation: yes Title: Characterization of Alternative Splicing based on Paired-End Reads Description: Infer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision. biocViews: GeneExpression, DifferentialExpression, Transcription, RNASeq, Sequencing Author: David Rossell, Camille Stephan-Otto, Manuel Kroiss, Miranda Stobbe Maintainer: David Rossell source.ver: src/contrib/casper_1.9.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/casper_1.9.0.zip win64.binary.ver: bin/windows64/contrib/3.1/casper_1.9.0.zip mac.binary.ver: bin/macosx/contrib/3.1/casper_1.9.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/casper_1.9.0.tgz vignettes: vignettes/casper/inst/doc/casper.pdf vignetteTitles: Manual for the casper library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/casper/inst/doc/casper.R Package: Category Version: 2.30.0 Depends: BiocGenerics, AnnotationDbi, Biobase, Matrix, GO.db, methods Imports: BiocGenerics, graph, methods, Biobase, AnnotationDbi, RBGL, GSEABase (>= 1.19.3), genefilter, annotate (>= 1.15.6), stats, utils Suggests: EBarrays, ALL, Rgraphviz, RColorBrewer, xtable (>= 1.4-6), hgu95av2.db, KEGG.db, SNPchip, geneplotter, limma, lattice, graph, Biobase, genefilter, methods, RUnit, org.Sc.sgd.db, GOstats License: Artistic-2.0 MD5sum: d9d5eef63a165aa9c6f2c1cf9c6fadba NeedsCompilation: no Title: Category Analysis Description: A collection of tools for performing category analysis. biocViews: Annotation, GO, Pathways, GeneSetEnrichment Author: R. Gentleman with contributions from S. Falcon and D.Sarkar Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Category_2.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Category_2.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Category_2.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Category_2.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Category_2.30.0.tgz vignettes: vignettes/Category/inst/doc/Category.pdf, vignettes/Category/inst/doc/ChromBand.pdf vignetteTitles: Using Categories to Analyze Microarray Data, Using Chromosome Bands as Categories hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Category/inst/doc/Category.R, vignettes/Category/inst/doc/ChromBand.R dependsOnMe: GOstats, meshr, PCpheno importsMe: categoryCompare, cellHTS2, eisa, gCMAP, GOstats, interactiveDisplay, PCpheno, phenoTest, ppiStats, RDAVIDWebService suggestsMe: BiocCaseStudies, cellHTS, MmPalateMiRNA Package: categoryCompare Version: 1.8.0 Depends: R (>= 2.10), Biobase, BiocGenerics Imports: AnnotationDbi, hwriter, GSEABase, Category, GOstats, annotate, colorspace, graph, RCytoscape (>= 1.5.11) Suggests: methods, GO.db, KEGG.db, estrogen, org.Hs.eg.db, hgu95av2.db, limma, affy, genefilter License: GPL-2 MD5sum: 36577cd91e6da83f59edda5bbed0ba7e NeedsCompilation: no Title: Meta-analysis of high-throughput experiments using feature annotations Description: Calculates significant annotations (categories) in each of two (or more) feature (i.e. gene) lists, determines the overlap between the annotations, and returns graphical and tabular data about the significant annotations and which combinations of feature lists the annotations were found to be significant. Interactive exploration is facilitated through the use of RCytoscape (heavily suggested). biocViews: Annotation, GO, MultipleComparison, Pathways, GeneExpression Author: Robert M. Flight Maintainer: Robert M. Flight SystemRequirements: Cytoscape (>= 2.8.0) (if used for visualization of results, heavily suggested), CytoscapeRPC plugin (>= 1.8) source.ver: src/contrib/categoryCompare_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/categoryCompare_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/categoryCompare_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/categoryCompare_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/categoryCompare_1.8.0.tgz vignettes: vignettes/categoryCompare/inst/doc/categoryCompare_vignette.pdf vignetteTitles: categoryCompare: High-throughput data meta-analysis using gene annotations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: ccrepe Version: 1.0.0 Imports: infotheo (>= 1.1) Suggests: knitr, BiocStyle, BiocGenerics License: MIT + file LICENSE MD5sum: 41f054a76b6fbe9031eb977afab40f7d NeedsCompilation: no Title: ccrepe_and_nc.score Description: The CCREPE (Compositionality Corrected by REnormalizaion and PErmutation) package is designed to assess the significance of general similarity measures in compositional datasets. In microbial abundance data, for example, the total abundances of all microbes sum to one; CCREPE is designed to take this constraint into account when assigning p-values to similarity measures between the microbes. The package has two functions: ccrepe: Calculates similarity measures, p-values and q-values for relative abundances of bugs in one or two body sites using bootstrap and permutation matrices of the data. nc.score: Calculates species-level co-variation and co-exclusion patterns based on an extension of the checkerboard score to ordinal data. biocViews: StatisticalMethod, Metagenomics, Software Author: Emma Schwager ,Craig Bielski, George Weingart Maintainer: Emma Schwager ,Craig Bielski, George Weingart VignetteBuilder: knitr source.ver: src/contrib/ccrepe_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ccrepe_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ccrepe_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ccrepe_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ccrepe_1.0.0.tgz vignettes: vignettes/ccrepe/inst/doc/ccrepe.pdf vignetteTitles: ccrepe hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ccrepe/inst/doc/ccrepe.R Package: cellGrowth Version: 1.8.0 Depends: R (>= 2.12.0), locfit (>= 1.5-4) Imports: lattice License: Artistic-2.0 MD5sum: 8c70fb31553088c16f054e781d9f706a NeedsCompilation: no Title: Fitting cell population growth models Description: This package provides functionalities for the fitting of cell population growth models on experimental OD curves. biocViews: CellBasedAssays, MicrotitrePlateAssay, DataImport, Visualization, TimeCourse Author: Julien Gagneur , Andreas Neudecker Maintainer: Julien Gagneur source.ver: src/contrib/cellGrowth_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cellGrowth_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cellGrowth_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cellGrowth_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cellGrowth_1.8.0.tgz vignettes: vignettes/cellGrowth/inst/doc/cellGrowth.pdf vignetteTitles: Overview of the cellGrowth package. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellGrowth/inst/doc/cellGrowth.R Package: cellHTS Version: 1.34.0 Depends: R (>= 2.10), prada (>= 1.9.4), RColorBrewer, Biobase (>= 1.11.12), genefilter (>= 1.11.2) Suggests: Category, GO.db, vsn (>= 2.0.35) License: Artistic-2.0 MD5sum: 5e60aa3733221ea53ba1d65cb4080874 NeedsCompilation: no Title: Analysis of cell-based screens Description: Analysis of cell-based RNA interference screens biocViews: CellBasedAssays, Visualization Author: Wolfgang Huber , Ligia Bras , Michael Boutros Maintainer: Ligia Bras URL: http://www.dkfz.de/signaling, http://www.ebi.ac.uk/huber source.ver: src/contrib/cellHTS_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cellHTS_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cellHTS_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cellHTS_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cellHTS_1.34.0.tgz vignettes: vignettes/cellHTS/inst/doc/cellhts.pdf, vignettes/cellHTS/inst/doc/twoChannels.pdf, vignettes/cellHTS/inst/doc/twoWay.pdf vignetteTitles: Main vignette: End-to-end analysis of cell-based screens, Supplement: multi-channel assays, Supplement: two-way assays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellHTS/inst/doc/cellhts.R, vignettes/cellHTS/inst/doc/twoChannels.R, vignettes/cellHTS/inst/doc/twoWay.R suggestsMe: prada Package: cellHTS2 Version: 2.28.0 Depends: R (>= 2.10), RColorBrewer, Biobase, methods, genefilter, splots, vsn, hwriter, locfit, grid Imports: prada, GSEABase, Category, stats4 License: Artistic-2.0 MD5sum: a776de45023278eba463df20618ae8c3 NeedsCompilation: no Title: Analysis of cell-based screens - revised version of cellHTS Description: This package provides tools for the analysis of high-throughput assays that were performed in microtitre plate formats (including but not limited to 384-well plates). The functionality includes data import and management, normalisation, quality assessment, replicate summarisation and statistical scoring. A webpage that provides a detailed graphical overview over the data and analysis results is produced. In our work, we have applied the package to RNAi screens on fly and human cells, and for screens of yeast libraries. See ?cellHTS2 for a brief introduction. biocViews: CellBasedAssays, Preprocessing, Visualization Author: Ligia Bras, Wolfgang Huber , Michael Boutros , Gregoire Pau , Florian Hahne Maintainer: Joseph Barry URL: http://www.dkfz.de/signaling, http://www.ebi.ac.uk/huber source.ver: src/contrib/cellHTS2_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cellHTS2_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cellHTS2_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cellHTS2_2.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cellHTS2_2.28.0.tgz vignettes: vignettes/cellHTS2/inst/doc/cellhts2Complete.pdf, vignettes/cellHTS2/inst/doc/cellhts2.pdf, vignettes/cellHTS2/inst/doc/twoChannels.pdf, vignettes/cellHTS2/inst/doc/twoWay.pdf vignetteTitles: Main vignette (complete version): End-to-end analysis of cell-based screens, Main vignette: End-to-end analysis of cell-based screens, Supplement: multi-channel assays, Supplement: enhancer-suppressor screens hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellHTS2/inst/doc/cellhts2Complete.R, vignettes/cellHTS2/inst/doc/cellhts2.R, vignettes/cellHTS2/inst/doc/twoChannels.R, vignettes/cellHTS2/inst/doc/twoWay.R dependsOnMe: coRNAi, imageHTS, staRank importsMe: HTSanalyzeR, RNAinteract Package: CellNOptR Version: 1.10.0 Depends: R (>= 2.15.0), RBGL, graph, methods, hash, ggplot2, RCurl, Rgraphviz, XML Suggests: RUnit, BiocGenerics, igraph License: GPL-3 Archs: i386, x64 MD5sum: f1fba7425bdd02d192d8ee260832142b NeedsCompilation: yes Title: Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data. Description: This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network. biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, TimeCourse Author: T.Cokelaer, F.Eduati, A.MacNamara, S.Schrier, C.Terfve Maintainer: T.Cokelaer SystemRequirements: Graphviz version >= 2.2 source.ver: src/contrib/CellNOptR_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CellNOptR_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CellNOptR_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CellNOptR_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CellNOptR_1.10.0.tgz vignettes: vignettes/CellNOptR/inst/doc/CellNOptR-vignette.pdf vignetteTitles: Main vignette:Playing with networks using CellNOptR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CellNOptR/inst/doc/CellNOptR-vignette.R dependsOnMe: CNORdt, CNORfeeder, CNORfuzzy, CNORode Package: CexoR Version: 1.2.0 Depends: R (>= 2.10.0), IRanges Imports: Rsamtools, GenomicRanges, rtracklayer, idr Suggests: RUnit, BiocGenerics, BiocStyle License: Artistic-2.0 | GPL-2 + file LICENSE MD5sum: 1c48ebec4b5042f76c975ef1aa87a0a4 NeedsCompilation: no Title: An R package to uncover high-resolution protein-DNA interactions in ChIP-exo replicates Description: Strand specific peak-pair calling in ChIP-exo replicates. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalized count differences of opposed sign at each DNA strand (peak-pairs). Irreproducible discovery rate for overlapping peak-pairs across biological replicates is estimated using the package 'idr'. biocViews: Transcription, Genetics, Sequencing Author: Pedro Madrigal Maintainer: Pedro Madrigal source.ver: src/contrib/CexoR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CexoR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CexoR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CexoR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CexoR_1.2.0.tgz vignettes: vignettes/CexoR/inst/doc/CexoR.pdf vignetteTitles: CexoR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/CexoR/inst/doc/CexoR.R Package: CGEN Version: 2.6.1 Depends: R (>= 2.10.1), survival Suggests: cluster License: GPL-2 + file LICENSE Archs: i386, x64 MD5sum: a596c1e3fd303a6a4ef24b805a4d975c NeedsCompilation: yes Title: An R package for analysis of case-control studies in genetic epidemiology Description: An R package for analysis of case-control studies in genetic epidemiology biocViews: SNP, MultipleComparison, Clustering Author: Samsiddhi Bhattacharjee, Nilanjan Chatterjee, Summer Han and William Wheeler Maintainer: William Wheeler source.ver: src/contrib/CGEN_2.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/CGEN_2.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/CGEN_2.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/CGEN_2.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CGEN_2.6.1.tgz vignettes: vignettes/CGEN/inst/doc/vignette.pdf vignetteTitles: CGEN Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/CGEN/inst/doc/vignette.R Package: CGHbase Version: 1.24.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), marray License: GPL MD5sum: e4cadbd9c3ea21c88aebcba7b1c1e432 NeedsCompilation: no Title: CGHbase: Base functions and classes for arrayCGH data analysis. Description: Contains functions and classes that are needed by arrayCGH packages. biocViews: Infrastructure, Microarray, CopyNumberVariation Author: Sjoerd Vosse, Mark van de Wiel Maintainer: Mark van de Wiel source.ver: src/contrib/CGHbase_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CGHbase_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CGHbase_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CGHbase_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CGHbase_1.24.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: CGHcall, CGHnormaliter, CGHregions, sigaR importsMe: CGHnormaliter, plrs, QDNAseq Package: CGHcall Version: 2.26.0 Depends: R (>= 2.0.0), impute(>= 1.8.0), DNAcopy (>= 1.6.0), methods, Biobase, CGHbase (>= 1.15.1), snowfall License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: cfdbbcb1293108e84560b937a54fc382 NeedsCompilation: no Title: Calling aberrations for array CGH tumor profiles. Description: Calls aberrations for array CGH data using a six state mixture model as well as several biological concepts that are ignored by existing algorithms. Visualization of profiles is also provided. biocViews: Microarray,Preprocessing,Visualization Author: Mark van de Wiel, Sjoerd Vosse Maintainer: Mark van de Wiel source.ver: src/contrib/CGHcall_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CGHcall_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CGHcall_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CGHcall_2.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CGHcall_2.26.0.tgz vignettes: vignettes/CGHcall/inst/doc/CGHcall.pdf vignetteTitles: CGHcall hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHcall/inst/doc/CGHcall.R dependsOnMe: CGHnormaliter importsMe: CGHnormaliter, QDNAseq Package: cghMCR Version: 1.22.0 Depends: methods, DNAcopy, CNTools, limma Imports: BiocGenerics (>= 0.1.6), stats4 License: LGPL MD5sum: 4bc6a1875219b0218999ddf260c28365 NeedsCompilation: no Title: Find chromosome regions showing common gains/losses Description: This package provides functions to identify genomic regions of interests based on segmented copy number data from multiple samples. biocViews: Microarray, CopyNumberVariation Author: J. Zhang and B. Feng Maintainer: J. Zhang source.ver: src/contrib/cghMCR_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cghMCR_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cghMCR_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cghMCR_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cghMCR_1.22.0.tgz vignettes: vignettes/cghMCR/inst/doc/findMCR.pdf vignetteTitles: cghMCR findMCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cghMCR/inst/doc/findMCR.R Package: CGHnormaliter Version: 1.18.0 Depends: CGHcall (>= 2.17.0), CGHbase (>= 1.15.0) Imports: Biobase, CGHbase, CGHcall, methods, stats, utils License: GPL (>= 3) MD5sum: 9beee3216314bfad1ead2ad3e414542a NeedsCompilation: no Title: Normalization of array CGH data with imbalanced aberrations. Description: Normalization and centralization of array comparative genomic hybridization (aCGH) data. The algorithm uses an iterative procedure that effectively eliminates the influence of imbalanced copy numbers. This leads to a more reliable assessment of copy number alterations (CNAs). biocViews: Microarray, Preprocessing Author: Bart P.P. van Houte, Thomas W. Binsl, Hannes Hettling Maintainer: Bart P.P. van Houte source.ver: src/contrib/CGHnormaliter_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CGHnormaliter_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CGHnormaliter_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CGHnormaliter_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CGHnormaliter_1.18.0.tgz vignettes: vignettes/CGHnormaliter/inst/doc/CGHnormaliter.pdf vignetteTitles: CGHnormaliter hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHnormaliter/inst/doc/CGHnormaliter.R Package: CGHregions Version: 1.22.0 Depends: R (>= 2.0.0), methods, Biobase, CGHbase License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: d14c06d03dd279d8c1ad075bfe70efb5 NeedsCompilation: no Title: Dimension Reduction for Array CGH Data with Minimal Information Loss. Description: Dimension Reduction for Array CGH Data with Minimal Information Loss biocViews: Microarray, CopyNumberVariation, Visualization Author: Sjoerd Vosse & Mark van de Wiel Maintainer: Sjoerd Vosse source.ver: src/contrib/CGHregions_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CGHregions_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CGHregions_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CGHregions_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CGHregions_1.22.0.tgz vignettes: vignettes/CGHregions/inst/doc/CGHregions.pdf vignetteTitles: CGHcall hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHregions/inst/doc/CGHregions.R suggestsMe: ADaCGH2 Package: ChAMP Version: 1.2.8 Depends: R (>= 3.0.1), minfi, ChAMPdata, Illumina450ProbeVariants.db Imports: sva, IlluminaHumanMethylation450kmanifest, limma, RPMM, DNAcopy, preprocessCore, impute, marray, wateRmelon, plyr License: GPL-3 MD5sum: 0608e334e91b291ab6099467ab66cd00 NeedsCompilation: no Title: Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 Description: The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number aberrations. biocViews: Microarray, MethylationArray, Normalization, TwoChannel, CopyNumber Author: Tiffany Morris, Lee Butcher, Andy Feber, Andrew Teschendorff, Ankur Chakravarthy and Stephan Beck Maintainer: Tiffany Morris source.ver: src/contrib/ChAMP_1.2.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChAMP_1.2.8.zip win64.binary.ver: bin/windows64/contrib/3.1/ChAMP_1.2.8.zip mac.binary.ver: bin/macosx/contrib/3.1/ChAMP_1.2.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChAMP_1.2.8.tgz vignettes: vignettes/ChAMP/inst/doc/ChAMP.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChAMP/inst/doc/ChAMP.R Package: charm Version: 2.10.1 Depends: R (>= 2.14.0), Biobase, SQN, fields, RColorBrewer, genefilter Imports: BSgenome, Biobase, oligo (>= 1.11.31), oligoClasses(>= 1.17.39), ff, preprocessCore, methods, stats, Biostrings, IRanges, siggenes, nor1mix, gtools, grDevices, graphics, utils, limma, parallel, sva(>= 3.1.2) Suggests: charmData, BSgenome.Hsapiens.UCSC.hg18, corpcor License: LGPL (>= 2) MD5sum: b1ec8d554217d7d3cafd8c6ae5e8e6ef NeedsCompilation: no Title: Analysis of DNA methylation data from CHARM microarrays Description: This package implements analysis tools for DNA methylation data generated using Nimblegen microarrays and the McrBC protocol. It finds differentially methylated regions between samples, calculates percentage methylation estimates and includes array quality assessment tools. biocViews: Microarray, DNAMethylation Author: Martin Aryee, Peter Murakami, Harris Jaffee, Rafael Irizarry Maintainer: Peter Murakami source.ver: src/contrib/charm_2.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/charm_2.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/charm_2.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/charm_2.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/charm_2.10.1.tgz vignettes: vignettes/charm/inst/doc/charm.pdf vignetteTitles: charm Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/charm/inst/doc/charm.R Package: ChemmineOB Version: 1.2.9 Depends: R (>= 2.15.1), methods Imports: BiocGenerics, zlibbioc LinkingTo: BH Suggests: ChemmineR, BiocStyle,knitr,knitcitations Enhances: ChemmineR (>= 2.13.0) License: file LICENSE Archs: i386, x64 MD5sum: 0252ad63c02f4edbef42cc5e98c86f62 NeedsCompilation: yes Title: R interface to a subset of OpenBabel functionalities Description: ChemmineOB provides an R interface to a subset of cheminformatics functionalities implemented by the OpelBabel C++ project. OpenBabel is an open source cheminformatics toolbox that includes utilities for structure format interconversions, descriptor calculations, compound similarity searching and more. ChemineOB aims to make a subset of these utilities available from within R. For non-developers, ChemineOB is primarily intended to be used from ChemmineR as an add-on package rather than used directly. biocViews: Cheminformatics Author: Kevin Horan, Thomas Girke Maintainer: Kevin Horan URL: http://manuals.bioinformatics.ucr.edu/home/chemminer VignetteBuilder: knitr source.ver: src/contrib/ChemmineOB_1.2.9.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChemmineOB_1.2.9.zip win64.binary.ver: bin/windows64/contrib/3.1/ChemmineOB_1.2.9.zip mac.binary.ver: bin/macosx/contrib/3.1/ChemmineOB_1.2.9.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChemmineOB_1.2.9.tgz vignettes: vignettes/ChemmineOB/inst/doc/ hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ChemmineOB/inst/doc/ChemmineOB.R htmlDocs: vignettes/ChemmineOB/inst/doc/ChemmineOB.html htmlTitles: "ChemmineOB" suggestsMe: ChemmineR Package: ChemmineR Version: 2.16.9 Depends: R (>= 2.10.0), methods Imports: graphics, methods, stats, RCurl, DBI, digest, BiocGenerics Suggests: RSQLite, scatterplot3d, gplots, fmcsR,snow, RPostgreSQL, BiocStyle,knitr,knitcitations, ChemmineOB Enhances: ChemmineOB License: Artistic-2.0 Archs: i386, x64 MD5sum: 9987be638add7562bce496311347f655 NeedsCompilation: yes Title: Cheminformatics Toolkit for R Description: ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. Its latest version contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures. biocViews: MicrotitrePlateAssay, CellBasedAssays, Visualization, Infrastructure, DataImport, Clustering, Bioinformatics, Proteomics Author: Y. Eddie Cao, Kevin Horan, Tyler Backman, Thomas Girke Maintainer: ChemmineR Team URL: http://manuals.bioinformatics.ucr.edu/home/chemminer VignetteBuilder: knitr source.ver: src/contrib/ChemmineR_2.16.9.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChemmineR_2.16.9.zip win64.binary.ver: bin/windows64/contrib/3.1/ChemmineR_2.16.9.zip mac.binary.ver: bin/macosx/contrib/3.1/ChemmineR_2.16.9.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChemmineR_2.16.9.tgz vignettes: vignettes/ChemmineR/inst/doc/ hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChemmineR/inst/doc/ChemmineR.R htmlDocs: vignettes/ChemmineR/inst/doc/ChemmineR.html htmlTitles: "ChemmineR" dependsOnMe: eiR, fmcsR importsMe: Rchemcpp, Rcpi suggestsMe: bioassayR, ChemmineOB Package: chimera Version: 1.6.16 Depends: Biobase, GenomicRanges (>= 1.13.3), Rsamtools (>= 1.13.1), GenomicAlignments, methods, AnnotationDbi, org.Hs.eg.db, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene Suggests: BiocParallel Enhances: Rsubread, BSgenome.Mmusculus.UCSC.mm9, TxDb.Mmusculus.UCSC.mm9.knownGene, org.Mm.eg.db License: Artistic-2.0 MD5sum: 3c168175b78d335a1fa20439fed39d82 NeedsCompilation: no Title: A package for secondary analysis of fusion products Description: This package facilitates the characterisation of fusion products events. It allows to import fusion data results from the following fusion finders: chimeraScan, bellerophontes, deFuse, FusionFinder, FusionHunter, mapSplice, tophat-fusion, FusionMap, STAR, Rsubread, fusionCatcher. biocViews: Infrastructure Author: Raffaele A Calogero, Matteo Carrara, Marco Beccuti, Francesca Cordero, Federica Cavallo Maintainer: Raffaele A Calogero SystemRequirements: STAR, TopHat, bowtie and samtools are required for some functionalities source.ver: src/contrib/chimera_1.6.16.tar.gz win.binary.ver: bin/windows/contrib/3.1/chimera_1.6.16.zip win64.binary.ver: bin/windows64/contrib/3.1/chimera_1.6.16.zip mac.binary.ver: bin/macosx/contrib/3.1/chimera_1.6.16.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/chimera_1.6.16.tgz vignettes: vignettes/chimera/inst/doc/chimera.pdf vignetteTitles: chimera hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chimera/inst/doc/chimera.R dependsOnMe: oneChannelGUI Package: chipenrich Version: 1.2.0 Depends: R (>= 2.15.1) Imports: chipenrich.data, methods, GenomicRanges (>= 1.10.0), IRanges (>= 1.16.0), mgcv, plyr (>= 1.7.0), lattice, latticeExtra, grid, stringr (>= 0.6), reshape License: GPL-3 MD5sum: 0ee579208398d60f473f15ce990a3bdf NeedsCompilation: no Title: Gene set enrichment for ChIP-seq peak data Description: ChIP-Enrich performs gene set enrichment testing using peaks called from a ChIP-seq experiment. The method empirically corrects for confounding factors such as the length of genes, and the mappability of the sequence surrounding genes. biocViews: Software, GeneSetEnrichment Author: Ryan P. Welch [aut, cre, cph], Chee Lee [ctb], Laura J. Scott [ths], Maureen A. Sartor [ths] Maintainer: Ryan P. Welch source.ver: src/contrib/chipenrich_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/chipenrich_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/chipenrich_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/chipenrich_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/chipenrich_1.2.0.tgz vignettes: vignettes/chipenrich/inst/doc/chipenrich.pdf vignetteTitles: ChIP-Enrich Vignette/Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chipenrich/inst/doc/chipenrich.R Package: ChIPpeakAnno Version: 2.14.1 Depends: R (>= 2.10), grid,VennDiagram, biomaRt, IRanges, Biostrings Imports: BiocGenerics (>= 0.1.0), GO.db, BSgenome, GenomicFeatures, AnnotationDbi, limma, multtest Suggests: reactome.db, BSgenome.Ecoli.NCBI.20080805, org.Hs.eg.db, gplots, RUnit License: GPL (>= 2) MD5sum: ecab1c86e2c12d987e7a758391513066 NeedsCompilation: no Title: Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments or any experiments resulted in large number of chromosome ranges. Description: The package includes functions to retrieve the sequences around the peak, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. Starting 2.0.5, new functions have been added for finding the peaks with bi-directional promoters with summary statistics (peaksNearBDP), for summarizing the occurrence of motifs in peaks (summarizePatternInPeaks) and for adding other IDs to annotated peaks or enrichedGO (addGeneIDs). This package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages biocViews: Annotation, ChIPSeq, ChIPchip Author: Lihua Julie Zhu, Herve Pages, Claude Gazin, Nathan Lawson, Jianhong Ou, Ryan Thompson, Simon Lin, David Lapointe and Michael Green Maintainer: Lihua Julie Zhu source.ver: src/contrib/ChIPpeakAnno_2.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChIPpeakAnno_2.14.1.zip win64.binary.ver: bin/windows64/contrib/3.1/ChIPpeakAnno_2.14.1.zip mac.binary.ver: bin/macosx/contrib/3.1/ChIPpeakAnno_2.14.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPpeakAnno_2.14.1.tgz vignettes: vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.pdf vignetteTitles: ChIPpeakAnno Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPpeakAnno/inst/doc/ChIPpeakAnno.R dependsOnMe: REDseq importsMe: FunciSNP, REDseq suggestsMe: oneChannelGUI, RIPSeeker Package: ChIPQC Version: 1.0.9 Depends: R (>= 3.0.0), ggplot2, DiffBind Imports: BiocGenerics (>= 0.8.0), Rsamtools (>= 1.14.2), GenomicRanges (>= 1.14.4), chipseq (>= 1.12.0), GenomicAlignments (>= 0.99.2), gtools, BiocParallel, methods, IRanges, reshape2, Nozzle.R1, Biobase,grDevices, stats, utils Suggests: BiocStyle, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Hsapiens.UCSC.hg18.knownGene, TxDb.Mmusculus.UCSC.mm10.knownGene, TxDb.Mmusculus.UCSC.mm9.knownGene, TxDb.Rnorvegicus.UCSC.rn4.ensGene, TxDb.Celegans.UCSC.ce6.ensGene, TxDb.Dmelanogaster.UCSC.dm3.ensGene License: GPL (>= 3) MD5sum: acbf38b61212598e80ff314bc9516ed4 NeedsCompilation: no Title: Quality metrics for ChIPseq data Description: Quality metrics for ChIPseq data biocViews: Sequencing, ChIPSeq, QualityControl, ReportWriting Author: Tom Carroll, Wei Liu, Ines de Santiago, Rory Stark Maintainer: Tom Carroll , Rory Stark source.ver: src/contrib/ChIPQC_1.0.9.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChIPQC_1.0.9.zip win64.binary.ver: bin/windows64/contrib/3.1/ChIPQC_1.0.9.zip mac.binary.ver: bin/macosx/contrib/3.1/ChIPQC_1.0.9.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPQC_1.0.9.tgz vignettes: vignettes/ChIPQC/inst/doc/ChIPQC.pdf, vignettes/ChIPQC/inst/doc/ChIPQCSampleReport.pdf vignetteTitles: Assessing ChIP-seq sample quality with ChIPQC, ChIPQCSampleReport.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPQC/inst/doc/ChIPQC.R Package: ChIPseeker Version: 1.0.11 Depends: R (>= 2.10) Imports: AnnotationDbi, BiocGenerics, IRanges, GenomicFeatures, GenomicRanges, ggplot2, gplots, grDevices, gtools, Matrix, plyr, RColorBrewer, rtracklayer, TxDb.Hsapiens.UCSC.hg19.knownGene Suggests: clusterProfiler, ReactomePA, DOSE, GOSemSim, org.Hs.eg.db, knitr License: Artistic-2.0 MD5sum: fd61b801f9edfede55ea57e480cd94a5 NeedsCompilation: no Title: ChIPseeker for ChIP peak Annotation, Comparison, and Visualization Description: This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes. biocViews: Annotation, ChIPSeq, Software, Visualization, MultipleComparison Author: Guangchuang Yu Maintainer: Guangchuang Yu VignetteBuilder: knitr source.ver: src/contrib/ChIPseeker_1.0.11.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChIPseeker_1.0.11.zip win64.binary.ver: bin/windows64/contrib/3.1/ChIPseeker_1.0.11.zip mac.binary.ver: bin/macosx/contrib/3.1/ChIPseeker_1.0.11.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPseeker_1.0.11.tgz vignettes: vignettes/ChIPseeker/inst/doc/ChIPseeker.pdf vignetteTitles: ChIPseeker: an R package for ChIP peak Annotation,, Comparison,, and Visualization hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPseeker/inst/doc/ChIPseeker.R suggestsMe: ReactomePA Package: chipseq Version: 1.14.0 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.4), GenomicRanges (>= 1.7.7), BSgenome, ShortRead Imports: methods, BiocGenerics, IRanges, BSgenome, GenomicRanges, lattice, ShortRead, stats Suggests: GenomicFeatures, TxDb.Mmusculus.UCSC.mm9.knownGene License: Artistic-2.0 Archs: i386, x64 MD5sum: c0621ae77e3ffd63ab40526f2af6d316 NeedsCompilation: yes Title: chipseq: A package for analyzing chipseq data Description: Tools for helping process short read data for chipseq experiments biocViews: ChIPSeq Author: Deepayan Sarkar, Robert Gentleman, Michael Lawrence, Zizhen Yao Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/chipseq_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/chipseq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/chipseq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/chipseq_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/chipseq_1.14.0.tgz vignettes: vignettes/chipseq/inst/doc/Workflow.pdf vignetteTitles: A Sample ChIP-Seq analysis workflow hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chipseq/inst/doc/Workflow.R dependsOnMe: PING importsMe: ChIPQC, HTSeqGenie suggestsMe: ggbio, oneChannelGUI Package: ChIPseqR Version: 1.18.0 Depends: R (>= 2.10.0), methods, BiocGenerics, ShortRead Imports: Biostrings, fBasics, GenomicRanges, graphics, grDevices, HilbertVis, IRanges, methods, ShortRead, stats, timsac, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: c25ce46ffe38e9f5bdd6ff21c78f5607 NeedsCompilation: yes Title: Identifying Protein Binding Sites in High-Throughput Sequencing Data Description: ChIPseqR identifies protein binding sites from ChIP-seq and nucleosome positioning experiments. The model used to describe binding events was developed to locate nucleosomes but should flexible enough to handle other types of experiments as well. biocViews: ChIPSeq, Infrastructure Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPseqR_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChIPseqR_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ChIPseqR_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ChIPseqR_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPseqR_1.18.0.tgz vignettes: vignettes/ChIPseqR/inst/doc/Introduction.pdf vignetteTitles: Introduction to ChIPseqR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPseqR/inst/doc/Introduction.R Package: ChIPsim Version: 1.18.0 Depends: Biostrings (>= 2.29.2) Imports: IRanges, XVector, Biostrings, ShortRead, graphics, methods, stats, utils Suggests: actuar, zoo License: GPL (>= 2) MD5sum: 9453a904ed1886d3647b18f65cde4c93 NeedsCompilation: no Title: Simulation of ChIP-seq experiments Description: A general framework for the simulation of ChIP-seq data. Although currently focused on nucleosome positioning the package is designed to support different types of experiments. biocViews: Infrastructure, ChIPSeq Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPsim_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChIPsim_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ChIPsim_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ChIPsim_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPsim_1.18.0.tgz vignettes: vignettes/ChIPsim/inst/doc/ChIPsimIntro.pdf vignetteTitles: Simulating ChIP-seq experiments hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPsim/inst/doc/ChIPsimIntro.R Package: ChIPXpress Version: 1.6.0 Depends: R (>= 2.10), ChIPXpressData Imports: Biobase, GEOquery, frma, affy, bigmemory, biganalytics Suggests: mouse4302frmavecs, mouse4302.db, mouse4302cdf, RUnit, BiocGenerics License: GPL(>=2) MD5sum: 659868e1034bb843e834d89f5bee5f25 NeedsCompilation: no Title: ChIPXpress: enhanced transcription factor target gene identification from ChIP-seq and ChIP-chip data using publicly available gene expression profiles Description: ChIPXpress takes as input predicted TF bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target. biocViews: ChIPchip, ChIPSeq Author: George Wu Maintainer: George Wu source.ver: src/contrib/ChIPXpress_1.6.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/ChIPXpress_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChIPXpress_1.6.0.tgz vignettes: vignettes/ChIPXpress/inst/doc/ChIPXpress.pdf vignetteTitles: ChIPXpress hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChIPXpress/inst/doc/ChIPXpress.R Package: chopsticks Version: 1.28.2 Depends: R(>= 2.10.0), survival, methods Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: bcd08f61dcc08cdbccfd7ef26a3d1a0a NeedsCompilation: yes Title: The snp.matrix and X.snp.matrix classes Description: Implements classes and methods for large-scale SNP association studies biocViews: Microarray, SNPsAndGeneticVariability, SNP, GeneticVariability Author: Hin-Tak Leung Maintainer: Hin-Tak Leung URL: http://outmodedbonsai.sourceforge.net/ source.ver: src/contrib/chopsticks_1.28.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/chopsticks_1.28.2.zip win64.binary.ver: bin/windows64/contrib/3.1/chopsticks_1.28.2.zip mac.binary.ver: bin/macosx/contrib/3.1/chopsticks_1.28.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/chopsticks_1.28.2.tgz vignettes: vignettes/chopsticks/inst/doc/chopsticks-vignette.pdf vignetteTitles: snpMatrix hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chopsticks/inst/doc/chopsticks-vignette.R Package: chroGPS Version: 1.8.1 Depends: R (>= 2.13.0), IRanges, methods, Biobase, MASS, graphics, stats, rgl, changepoint Imports: graphics, cluster, DPpackage, ICSNP Enhances: parallel, XML License: GPL (>=2) MD5sum: 6524621d1d1d7b7fdc07a93b665a0cc8 NeedsCompilation: no Title: chroGPS: visualizing the epigenome Description: We provide intuitive maps to visualize the association between genetic elements, with emphasis on epigenetics. The approach is based on Multi-Dimensional Scaling. We provide several sensible distance metrics, and adjustment procedures to remove systematic biases typically observed when merging data obtained under different technologies or genetic backgrounds. biocViews: Visualization, Clustering Author: Oscar Reina, David Rossell Maintainer: Oscar Reina source.ver: src/contrib/chroGPS_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/chroGPS_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/chroGPS_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/chroGPS_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/chroGPS_1.8.1.tgz vignettes: vignettes/chroGPS/inst/doc/chroGPS.pdf vignetteTitles: Manual for the chroGPS library hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chroGPS/inst/doc/chroGPS.R Package: ChromHeatMap Version: 1.18.0 Depends: R (>= 2.9.0), BiocGenerics (>= 0.3.2), annotate (>= 1.20.0), AnnotationDbi (>= 1.4.0) Imports: Biobase (>= 2.17.8), graphics, grDevices, methods, stats, IRanges, rtracklayer Suggests: ALL, hgu95av2.db License: Artistic-2.0 MD5sum: f939e0db9c117b7495a79c88692d5f4a NeedsCompilation: no Title: Heat map plotting by genome coordinate Description: The ChromHeatMap package can be used to plot genome-wide data (e.g. expression, CGH, SNP) along each strand of a given chromosome as a heat map. The generated heat map can be used to interactively identify probes and genes of interest. biocViews: Visualization Author: Tim F. Rayner Maintainer: Tim F. Rayner source.ver: src/contrib/ChromHeatMap_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ChromHeatMap_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ChromHeatMap_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ChromHeatMap_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ChromHeatMap_1.18.0.tgz vignettes: vignettes/ChromHeatMap/inst/doc/ChromHeatMap.pdf vignetteTitles: Plotting expression data with ChromHeatMap hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChromHeatMap/inst/doc/ChromHeatMap.R Package: cisPath Version: 1.4.8 Depends: R (>= 2.10.0) Imports: methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: b54cb554f82bd671e98050b807e83799 NeedsCompilation: yes Title: Visualization and management of the protein-protein interaction networks. Description: cisPath is an R package that uses web browsers to visualize and manage protein-protein interaction networks. biocViews: Proteomics Author: Likun Wang Maintainer: Likun Wang source.ver: src/contrib/cisPath_1.4.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/cisPath_1.4.8.zip win64.binary.ver: bin/windows64/contrib/3.1/cisPath_1.4.8.zip mac.binary.ver: bin/macosx/contrib/3.1/cisPath_1.4.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cisPath_1.4.8.tgz vignettes: vignettes/cisPath/inst/doc/cisPath.pdf vignetteTitles: cisPath hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cisPath/inst/doc/cisPath.R Package: cleanUpdTSeq Version: 1.2.0 Depends: R (>= 2.15), BiocGenerics (>= 0.1.0), BSgenome, BSgenome.Drerio.UCSC.danRer7, GenomicRanges, seqinr, e1071 License: GPL-2 MD5sum: 0ef73e6f65cff0fc0fbc24e1a2bebdbf NeedsCompilation: no Title: This package classifies putative polyadenylation sites as true or false/internally oligodT primed. Description: This package uses the Naive Bayes classifier (from e1071) to assign probability values to putative polyadenylation sites (pA sites) based on training data from zebrafish. This will allow the user to separate true, biologically relevant pA sites from false, oligodT primed pA sites. biocViews: Sequencing, SequenceMatching, Genetics, GeneRegulation Author: Sarah Sheppard, Jianhong Ou, Nathan Lawson, Lihua Julie Zhu Maintainer: Sarah Sheppard ; Jianhong Ou ; Lihua Julie Zhu source.ver: src/contrib/cleanUpdTSeq_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cleanUpdTSeq_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cleanUpdTSeq_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cleanUpdTSeq_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cleanUpdTSeq_1.2.0.tgz vignettes: vignettes/cleanUpdTSeq/inst/doc/cleanUpdTSeq.pdf vignetteTitles: cleanUpdTSeq Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cleanUpdTSeq/inst/doc/cleanUpdTSeq.R Package: cleaver Version: 1.2.0 Depends: R (>= 3.0.0), methods, Biostrings (>= 1.29.8) Imports: IRanges Suggests: testthat (>= 0.8), knitr, BiocStyle (>= 0.0.14), BRAIN, UniProt.ws (>= 2.1.4) License: GPL (>= 3) MD5sum: 7fc48c63811b9b48c6d094d9089cea2c NeedsCompilation: no Title: Cleavage of polypeptide sequences Description: In-silico cleavage of polypeptide sequences. The cleavage rules are taken from: http://web.expasy.org/peptide_cutter/peptidecutter_enzymes.html biocViews: Proteomics Author: Sebastian Gibb [aut, cre] Maintainer: Sebastian Gibb URL: https://github.com/sgibb/cleaver/ VignetteBuilder: knitr source.ver: src/contrib/cleaver_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cleaver_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cleaver_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cleaver_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cleaver_1.2.0.tgz vignettes: vignettes/cleaver/inst/doc/cleaver.pdf vignetteTitles: in-silico cleavage of polypeptides hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cleaver/inst/doc/cleaver.R importsMe: synapter Package: clippda Version: 1.14.0 Depends: R (>= 2.13.1),limma, statmod, rgl, lattice, scatterplot3d, graphics, grDevices, stats, utils, Biobase, tools, methods License: GPL (>=2) MD5sum: 0626f3b9da6579ebef309bb37056ff52 NeedsCompilation: no Title: A package for the clinical proteomic profiling data analysis Description: Methods for the nalysis of data from clinical proteomic profiling studies. The focus is on the studies of human subjects, which are often observational case-control by design and have technical replicates. A method for sample size determination for planning these studies is proposed. It incorporates routines for adjusting for the expected heterogeneities and imbalances in the data and the within-sample replicate correlations. biocViews: Proteomics, OneChannel, Preprocessing, DifferentialExpression, MultipleComparison, SampleSize Author: Stephen Nyangoma Maintainer: Stephen Nyangoma URL: http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml source.ver: src/contrib/clippda_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clippda_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clippda_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clippda_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clippda_1.14.0.tgz vignettes: vignettes/clippda/inst/doc/clippda.pdf vignetteTitles: Sample Size Calculation hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clippda/inst/doc/clippda.R Package: clipper Version: 1.4.0 Depends: R (>= 2.15.0), Matrix, graph Imports: methods, Biobase, Rcpp, igraph, gRbase (>= 1.6.6), qpgraph, KEGGgraph, corpcor, RBGL Suggests: RUnit, BiocGenerics, RCytoscape (>= 1.6.3), graphite, ALL, hgu95av2.db, MASS, BiocStyle License: AGPL-3 MD5sum: f7dae06128a36ed7740f217aef2d7d43 NeedsCompilation: no Title: Gene set analysis exploiting pathway topology Description: clipper is a package for topological gene set analysis. It implements a two-step empirical approach based on the exploitation of graph decomposition into a junction tree to reconstruct the most relevant signal path. In the first step clipper selects significant pathways according to statistical tests on the means and the concentration matrices of the graphs derived from pathway topologies. Then, it "clips" the whole pathway identifying the signal paths having the greatest association with a specific phenotype. Author: Paolo Martini , Gabriele Sales , Chiara Romualdi Maintainer: Paolo Martini source.ver: src/contrib/clipper_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clipper_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clipper_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clipper_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clipper_1.4.0.tgz vignettes: vignettes/clipper/inst/doc/clipper.pdf vignetteTitles: clipper hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clipper/inst/doc/clipper.R suggestsMe: graphite Package: Clomial Version: 1.0.0 Depends: R (>= 2.10), matrixStats Imports: methods License: GPL (>= 2) MD5sum: 9546cf5bc99f19922eb123d6ba21c287 NeedsCompilation: no Title: Infers clonal composition of a tumor Description: Clomial fits binomial distributions to counts obtained from Next Gen Sequencing data of multiple samples of the same tumor. The trained parameters can be interpreted to infer the clonal structure of the tumor. biocViews: Genetics, GeneticVariability, Sequencing, Clustering, MultipleComparison, Bayesian, DNASeq, ExomeSeq, TargetedResequencing Author: Habil Zare and Alex Hu Maintainer: Habil Zare source.ver: src/contrib/Clomial_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Clomial_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Clomial_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Clomial_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Clomial_1.0.0.tgz vignettes: vignettes/Clomial/inst/doc/Clonal_decomposition_by_Clomial.pdf vignetteTitles: A likelihood maximization approach to infer the clonal structure of a cancer using multiple tumor samples hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: Clonality Version: 1.12.0 Depends: R (>= 2.12.2), DNAcopy Imports: DNAcopy, grDevices, graphics, stats, utils Suggests: gdata, DNAcopy License: GPL-3 MD5sum: 870d2dd6dfd3df442c9675a59e352101 NeedsCompilation: no Title: Clonality testing Description: Statistical tests for clonality versus independence of tumors from the same patient based on their LOH or genomewide copy number profiles biocViews: Microarray, CopyNumberVariation, Classification, aCGH Author: Irina Ostrovnaya Maintainer: Irina Ostrovnaya source.ver: src/contrib/Clonality_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Clonality_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Clonality_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Clonality_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Clonality_1.12.0.tgz vignettes: vignettes/Clonality/inst/doc/Clonality.pdf vignetteTitles: Clonality hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Clonality/inst/doc/Clonality.R Package: clonotypeR Version: 1.2.1 Depends: methods Suggests: BiocGenerics, edgeR, knitr, pvclust, RUnit, vegan License: file LICENSE MD5sum: a83c79259582b494924e8f407274bb0b NeedsCompilation: no Title: High throughput analysis of T cell antigen receptor sequences Description: High throughput analysis of T cell antigen receptor sequences The genes encoding T cell receptors are created by somatic recombination, generating an immense combination of V, (D) and J segments. Additional processes during the recombination create extra sequence diversity between the V an J segments. Collectively, this hyper-variable region is called the CDR3 loop. . The purpose of this package is to process and quantitatively analyse millions of V-CDR3-J combination, called clonotypes, from multiple sequence libraries. biocViews: Sequencing Author: Charles Plessy Maintainer: Charles Plessy VignetteBuilder: knitr source.ver: src/contrib/clonotypeR_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/clonotypeR_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/clonotypeR_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/clonotypeR_1.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clonotypeR_1.2.1.tgz vignettes: vignettes/clonotypeR/inst/doc/ hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/clonotypeR/inst/doc/clonotypeR.R htmlDocs: vignettes/clonotypeR/inst/doc/clonotypeR.html htmlTitles: "clonotypeR User's Guide" Package: clst Version: 1.12.0 Depends: R (>= 2.10) Imports: ROC, lattice Suggests: RUnit License: GPL-3 MD5sum: 21485c9bcafbf2649d2b774cf01475eb NeedsCompilation: no Title: Classification by local similarity threshold Description: Package for modified nearest-neighbor classification based on calculation of a similarity threshold distinguishing within-group from between-group comparisons. biocViews: Classification Author: Noah Hoffman Maintainer: Noah Hoffman source.ver: src/contrib/clst_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clst_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clst_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clst_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clst_1.12.0.tgz vignettes: vignettes/clst/inst/doc/clstDemo.pdf vignetteTitles: clst hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clst/inst/doc/clstDemo.R dependsOnMe: clstutils Package: clstutils Version: 1.12.0 Depends: R (>= 2.10), clst, rjson, ape Imports: lattice, RSQLite Suggests: RUnit, RSVGTipsDevice License: GPL-3 MD5sum: c3443eb67f65a43504b6b43be3800dce NeedsCompilation: no Title: Tools for performing taxonomic assignment. Description: Tools for performing taxonomic assignment based on phylogeny using pplacer and clst. biocViews: Sequencing, Classification, Visualization, QualityControl Author: Noah Hoffman Maintainer: Noah Hoffman source.ver: src/contrib/clstutils_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clstutils_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clstutils_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clstutils_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clstutils_1.12.0.tgz vignettes: vignettes/clstutils/inst/doc/pplacerDemo.pdf, vignettes/clstutils/inst/doc/refSet.pdf vignetteTitles: clst, clstutils hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clstutils/inst/doc/pplacerDemo.R, vignettes/clstutils/inst/doc/refSet.R Package: clusterProfiler Version: 1.12.0 Depends: R (>= 2.10), ggplot2 Imports: methods, stats4, plyr, AnnotationDbi, GO.db, KEGG.db, DOSE, GOSemSim Suggests: org.Hs.eg.db, ReactomePA, pathview, knitr License: Artistic-2.0 MD5sum: 45f083fa1a37f4455a323fa138e80cd2 NeedsCompilation: no Title: statistical analysis and visulization of functional profiles for genes and gene clusters Description: The package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters. biocViews: Clustering, GO, Pathways, Visualization, MultipleComparison, GeneSetEnrichment Author: Guangchuang Yu, Li-Gen Wang Maintainer: Guangchuang Yu URL: http://online.liebertpub.com/doi/abs/10.1089/omi.2011.0118 VignetteBuilder: knitr source.ver: src/contrib/clusterProfiler_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clusterProfiler_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clusterProfiler_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clusterProfiler_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clusterProfiler_1.12.0.tgz vignettes: vignettes/clusterProfiler/inst/doc/clusterProfiler.pdf vignetteTitles: An introduction to clusterProfiler hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clusterProfiler/inst/doc/clusterProfiler.R suggestsMe: ChIPseeker, DOSE, GOSemSim, ReactomePA Package: clusterStab Version: 1.36.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), methods Suggests: fibroEset, genefilter License: Artistic-2.0 MD5sum: 810ba2bc3d0f5b3e3d6df00eace367b2 NeedsCompilation: no Title: Compute cluster stability scores for microarray data Description: This package can be used to estimate the number of clusters in a set of microarray data, as well as test the stability of these clusters. biocViews: Clustering Author: James W. MacDonald, Debashis Ghosh, Mark Smolkin Maintainer: James W. MacDonald source.ver: src/contrib/clusterStab_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/clusterStab_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/clusterStab_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/clusterStab_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/clusterStab_1.36.0.tgz vignettes: vignettes/clusterStab/inst/doc/clusterStab.pdf vignetteTitles: clusterStab Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clusterStab/inst/doc/clusterStab.R Package: CMA Version: 1.22.0 Depends: R (>= 2.10), methods, stats, Biobase Suggests: MASS, class, nnet, glmnet, e1071, randomForest, plsgenomics, gbm, mgcv, corpcor, limma, st, mvtnorm License: GPL (>= 2) MD5sum: 0d3bdb3c7e47cf038e746bbd489cda0c NeedsCompilation: no Title: Synthesis of microarray-based classification Description: This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment. biocViews: Classification Author: Martin Slawski , Anne-Laure Boulesteix , Christoph Bernau . Maintainer: Christoph Bernau source.ver: src/contrib/CMA_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CMA_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CMA_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CMA_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CMA_1.22.0.tgz vignettes: vignettes/CMA/inst/doc/CMA_vignette.pdf vignetteTitles: CMA_vignette.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CMA/inst/doc/CMA_vignette.R Package: CNAnorm Version: 1.10.1 Depends: R (>= 2.10.1), methods Imports: DNAcopy License: GPL-2 Archs: i386, x64 MD5sum: 071e435ad7e216e9596421eef0307ebb NeedsCompilation: yes Title: A normalization method for Copy Number Aberration in cancer samples Description: Performs ratio, GC content correction and normalization of data obtained using low coverage (one read every 100-10,000 bp) high troughput sequencing. It performs a "discrete" normalization looking for the ploidy of the genome. It will also provide tumour content if at least two ploidy states can be found. biocViews: CopyNumberVariation, Sequencing, Cancer, Lung Author: Stefano Berri , Henry M. Wood , Arief Gusnanto Maintainer: Stefano Berri URL: http://www.r-project.org, source.ver: src/contrib/CNAnorm_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNAnorm_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/CNAnorm_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/CNAnorm_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNAnorm_1.10.1.tgz vignettes: vignettes/CNAnorm/inst/doc/CNAnorm.pdf vignetteTitles: CNAnorm.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: CNEr Version: 1.0.0 Depends: R (>= 3.0.2) Imports: Biostrings(>= 2.26.3), RSQLite(>= 0.11.4), GenomicRanges(>= 1.12.5), rtracklayer(>= 1.20.4), XVector(>= 0.2.0), DBI(>= 0.2-7), GenomicAlignments(>= 0.99.17), methods, IRanges(>= 1.19.38) LinkingTo: IRanges, XVector Suggests: Gviz(>= 1.7.4), RUnit, BiocGenerics License: GPL-2 | file LICENSE License_restricts_use: yes Archs: i386, x64 MD5sum: 2f8f22531665f1a9103e83b508c69465 NeedsCompilation: yes Title: CNE detection and visualization. Description: Large-scale identification and advanced visualization of sets of conserved noncoding elements. biocViews: GeneRegulation, Visualization, DataImport Author: Ge Tan Maintainer: Ge Tan URL: http://ancora.genereg.net/ source.ver: src/contrib/CNEr_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNEr_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNEr_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNEr_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNEr_1.0.0.tgz vignettes: vignettes/CNEr/inst/doc/CNEr.pdf vignetteTitles: CNEr hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/CNEr/inst/doc/CNEr.R importsMe: TFBSTools Package: cn.farms Version: 1.12.0 Depends: R (>= 2.11), Biobase, methods, ff, oligoClasses, snow Imports: BiocGenerics, DBI, affxparser, oligo, DNAcopy, preprocessCore, lattice Suggests: pd.mapping250k.sty, pd.mapping250k.nsp, pd.genomewidesnp.5, pd.genomewidesnp.6 License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: ba5a0145956d63cb4d2f3377116e666d NeedsCompilation: yes Title: cn.farms - factor analysis for copy number estimation Description: This package implements the cn.FARMS algorithm for copy number variation (CNV) analysis. cn.FARMS allows to analyze the most common Affymetrix (250K-SNP6.0) array types, supports high-performance computing using snow and ff. biocViews: Microarray, CopyNumberVariation Author: Andreas Mitterecker, Djork-Arne Clevert Maintainer: Andreas Mitterecker URL: http://www.bioinf.jku.at/software/cnfarms/cnfarms.html source.ver: src/contrib/cn.farms_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cn.farms_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cn.farms_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cn.farms_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cn.farms_1.12.0.tgz vignettes: vignettes/cn.farms/inst/doc/cn.farms.pdf vignetteTitles: cn.farms: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cn.farms/inst/doc/cn.farms.R Package: cn.mops Version: 1.10.1 Depends: R (>= 2.12), BiocGenerics, Biobase, IRanges, GenomicRanges Imports: methods, graphics, BiocGenerics, IRanges, Rsamtools, Suggests: snow, DNAcopy License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: b1118ba1e0baa6e1c554e23ee95fd6d1 NeedsCompilation: yes Title: cn.mops - Mixture of Poissons for CNV detection in NGS data Description: cn.mops (Copy Number estimation by a Mixture Of PoissonS) is a data processing pipeline for copy number variations and aberrations (CNVs and CNAs) from next generation sequencing (NGS) data. The package supplies functions to convert BAM files into read count matrices or genomic ranges objects, which are the input objects for cn.mops. cn.mops models the depths of coverage across samples at each genomic position. Therefore, it does not suffer from read count biases along chromosomes. Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++. biocViews: Sequencing, CopyNumberVariation, Homo_sapiens, CellBiology, HapMap, Genetics Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/cnmops/cnmops.html source.ver: src/contrib/cn.mops_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/cn.mops_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/cn.mops_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/cn.mops_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cn.mops_1.10.1.tgz vignettes: vignettes/cn.mops/inst/doc/cn.mops.pdf vignetteTitles: cn.mops: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cn.mops/inst/doc/cn.mops.R Package: CNORdt Version: 1.6.0 Depends: R (>= 1.8.0), CellNOptR (>= 0.99), abind License: GPL-2 Archs: i386, x64 MD5sum: 7bbf10d5f254a2ba9eb24d9cae9ba8fe NeedsCompilation: yes Title: Add-on to CellNOptR: Discretized time treatments Description: This add-on to the package CellNOptR handles time-course data, as opposed to steady state data in CellNOptR. It scales the simulation step to allow comparison and model fitting for time-course data. Future versions will optimize delays and strengths for each edge. biocViews: CellBasedAssays, CellBiology, Proteomics, TimeCourse Author: A. MacNamara Maintainer: A. MacNamara source.ver: src/contrib/CNORdt_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNORdt_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNORdt_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNORdt_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNORdt_1.6.0.tgz vignettes: vignettes/CNORdt/inst/doc/CNORdt-vignette.pdf vignetteTitles: Using multiple time points to train logic models to data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORdt/inst/doc/CNORdt-vignette.R Package: CNORfeeder Version: 1.4.0 Depends: R (>= 2.15.0), CellNOptR (>= 1.4.0), graph Suggests: minet, catnet, igraph, Rgraphviz, RUnit, BiocGenerics License: GPL-3 MD5sum: 9a1fa2281aaf524e1e6068438e883fcc NeedsCompilation: no Title: Integration of CellNOptR to add missing links Description: This package integrates literature-constrained and data-driven methods to infer signalling networks from perturbation experiments. It permits to extends a given network with links derived from the data via various inference methods, and uses information on physical interactions of proteins to guide and validate the integration of links. biocViews: CellBasedAssays, CellBiology, Proteomics, NetworkInference Author: F.Eduati Maintainer: F.Eduati source.ver: src/contrib/CNORfeeder_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNORfeeder_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNORfeeder_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNORfeeder_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNORfeeder_1.4.0.tgz vignettes: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.pdf vignetteTitles: Main vignette:Playing with networks using CNORfeeder hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.R Package: CNORfuzzy Version: 1.6.0 Depends: R (>= 2.15.0), CellNOptR (>= 1.4.0), nloptr (>= 0.8.5) Suggests: xtable, Rgraphviz, RUnit, BiocGenerics License: GPL-2 Archs: i386, x64 MD5sum: 5e77c1522b3a1655508b9fa3c38a387e NeedsCompilation: yes Title: Addon to CellNOptR: Fuzzy Logic Description: This package is an extension to CellNOptR. It contains additional functionality needed to simulate and train a prior knowledge network to experimental data using constrained fuzzy logic (cFL, rather than Boolean logic as is the case in CellNOptR). Additionally, this package will contain functions to use for the compilation of multiple optimization results (either Boolean or cFL). biocViews: Network Author: M. Morris, T. Cokelaer Maintainer: T. Cokelaer source.ver: src/contrib/CNORfuzzy_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNORfuzzy_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNORfuzzy_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNORfuzzy_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNORfuzzy_1.6.0.tgz vignettes: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.pdf vignetteTitles: Main vignette:Playing with networks using CNORfuzzyl hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.R Package: CNORode Version: 1.6.0 Depends: CellNOptR (>= 1.5.14), genalg Enhances: MEIGOR License: GPL-2 Archs: i386, x64 MD5sum: ea36f32462502127ce5ac4e49cf694fa NeedsCompilation: yes Title: ODE add-on to CellNOptR Description: ODE add-on to CellNOptR biocViews: CellBasedAssays, CellBiology, Proteomics, Bioinformatics, TimeCourse Author: David Henriques, Thomas Cokelaer Maintainer: David Henriques source.ver: src/contrib/CNORode_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNORode_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNORode_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNORode_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNORode_1.6.0.tgz vignettes: vignettes/CNORode/inst/doc/CNORode-vignette.pdf vignetteTitles: Main vignette:Playing with networks using CNORode hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORode/inst/doc/CNORode-vignette.R Package: CNTools Version: 1.20.0 Depends: R (>= 2.10), methods, tools, stats, genefilter License: LGPL Archs: i386, x64 MD5sum: de1f6e1fb7122ad47c19bda5b6b2913c NeedsCompilation: yes Title: Convert segment data into a region by sample matrix to allow for other high level computational analyses. Description: This package provides tools to convert the output of segmentation analysis using DNAcopy to a matrix structure with overlapping segments as rows and samples as columns so that other computational analyses can be applied to segmented data biocViews: Microarray, CopyNumberVariation Author: Jianhua Zhang Maintainer: J. Zhang source.ver: src/contrib/CNTools_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNTools_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNTools_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNTools_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNTools_1.20.0.tgz vignettes: vignettes/CNTools/inst/doc/HowTo.pdf vignetteTitles: NCTools HowTo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNTools/inst/doc/HowTo.R dependsOnMe: cghMCR Package: cnvGSA Version: 1.8.0 Depends: methods, brglm Suggests: cnvGSAdata, org.Hs.eg.db License: LGPL MD5sum: 5d19d8affe06a36bfb831d6cab525154 NeedsCompilation: no Title: Gene Set Analysis of (Rare) Copy Number Variants Description: This package is intended to facilitate gene-set association with rare CNVs in case-control studies. biocViews: MultipleComparison Author: Daniele Merico ; packaged by Robert Ziman Maintainer: Robert Ziman source.ver: src/contrib/cnvGSA_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cnvGSA_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cnvGSA_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cnvGSA_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cnvGSA_1.8.0.tgz vignettes: vignettes/cnvGSA/inst/doc/cnvGSA-vignette.pdf vignetteTitles: cnvGSA - Gene-Set Analysis of Rare Copy Number Variants hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cnvGSA/inst/doc/cnvGSA-vignette.R Package: CNVrd2 Version: 1.2.0 Depends: R (>= 3.0.0), DNAcopy, methods, Rsamtools, VariantAnnotation, parallel, rjags, ggplot2, gridExtra Imports: IRanges Suggests: knitr License: GPL-2 MD5sum: 8db58ad7e656833b227f8cfe60dddd03 NeedsCompilation: no Title: CNVrd2: a read depth-based method to detect and genotype complex common copy number variants from next generation sequencing data. Description: CNVrd2 uses next-generation sequencing data to measure human gene copy number for multiple samples, indentify SNPs tagging copy number variants and detect copy number polymorphic genomic regions. biocViews: High Throughput Sequencing, CNV, SNP. Author: Hoang Tan Nguyen, Tony R Merriman and MA Black Maintainer: Hoang Tan Nguyen URL: https://github.com/hoangtn/CNVrd2 VignetteBuilder: knitr source.ver: src/contrib/CNVrd2_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNVrd2_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNVrd2_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNVrd2_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNVrd2_1.2.0.tgz vignettes: vignettes/CNVrd2/inst/doc/CNVrd2.pdf vignetteTitles: A Markdown Vignette with knitr hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNVrd2/inst/doc/CNVrd2.R Package: CNVtools Version: 1.58.0 Depends: R (>= 2.10), survival License: GPL-3 Archs: i386, x64 MD5sum: 7f06763fad239e7291379b6c1875c356 NeedsCompilation: yes Title: A package to test genetic association with CNV data Description: This package is meant to facilitate the testing of Copy Number Variant data for genetic association, typically in case-control studies. biocViews: GeneticVariability Author: Chris Barnes and Vincent Plagnol Maintainer: Chris Barnes source.ver: src/contrib/CNVtools_1.58.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CNVtools_1.58.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CNVtools_1.58.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CNVtools_1.58.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CNVtools_1.58.0.tgz vignettes: vignettes/CNVtools/inst/doc/CNVtools-vignette.pdf vignetteTitles: Copy Number Variation Tools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNVtools/inst/doc/CNVtools-vignette.R Package: cobindR Version: 1.2.0 Imports: yaml, seqinr, Biostrings, biomaRt, BSgenome, methods, gmp, mclust, rtfbs, gplots, IRanges Suggests: RUnit, BiocGenerics Enhances: rGADEM, seqLogo, genoPlotR, parallel, VennDiagram, RColorBrewer, vcd, MotifDb, snowfall License: Artistic-2.0 MD5sum: ec833ce7ffaef46859cf5f94741150fd NeedsCompilation: no Title: Finding Co-occuring motifs of transcription factor binding sites Description: Finding and analysing co-occuring motifs of transcription factor binding sites in groups of genes biocViews: ChIPSeq, CellBiology, MultipleComparison, SequenceMatching Author: Manuela Benary, Stefan Kroeger, Yuehien Lee, Robert Lehmann Maintainer: Manuela Benary source.ver: src/contrib/cobindR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cobindR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cobindR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cobindR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cobindR_1.2.0.tgz vignettes: vignettes/cobindR/inst/doc/cobindR.pdf vignetteTitles: Using cobindR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cobindR/inst/doc/cobindR.R Package: CoCiteStats Version: 1.36.0 Depends: R (>= 2.0), org.Hs.eg.db Imports: AnnotationDbi License: CPL MD5sum: a191811f328d438ebec08a09b8e095cf NeedsCompilation: no Title: Different test statistics based on co-citation. Description: A collection of software tools for dealing with co-citation data. biocViews: Software Author: B. Ding and R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/CoCiteStats_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CoCiteStats_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CoCiteStats_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CoCiteStats_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CoCiteStats_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: codelink Version: 1.32.0 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), methods, Biobase (>= 2.17.8), limma Imports: annotate Suggests: genefilter, parallel, knitr License: GPL-2 MD5sum: c792a2f178a192816ae6cad9aaea3dcb NeedsCompilation: no Title: Manipulation of Codelink microarray data. Description: This package facilitates reading, preprocessing and manipulating Codelink microarray data. The raw data must be exported as text file using the Codelink software. biocViews: Microarray, OneChannel, DataImport, Preprocessing Author: Diego Diez Maintainer: Diego Diez VignetteBuilder: knitr source.ver: src/contrib/codelink_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/codelink_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/codelink_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/codelink_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/codelink_1.32.0.tgz vignettes: vignettes/codelink/inst/doc/Codelink_Introduction.pdf, vignettes/codelink/inst/doc/Codelink_Legacy.pdf vignetteTitles: Codelink Intruction, Codelink Legacy hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/codelink/inst/doc/Codelink_Introduction.R, vignettes/codelink/inst/doc/Codelink_Legacy.R Package: CoGAPS Version: 1.14.0 Depends: R (>= 2.9.0), R.utils (>= 1.2.4), gplots (>= 2.8.0) Imports: graphics, grDevices, methods, stats, utils License: GPL (== 2) MD5sum: 8eb7975eef3d9aa12c7bfce1b611b040 NeedsCompilation: yes Title: Coordinated Gene Activity in Pattern Sets Description: Coordinated Gene Activity in Pattern Sets (CoGAPS) infers biological processes which are active in individual gene sets from corresponding microarray measurements. CoGAPS achieves this inference by combining a MCMC matrix decomposition algorithm (GAPS) with a novel statistic inferring activity on gene sets. biocViews: GeneExpression, Microarray Author: Elana J. Fertig Maintainer: Elana J. Fertig , Michael F. Ochs URL: http://sourceforge.net/p/cogapscpp/wiki/Home/ SystemRequirements: GAPS-JAGS (==1.0.2) source.ver: src/contrib/CoGAPS_1.14.0.tar.gz vignettes: vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.pdf vignetteTitles: GAPS/CoGAPS Users Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CoGAPS/inst/doc/CoGAPSUsersManual.R Package: coGPS Version: 1.8.0 Depends: R (>= 2.13.0) Imports: graphics, grDevices Suggests: limma License: GPL-2 MD5sum: fbd30267cd8019338e7de37fa975b0bf NeedsCompilation: no Title: cancer outlier Gene Profile Sets Description: Gene Set Enrichment Analysis of P-value based statistics for outlier gene detection in dataset merged from multiple studies biocViews: Microarray, DifferentialExpression Author: Yingying Wei, Michael Ochs Maintainer: Yingying Wei source.ver: src/contrib/coGPS_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/coGPS_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/coGPS_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/coGPS_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/coGPS_1.8.0.tgz vignettes: vignettes/coGPS/inst/doc/coGPS.pdf vignetteTitles: coGPS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/coGPS/inst/doc/coGPS.R Package: COHCAP Version: 1.0.2 Depends: WriteXLS, COHCAPanno License: GPL-3 MD5sum: 6e13d6ded48057624875aa27e0e402d6 NeedsCompilation: no Title: CpG Island Analysis Pipeline for Illumina Methylation Array and Targeted BS-Seq Data Description: This package provides a pipeline to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). It provides QC metrics, differential methylation for CpG Sites, differential methylation for CpG Islands, integration with gene expression data, and visualization of methylation values. biocViews: DNAMethylation, Microarray, MethylSeq, Epigenetics, DifferentialMethylation Author: Charles Warden Maintainer: Charles Warden source.ver: src/contrib/COHCAP_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/COHCAP_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/COHCAP_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/COHCAP_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/COHCAP_1.0.2.tgz vignettes: vignettes/COHCAP/inst/doc/COHCAP.pdf vignetteTitles: COHCAP Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/COHCAP/inst/doc/COHCAP.R Package: COMPASS Version: 1.2.1 Depends: R (>= 3.0.2) Imports: Rcpp, data.table, RColorBrewer, scales, grid, plyr, knitr, abind, clue, grDevices, utils LinkingTo: Rcpp (>= 0.11.0) Suggests: flowWorkspace (>= 3.9.66), shiny, testthat, devtools, Kmisc License: Artistic-2.0 Archs: i386, x64 MD5sum: e2034a01ded660d06034bb3866d67fec NeedsCompilation: yes Title: Combinatorial Polyfunctionality Analysis of Single Cells Description: COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination. biocViews: FlowCytometry Author: Lynn Lin [aut], Kevin Ushey [aut, cre], Greg Finak [aut], Raivo Kolde [ctb] (Author of 'pheatmap', which was modified and now used internally in COMPASS) Maintainer: Kevin Ushey VignetteBuilder: knitr source.ver: src/contrib/COMPASS_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/COMPASS_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/COMPASS_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/COMPASS_1.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/COMPASS_1.2.1.tgz vignettes: vignettes/COMPASS/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/COMPASS/inst/doc/COMPASS.R htmlDocs: vignettes/COMPASS/inst/doc/COMPASS.html htmlTitles: "COMPASS" Package: compcodeR Version: 1.0.0 Depends: R (>= 3.0.2), sm Imports: tcltk, knitr (>= 1.2), markdown, ROCR, lattice (>= 0.16), gplots, gtools, gdata, caTools, grid, KernSmooth, MASS, ggplot2, stringr, modeest, edgeR, limma, vioplot, methods Suggests: BiocStyle, EBSeq, DESeq, DESeq2 (>= 1.1.31), baySeq (>= 1.16.0), genefilter, NOISeq, DSS, TCC, samr, NBPSeq, HTSDiff Enhances: rpanel License: GPL (>= 2) MD5sum: b8d96859c1959e64a5a10cb75e9b5113 NeedsCompilation: no Title: RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods Description: This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data and interfaces to several packages for performing the differential expression analysis. biocViews: RNASeq, DifferentialExpression Author: Charlotte Soneson Maintainer: Charlotte Soneson VignetteBuilder: knitr source.ver: src/contrib/compcodeR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/compcodeR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/compcodeR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/compcodeR_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/compcodeR_1.0.0.tgz vignettes: vignettes/compcodeR/inst/doc/compcodeR.pdf vignetteTitles: compcodeR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/compcodeR/inst/doc/compcodeR.R Package: CompGO Version: 1.0.0 Depends: RDAVIDWebService Imports: rtracklayer, Rgraphviz, ggplot2, GenomicFeatures, TxDb.Mmusculus.UCSC.mm9.knownGene License: GPL-2 MD5sum: 5eafaa817064c47cf84891f3d5cb854f NeedsCompilation: no Title: An R pipeline for .bed file annotation, comparing GO term enrichment between gene sets and data visualisation Description: This package contains functions to accomplish several tasks. It is able to download full genome databases from UCSC, import .bed files easily, annotate these .bed file regions with genes (plus distance) from aforementioned database dumps, interface with DAVID to create functional annotation and gene ontology enrichment charts based on gene lists (such as those generated from input .bed files) and finally visualise and compare these enrichments using either directed acyclic graphs or scatterplots. biocViews: GeneSetEnrichment, MultipleComparison, GO, Visualization Author: Sam Bassett [aut], Ash Waardenberg [aut, cre] Maintainer: Ash Waardenberg source.ver: src/contrib/CompGO_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CompGO_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CompGO_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CompGO_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CompGO_1.0.0.tgz vignettes: vignettes/CompGO/inst/doc/CompGO.pdf vignetteTitles: Introduction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CompGO/inst/doc/CompGO.R Package: ConsensusClusterPlus Version: 1.18.0 Imports: Biobase, ALL, graphics, stats, utils, cluster License: GPL version 2 MD5sum: 4e59fa6dda93790133186b9e1e59acf8 NeedsCompilation: no Title: ConsensusClusterPlus Description: algorithm for determining cluster count and membership by stability evidence in unsupervised analysis biocViews: Software, Clustering Author: Matt Wilkerson , Peter Waltman Maintainer: Matt Wilkerson source.ver: src/contrib/ConsensusClusterPlus_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ConsensusClusterPlus_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ConsensusClusterPlus_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ConsensusClusterPlus_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ConsensusClusterPlus_1.18.0.tgz vignettes: vignettes/ConsensusClusterPlus/inst/doc/ConsensusClusterPlus.pdf vignetteTitles: ConsensusClusterPlus Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: convert Version: 1.40.0 Depends: R (>= 2.6.0), Biobase (>= 1.15.33), limma (>= 1.7.0), marray, utils, methods License: LGPL MD5sum: 36010f945f3369c8b3f8ed37ca4a415a NeedsCompilation: no Title: Convert Microarray Data Objects Description: Define coerce methods for microarray data objects. biocViews: Infrastructure, Microarray, TwoChannel Author: Gordon Smyth , James Wettenhall , Yee Hwa (Jean Yang) , Martin Morgan Martin Morgan Maintainer: Yee Hwa (Jean) Yang URL: http://bioinf.wehi.edu.au/limma/convert.html source.ver: src/contrib/convert_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/convert_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/convert_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/convert_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/convert_1.40.0.tgz vignettes: vignettes/convert/inst/doc/convert.pdf vignetteTitles: Converting Between Microarray Data Classes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/convert/inst/doc/convert.R dependsOnMe: maigesPack, TurboNorm suggestsMe: BiocCaseStudies, dyebias, OLIN Package: copa Version: 1.32.0 Depends: Biobase, methods Suggests: colonCA License: Artistic-2.0 Archs: i386, x64 MD5sum: 094f7790a15d4f7e490fea4a2cafa0de NeedsCompilation: yes Title: Functions to perform cancer outlier profile analysis. Description: COPA is a method to find genes that undergo recurrent fusion in a given cancer type by finding pairs of genes that have mutually exclusive outlier profiles. biocViews: OneChannel, TwoChannel, DifferentialExpression, Visualization Author: James W. MacDonald Maintainer: James W. MacDonald source.ver: src/contrib/copa_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/copa_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/copa_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/copa_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/copa_1.32.0.tgz vignettes: vignettes/copa/inst/doc/copa.pdf vignetteTitles: copa Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/copa/inst/doc/copa.R Package: COPDSexualDimorphism Version: 1.0.0 Depends: COPDSexualDimorphism.data, NCBI2R, RColorBrewer, beeswarm, limma, GenomicRanges, gplots, gtools License: LGPL-2.1 MD5sum: 138bddaaf2b419f2f1109b83ff609a57 NeedsCompilation: no Title: Sexual dimorphic and COPD differential analysis for gene expression and methylation. Description: Sexual dimoprhic and COPD differential (SDCD) analysis contrasts regression coefficients from two stratified analysis. Stratification can be done in two ways: by COPD status or by sex. For COPD-stratified analysis, SDCD analysis contrasts sexual dimorphism between cases and controls, while sex-stratified SDCD analsysis contrasts COPD differential expression pattern between males and females. The package is meant to be used in conjunction with the package limma. biocViews: Software, AssayDomain, Microarray, GeneExpression, DNAMethylation, DifferentialExpression Author: J Fah Sathirapongsasuti Maintainer: J Fah Sathirapongsasuti source.ver: src/contrib/COPDSexualDimorphism_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/COPDSexualDimorphism_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/COPDSexualDimorphism_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/COPDSexualDimorphism_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/COPDSexualDimorphism_1.0.0.tgz vignettes: vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_eQTL.pdf, vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_expression.pdf, vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_methp.pdf vignetteTitles: SDCD eQTL, SDCD Genes, SDCD Methylation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_eQTL.R, vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_expression.R, vignettes/COPDSexualDimorphism/inst/doc/lgrc_sdcd_methp.R Package: copynumber Version: 1.4.0 Depends: R (>= 2.10), BiocGenerics Imports: GenomicRanges, IRanges License: Artistic-2.0 MD5sum: bd1e5d41027d089486d40585960ee5ce NeedsCompilation: no Title: Segmentation of single- and multi-track copy number data by penalized least squares regression. Description: Penalized least squares regression is applied to fit piecewise constant curves to copy number data to locate genomic regions of constant copy number. Procedures are available for individual segmentation of each sample, joint segmentation of several samples and joint segmentation of the two data tracks from SNP-arrays. Several plotting functions are available for visualization of the data and the segmentation results. biocViews: aCGH, SNP, CopyNumberVariation, Genetics, Visualization Author: Gro Nilsen, Knut Liestoel and Ole Christian Lingjaerde. Maintainer: Gro Nilsen source.ver: src/contrib/copynumber_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/copynumber_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/copynumber_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/copynumber_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/copynumber_1.4.0.tgz vignettes: vignettes/copynumber/inst/doc/copynumber.pdf vignetteTitles: copynumber.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/copynumber/inst/doc/copynumber.R Package: CopyNumber450k Version: 1.0.0 Depends: Biobase, minfi, DNAcopy, preprocessCore, BiocGenerics Imports: methods Suggests: CopyNumber450kData, minfiData License: Artistic-2.0 MD5sum: de5385faa8b9c1d714414d32ffa29264 NeedsCompilation: no Title: R package for calling CNV from Illumina 450k methylation microarrays Description: This package contains a set of functions that allow CNV calling from Illumina 450k methylation microarrays. biocViews: DNAMethylation, Microarray, Preprocessing, QualityControl, CopyNumberVariation Author: Simon Papillon-Cavanagh, Jean-Philippe Fortin, Nicolas De Jay Maintainer: Simon Papillon-Cavanagh source.ver: src/contrib/CopyNumber450k_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CopyNumber450k_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CopyNumber450k_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CopyNumber450k_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CopyNumber450k_1.0.0.tgz vignettes: vignettes/CopyNumber450k/inst/doc/CopyNumber450k.pdf vignetteTitles: CopyNumber450k User's Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CopyNumber450k/inst/doc/CopyNumber450k.R Package: Cormotif Version: 1.10.0 Depends: R (>= 2.12.0), affy, limma Imports: affy, graphics, grDevices License: GPL-2 MD5sum: 6d1f677a5aab1fc7b96909c22c09b692 NeedsCompilation: no Title: Correlation Motif Fit Description: It fits correlation motif model to multiple studies to detect study specific differential expression patterns. biocViews: Microarray, DifferentialExpression Author: Hongkai Ji, Yingying Wei Maintainer: Yingying Wei source.ver: src/contrib/Cormotif_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Cormotif_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Cormotif_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Cormotif_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Cormotif_1.10.0.tgz vignettes: vignettes/Cormotif/inst/doc/CormotifVignette.pdf vignetteTitles: Cormotif Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Cormotif/inst/doc/CormotifVignette.R Package: CorMut Version: 1.6.0 Depends: seqinr,igraph License: GPL-2 MD5sum: 96d5b1ce0dec651430654cd1afbbec6d NeedsCompilation: no Title: Detect the correlated mutations based on selection pressure Description: CorMut provides functions for computing kaks for individual sites or specific amino acids and detecting correlated mutations among them. Three methods are provided for detecting correlated mutations ,including conditional selection pressure, mutual information and Jaccard index. The computation consists of two steps: First, the positive selection sites are detected; Second, the mutation correlations are computed among the positive selection sites. Note that the first step is optional. Meanwhile, CorMut facilitates the comparison of the correlated mutations between two conditions by the means of correlated mutation network. biocViews: Sequencing Author: Zhenpeng Li, Yang Huang, Yabo Ouyang, Yiming Shao, Liying Ma Maintainer: Zhenpeng Li source.ver: src/contrib/CorMut_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CorMut_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CorMut_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CorMut_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CorMut_1.6.0.tgz vignettes: vignettes/CorMut/inst/doc/CorMut.pdf vignetteTitles: CorMut hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CorMut/inst/doc/CorMut.R Package: coRNAi Version: 1.14.0 Depends: R (>= 2.10), cellHTS2, limma, locfit Imports: MASS, gplots, lattice, grDevices, graphics, stats License: Artistic-2.0 MD5sum: 1723569d9b141b0c548fd44e6fa8a31e NeedsCompilation: no Title: Analysis of co-knock-down RNAi data Description: Analysis of combinatorial cell-based RNAi screens biocViews: CellBasedAssays Author: Elin Axelsson Maintainer: Elin Axelsson SystemRequirements: Graphviz source.ver: src/contrib/coRNAi_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/coRNAi_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/coRNAi_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/coRNAi_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/coRNAi_1.14.0.tgz vignettes: vignettes/coRNAi/inst/doc/coRNAi.pdf vignetteTitles: coRNAi hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/coRNAi/inst/doc/coRNAi.R Package: CORREP Version: 1.30.0 Imports: e1071, stats Suggests: cluster, MASS License: GPL (>= 2) MD5sum: bc5cb6ad2518fffab3f517769d862f09 NeedsCompilation: no Title: Multivariate Correlation Estimator and Statistical Inference Procedures. Description: Multivariate correlation estimation and statistical inference. See package vignette. biocViews: Microarray, Clustering, GraphAndNetwork Author: Dongxiao Zhu and Youjuan Li Maintainer: Dongxiao Zhu source.ver: src/contrib/CORREP_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CORREP_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CORREP_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CORREP_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CORREP_1.30.0.tgz vignettes: vignettes/CORREP/inst/doc/CORREP.pdf vignetteTitles: Multivariate Correlation Estimator hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CORREP/inst/doc/CORREP.R Package: CoverageView Version: 1.0.0 Depends: R (>= 2.10), methods,Rsamtools,rtracklayer Imports: IRanges,GenomicRanges,GenomicAlignments,parallel,tools License: Artistic-2.0 MD5sum: a3208775662b10fe4537966b2e66a977 NeedsCompilation: no Title: Coverage visualization package for R Description: This package provides a framework for the visualization of genome coverage profiles. It can be used for ChIP-seq experiments, but it can be also used for genome-wide nucleosome positioning experiments or other experiment types where it is important to have a framework in order to inspect how the coverage distributed across the genome biocViews: Visualization,RNASeq,ChIPSeq,Sequencing,Technology,Software Author: Ernesto Lowy Maintainer: Ernesto Lowy source.ver: src/contrib/CoverageView_1.0.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/CoverageView_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CoverageView_1.0.0.tgz vignettes: vignettes/CoverageView/inst/doc/CoverageView.pdf vignetteTitles: Easy visualization of the read coverage hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CoverageView/inst/doc/CoverageView.R Package: cqn Version: 1.10.0 Depends: R (>= 2.10.0), mclust, nor1mix, stats, preprocessCore, splines, quantreg Imports: splines Suggests: scales, edgeR License: Artistic-2.0 MD5sum: 22e983fba5dc000877159f015c28df6d NeedsCompilation: no Title: Conditional quantile normalization Description: A normalization tool for RNA-Seq data, implementing the conditional quantile normalization method. biocViews: RNASeq, Preprocessing, DifferentialExpression Author: Jean (Zhijin) Wu, Kasper Daniel Hansen Maintainer: Kasper Daniel Hansen source.ver: src/contrib/cqn_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cqn_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cqn_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cqn_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cqn_1.10.0.tgz vignettes: vignettes/cqn/inst/doc/cqn.pdf vignetteTitles: CQN (Conditional Quantile Normalization) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cqn/inst/doc/cqn.R importsMe: tweeDEseq Package: CRImage Version: 1.12.0 Depends: EBImage, DNAcopy, aCGH Imports: MASS, e1071, foreach, sgeostat License: Artistic-2.0 MD5sum: 09afdb6d422812dd57f76bd0ce98d105 NeedsCompilation: no Title: CRImage a package to classify cells and calculate tumour cellularity Description: CRImage provides functionality to process and analyze images, in particular to classify cells in biological images. Furthermore, in the context of tumor images, it provides functionality to calculate tumour cellularity. biocViews: CellBiology, Classification Author: Henrik Failmezger , Yinyin Yuan , Oscar Rueda , Florian Markowetz Maintainer: Henrik Failmezger , Yinyin Yuan source.ver: src/contrib/CRImage_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CRImage_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CRImage_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CRImage_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CRImage_1.12.0.tgz vignettes: vignettes/CRImage/inst/doc/CRImage.pdf vignetteTitles: CRImage Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CRImage/inst/doc/CRImage.R Package: CRISPRseek Version: 1.0.3 Depends: R (>= 3.0.1), BiocGenerics, Biostrings, BSgenome Suggests: RUnit, BiocStyle, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene License: GPL (>= 2) MD5sum: 9c0bc98bcefdb427fbade986eccf5847 NeedsCompilation: no Title: Design of target-specific guide RNAs in CRISPR-Cas9, genome-editing systems Description: The package includes functions to find potential guide RNAs for input target sequences, optionally filter guide RNAs without restriction enzyme cut site, or without paired guide RNAs, genome-wide search for off-targets, score, rank, fetch flank sequence and indicate whether the target and off-targets are located in exon region or not. Potential guide RNAs are annotated with total score of the top5 and topN off-targets, detailed topN mismatch sites, restriction enzyme cut sites, and paired guide RNAs. This package leverages Biostrings and BSgenome packages. biocViews: GeneRegulation, SequenceMatching Author: Lihua Julie Zhu, Benjamin R. Holmes, Neil Aronin and Michael Brodsky Maintainer: Lihua Julie Zhu source.ver: src/contrib/CRISPRseek_1.0.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/CRISPRseek_1.0.3.zip win64.binary.ver: bin/windows64/contrib/3.1/CRISPRseek_1.0.3.zip mac.binary.ver: bin/macosx/contrib/3.1/CRISPRseek_1.0.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CRISPRseek_1.0.3.tgz vignettes: vignettes/CRISPRseek/inst/doc/CRISPRseek.pdf vignetteTitles: CRISPRseek Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CRISPRseek/inst/doc/CRISPRseek.R Package: crlmm Version: 1.22.0 Depends: R (>= 2.14.0), oligoClasses (>= 1.21.12), preprocessCore (>= 1.17.7) Imports: methods, Biobase (>= 2.15.4), BiocGenerics, affyio (>= 1.23.2), illuminaio, ellipse, mvtnorm, splines, stats, SNPchip, utils, lattice, ff, foreach, RcppEigen (>= 0.3.1.2.1), matrixStats, VGAM LinkingTo: preprocessCore (>= 1.17.7) Suggests: hapmapsnp6, genomewidesnp6Crlmm (>= 1.0.7), GGdata, snpStats, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: 5e89bfe918fdf1202cbd98c0df7bf42f NeedsCompilation: yes Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays. Description: Faster implementation of CRLMM specific to SNP 5.0 and 6.0 arrays, as well as a copy number tool specific to 5.0, 6.0, and Illumina platforms biocViews: Microarray, Preprocessing, SNP, CopyNumberVariation Author: Benilton S Carvalho, Robert Scharpf, Matt Ritchie, Ingo Ruczinski, Rafael A Irizarry Maintainer: Benilton S Carvalho , Robert Scharpf , Matt Ritchie source.ver: src/contrib/crlmm_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/crlmm_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/crlmm_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/crlmm_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/crlmm_1.22.0.tgz vignettes: vignettes/crlmm/inst/doc/AffyGW.pdf, vignettes/crlmm/inst/doc/CopyNumberOverview.pdf, vignettes/crlmm/inst/doc/genotyping.pdf, vignettes/crlmm/inst/doc/gtypeDownstream.pdf, vignettes/crlmm/inst/doc/IlluminaPreprocessCN.pdf, vignettes/crlmm/inst/doc/Infrastructure.pdf vignetteTitles: Copy number estimation, Overview of copy number vignettes, crlmm Vignette - Genotyping, crlmm Vignette - Downstream Analysis, Preprocessing and genotyping Illumina arrays for copy number analysis, Infrastructure for copy number analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/crlmm/inst/doc/AffyGW.R, vignettes/crlmm/inst/doc/CopyNumberOverview.R, vignettes/crlmm/inst/doc/genotyping.R, vignettes/crlmm/inst/doc/gtypeDownstream.R, vignettes/crlmm/inst/doc/IlluminaPreprocessCN.R, vignettes/crlmm/inst/doc/Infrastructure.R suggestsMe: ArrayTV, oligoClasses, SNPchip Package: CSAR Version: 1.16.0 Depends: R (>= 2.15.0), IRanges, GenomicRanges Imports: stats, utils Suggests: ShortRead, Biostrings License: Artistic-2.0 Archs: i386, x64 MD5sum: aa922abd8c192b07a7659db657d37518 NeedsCompilation: yes Title: Statistical tools for the analysis of ChIP-seq data Description: Statistical tools for ChIP-seq data analysis. The package includes the statistical method described in Kaufmann et al. (2009) PLoS Biology: 7(4):e1000090. Briefly, Taking the average DNA fragment size subjected to sequencing into account, the software calculates genomic single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutation. biocViews: ChIPSeq, Transcription, Genetics Author: Jose M Muino Maintainer: Jose M Muino source.ver: src/contrib/CSAR_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CSAR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CSAR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CSAR_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CSAR_1.16.0.tgz vignettes: vignettes/CSAR/inst/doc/CSAR.pdf vignetteTitles: CSAR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CSAR/inst/doc/CSAR.R importsMe: NarrowPeaks suggestsMe: NarrowPeaks Package: CSSP Version: 1.2.0 Imports: methods, splines, stats, utils Suggests: testthat License: GPL-2 Archs: i386, x64 MD5sum: 0bf70eade132209a9c4deefb894e1614 NeedsCompilation: yes Title: ChIP-Seq Statistical Power Description: Power computation for ChIP-Seq data based on Bayesian estimation for local poisson counting process. biocViews: ChIPseqData, Sequencing, QualityControl Author: Chandler Zuo, Sunduz Keles Maintainer: Chandler Zuo source.ver: src/contrib/CSSP_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/CSSP_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/CSSP_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/CSSP_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/CSSP_1.2.0.tgz vignettes: vignettes/CSSP/inst/doc/cssp.pdf vignetteTitles: cssp.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CSSP/inst/doc/cssp.R Package: ctc Version: 1.38.0 Depends: amap License: GPL-2 MD5sum: 62ed7094dcd1f192af0efe7cad346846 NeedsCompilation: no Title: Cluster and Tree Conversion. Description: Tools for export and import classification trees and clusters to other programs biocViews: Microarray, Clustering, Classification, DataImport, Visualization Author: Antoine Lucas , Laurent Gautier Maintainer: Antoine Lucas URL: http://antoinelucas.free.fr/ctc source.ver: src/contrib/ctc_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ctc_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ctc_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ctc_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ctc_1.38.0.tgz vignettes: vignettes/ctc/inst/doc/ctc.pdf vignetteTitles: Introduction to ctc hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ctc/inst/doc/ctc.R Package: cummeRbund Version: 2.6.1 Depends: R (>= 2.7.0), BiocGenerics (>= 0.3.2), RSQLite, ggplot2, reshape2, fastcluster, rtracklayer, Gviz Imports: methods, plyr, BiocGenerics Suggests: cluster, plyr License: Artistic-2.0 MD5sum: f77ff3ff88e8859c7567f29c4e8d0245 NeedsCompilation: no Title: Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data. Description: Allows for persistent storage, access, exploration, and manipulation of Cufflinks high-throughput sequencing data. In addition, provides numerous plotting functions for commonly used visualizations. biocViews: Sequencing, RNASeq, RNAseqData, GeneExpression, DifferentialExpression, Infrastructure, DataImport, DataRepresentation, Visualization, Clustering, MultipleComparison, QualityControl Author: L. Goff, C. Trapnell, D. Kelley Maintainer: Loyal A. Goff source.ver: src/contrib/cummeRbund_2.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/cummeRbund_2.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/cummeRbund_2.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/cummeRbund_2.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cummeRbund_2.6.1.tgz vignettes: vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.pdf, vignettes/cummeRbund/inst/doc/cummeRbund-manual.pdf vignetteTitles: Sample cummeRbund workflow, CummeRbund User Guide hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.R, vignettes/cummeRbund/inst/doc/cummeRbund-manual.R dependsOnMe: meshr, spliceR suggestsMe: oneChannelGUI Package: customProDB Version: 1.4.1 Depends: R (>= 3.0.1), IRanges, AnnotationDbi, biomaRt Imports: IRanges, GenomicRanges, Rsamtools (>= 1.10.2), GenomicAlignments, Biostrings (>= 2.26.3), GenomicFeatures (>= 1.13.15), biomaRt (>= 2.17.1), stringr, RCurl, plyr, VariantAnnotation (>= 1.7.28), rtracklayer, RSQLite, AnnotationDbi Suggests: BSgenome.Hsapiens.UCSC.hg19 License: Artistic-2.0 MD5sum: 2f29dac027b748d463166cf499ec31cd NeedsCompilation: no Title: Generate customized protein database from NGS data, with a focus on RNA-Seq data, for proteomics search. Description: Generate customized protein sequence database from RNA-Seq data for proteomics search biocViews: Proteomics Author: xiaojing wang Maintainer: xiaojing wang source.ver: src/contrib/customProDB_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/customProDB_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/customProDB_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/customProDB_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/customProDB_1.4.1.tgz vignettes: vignettes/customProDB/inst/doc/customProDB.pdf vignetteTitles: Introduction to customProDB hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/customProDB/inst/doc/customProDB.R Package: cycle Version: 1.18.0 Depends: R (>= 2.10.0), Mfuzz Imports: Biobase, stats License: GPL-2 MD5sum: 6253dcb0a4634fe68682f424581c8014 NeedsCompilation: no Title: Significance of periodic expression pattern in time-series data Description: Package for assessing the statistical significance of periodic expression based on Fourier analysis and comparison with data generated by different background models biocViews: Microarray, TimeCourse Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/cycle/index.html source.ver: src/contrib/cycle_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/cycle_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/cycle_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/cycle_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/cycle_1.18.0.tgz vignettes: vignettes/cycle/inst/doc/cycle.pdf vignetteTitles: Introduction to cycle hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cycle/inst/doc/cycle.R Package: dagLogo Version: 1.2.1 Depends: R (>= 3.0.1), methods, biomaRt, grImport, grid, motifStack Imports: pheatmap, Biostrings Suggests: XML, UniProt.ws, RUnit, BiocGenerics, BiocStyle License: GPL (>=2) MD5sum: 3fe6d10a6fd2e1601bf6b9b296e1d9c9 NeedsCompilation: no Title: dagLogo Description: Visualize significant conserved amino acid sequence pattern in groups based on probability theory biocViews: SequenceMatching, GenomicsSequence, Visualization Author: Jianhong Ou, Niraj Nirala, Usha Acharya, Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/dagLogo_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/dagLogo_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/dagLogo_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/dagLogo_1.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/dagLogo_1.2.1.tgz vignettes: vignettes/dagLogo/inst/doc/dagLogo.pdf vignetteTitles: dagLogo Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dagLogo/inst/doc/dagLogo.R Package: daMA Version: 1.36.0 Imports: MASS, stats License: GPL (>= 2) MD5sum: 0e51eb88718f46f34a9ceca2e9030e8a NeedsCompilation: no Title: Efficient design and analysis of factorial two-colour microarray data Description: This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data. Statistical details are described in Bretz et al. (2003, submitted) biocViews: Microarray, TwoChannel, DifferentialExpression Author: Jobst Landgrebe and Frank Bretz Maintainer: Jobst Landgrebe URL: http://www.microarrays.med.uni-goettingen.de source.ver: src/contrib/daMA_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/daMA_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/daMA_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/daMA_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/daMA_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: DART Version: 1.10.0 Depends: R (>= 2.10.0), igraph (>= 0.6.0) Suggests: breastCancerVDX, breastCancerMAINZ, Biobase License: GPL-2 MD5sum: 5e0014a26a94fbe356d1906353a4350d NeedsCompilation: no Title: Denoising Algorithm based on Relevance network Topology Description: Denoising Algorithm based on Relevance network Topology (DART) is an algorithm designed to evaluate the consistency of prior information molecular signatures (e.g in-vitro perturbation expression signatures) in independent molecular data (e.g gene expression data sets). If consistent, a pruning network strategy is then used to infer the activation status of the molecular signature in individual samples. biocViews: GeneExpression, DifferentialExpression, GraphAndNetwork, Pathways Author: Yan Jiao, Katherine Lawler, Andrew E Teschendorff Maintainer: Katherine Lawler source.ver: src/contrib/DART_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DART_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DART_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DART_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DART_1.10.0.tgz vignettes: vignettes/DART/inst/doc/DART.pdf vignetteTitles: DART Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DART/inst/doc/DART.R Package: DASiR Version: 1.4.0 Depends: IRanges, GenomicRanges, XML, Biostrings License: LGPL (>= 3) MD5sum: ddf13b17e58bf5727c6476f6aa6aad35 NeedsCompilation: no Title: Distributed Annotation System in R Description: R package for programmatic retrieval of information from DAS servers biocViews: Annotation Author: Oscar Flores, Anna Mantsoki Maintainer: Oscar Flores , Anna Mantsoki source.ver: src/contrib/DASiR_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DASiR_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DASiR_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DASiR_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DASiR_1.4.0.tgz vignettes: vignettes/DASiR/inst/doc/DASiR.pdf vignetteTitles: Programmatic retrieval of information from DAS servers hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DASiR/inst/doc/DASiR.R Package: DAVIDQuery Version: 1.24.0 Depends: RCurl (>= 1.4.0), utils License: GPL-2 MD5sum: cbfdcfcd28af1d2c2277ef2e6db00451 NeedsCompilation: no Title: Retrieval from the DAVID bioinformatics data resource into R Description: Tools to retrieve data from DAVID, the Database for Annotation, Visualization and Integrated Discovery biocViews: Annotation Author: Roger Day, Alex Lisovich Maintainer: Roger Day source.ver: src/contrib/DAVIDQuery_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DAVIDQuery_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DAVIDQuery_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DAVIDQuery_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DAVIDQuery_1.24.0.tgz vignettes: vignettes/DAVIDQuery/inst/doc/DAVIDQuery.pdf vignetteTitles: An R Package for retrieving data from DAVID into R objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DAVIDQuery/inst/doc/DAVIDQuery.R importsMe: IdMappingRetrieval Package: DBChIP Version: 1.8.0 Depends: R (>= 2.15.0), edgeR, DESeq Suggests: ShortRead, BiocGenerics License: GPL (>= 2) MD5sum: cdd76a15a53abd6f83236fda520e3a19 NeedsCompilation: no Title: Differential Binding of Transcription Factor with ChIP-seq Description: DBChIP detects differentially bound sharp binding sites across multiple conditions, with or without matching control samples. biocViews: ChIPSeq, Sequencing, Transcription, Genetics Author: Kun Liang Maintainer: Kun Liang source.ver: src/contrib/DBChIP_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DBChIP_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DBChIP_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DBChIP_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DBChIP_1.8.0.tgz vignettes: vignettes/DBChIP/inst/doc/DBChIP.pdf vignetteTitles: DBChIP hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DBChIP/inst/doc/DBChIP.R Package: ddCt Version: 1.18.0 Depends: R (>= 2.3.0), Biobase (>= 1.10.0), RColorBrewer (>= 0.1-3), xtable, lattice, methods Suggests: RUnit License: LGPL-3 MD5sum: 7b847508a76969e56a4d30deac8362e9 NeedsCompilation: no Title: The ddCt Algorithm for the Analysis of Quantitative Real-Time PCR (qRT-PCR) Description: The Delta-Delta-Ct (ddCt) Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions. biocViews: GeneExpression, DifferentialExpression, MicrotitrePlateAssay, qPCR Author: Jitao David Zhang, Rudolf Biczok and Markus Ruschhaupt Maintainer: Jitao David Zhang source.ver: src/contrib/ddCt_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ddCt_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ddCt_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ddCt_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ddCt_1.18.0.tgz vignettes: vignettes/ddCt/inst/doc/rtPCR.pdf, vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.pdf, vignettes/ddCt/inst/doc/rtPCR-usage.pdf vignetteTitles: Introduction to the ddCt method for qRT-PCR data analysis: background,, algorithm and example, How to apply the ddCt method, Analyse RT-PCR data with the end-to-end script in ddCt package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddCt/inst/doc/rtPCR.R, vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.R, vignettes/ddCt/inst/doc/rtPCR-usage.R Package: ddgraph Version: 1.8.0 Depends: graph, methods, Rcpp Imports: bnlearn (>= 2.8), gtools, pcalg, RColorBrewer, plotrix, MASS LinkingTo: Rcpp Suggests: Rgraphviz, e1071, ROCR, testthat License: GPL-3 Archs: i386, x64 MD5sum: 2e83ce65d13b26671116a2fba8b9bef5 NeedsCompilation: yes Title: Distinguish direct and indirect interactions with Graphical Modelling Description: Distinguish direct from indirect interactions in gene regulation and infer combinatorial code from highly correlated variables such as transcription factor binding profiles. The package implements the Neighbourhood Consistent PC algorithm (NCPC) and draws Direct Dependence Graphs to represent dependence structure around a target variable. The package also provides a unified interface to other Graphical Modelling (Bayesian Network) packages for distinguishing direct and indirect interactions. biocViews: GraphAndNetwork Author: Robert Stojnic Maintainer: Robert Stojnic source.ver: src/contrib/ddgraph_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ddgraph_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ddgraph_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ddgraph_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ddgraph_1.8.0.tgz vignettes: vignettes/ddgraph/inst/doc/ddgraph.pdf vignetteTitles: Overview of the 'ddgraph' package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddgraph/inst/doc/ddgraph.R Package: DECIPHER Version: 1.10.1 Depends: R (>= 2.13.0), Biostrings (>= 2.31.9), RSQLite (>= 0.9), stats, parallel Imports: methods, IRanges, XVector LinkingTo: Biostrings, RSQLite, IRanges, XVector License: GPL-3 Archs: i386, x64 MD5sum: 00234637ffb9b006030a819093ffda6d NeedsCompilation: yes Title: Database Enabled Code for Ideal Probe Hybridization Employing R Description: A toolset that assist in the design of hybridization probes. biocViews: Clustering, Genetics, Sequencing, Infrastructure, DataImport, Visualization, Microarray, QualityControl Author: Erik Wright Maintainer: Erik Wright source.ver: src/contrib/DECIPHER_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/DECIPHER_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/DECIPHER_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/DECIPHER_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DECIPHER_1.10.1.tgz vignettes: vignettes/DECIPHER/inst/doc/ArtOfAlignmentInR.pdf, vignettes/DECIPHER/inst/doc/DECIPHERing.pdf, vignettes/DECIPHER/inst/doc/DesignMicroarray.pdf, vignettes/DECIPHER/inst/doc/DesignPrimers.pdf, vignettes/DECIPHER/inst/doc/DesignProbes.pdf, vignettes/DECIPHER/inst/doc/FindChimeras.pdf vignetteTitles: The Art of Multiple Sequence Alignment in R, Getting Started DECIPHERing, Design Microarray Probes, Design Group-Specific Primers, Design Group-Specific FISH Probes, Finding Chimeric Sequences hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DECIPHER/inst/doc/ArtOfAlignmentInR.R, vignettes/DECIPHER/inst/doc/DECIPHERing.R, vignettes/DECIPHER/inst/doc/DesignMicroarray.R, vignettes/DECIPHER/inst/doc/DesignPrimers.R, vignettes/DECIPHER/inst/doc/DesignProbes.R, vignettes/DECIPHER/inst/doc/FindChimeras.R Package: DeconRNASeq Version: 1.6.0 Depends: R (>= 2.14.0), limSolve, pcaMethods, ggplot2, grid License: GPL-2 MD5sum: 1553803ce31916da9b3008f7af82a5dd NeedsCompilation: no Title: Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data Description: DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles. biocViews: ExperimentData, DifferentialExpression Author: Ting Gong Joseph D. Szustakowski Maintainer: Ting Gong source.ver: src/contrib/DeconRNASeq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DeconRNASeq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DeconRNASeq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DeconRNASeq_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DeconRNASeq_1.6.0.tgz vignettes: vignettes/DeconRNASeq/inst/doc/DeconRNASeq.pdf vignetteTitles: DeconRNASeq Demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DeconRNASeq/inst/doc/DeconRNASeq.R Package: DEDS Version: 1.38.0 Depends: R (>= 1.7.0) License: LGPL Archs: i386, x64 MD5sum: 749546bd1e79ce8f9e422f543460a2cc NeedsCompilation: yes Title: Differential Expression via Distance Summary for Microarray Data Description: This library contains functions that calculate various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B statistics. It also implements a new methodology called DEDS (Differential Expression via Distance Summary), which selects differentially expressed genes by integrating and summarizing a set of statistics using a weighted distance approach. biocViews: Microarray, DifferentialExpression Author: Yuanyuan Xiao , Jean Yee Hwa Yang . Maintainer: Yuanyuan Xiao source.ver: src/contrib/DEDS_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DEDS_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DEDS_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DEDS_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DEDS_1.38.0.tgz vignettes: vignettes/DEDS/inst/doc/DEDS.pdf vignetteTitles: DEDS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEDS/inst/doc/DEDS.R Package: deepSNV Version: 1.10.0 Depends: R (>= 2.13.0), Rsamtools (>= 1.4.3), GenomicRanges, IRanges, Biostrings, VGAM, methods, graphics, VariantAnnotation (>= 1.5.0), parallel Imports: Rsamtools LinkingTo: Rsamtools Suggests: RColorBrewer, knitr License: GPL-3 Archs: i386, x64 MD5sum: 40c914044eca85d772860aa0f66a2978 NeedsCompilation: yes Title: Detection of subclonal SNVs in deep sequencing experiments. Description: This package provides provides a quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The new shearwater algorithm (beta) computes a Bayes classifier based on a beta- binomial model for variant calling with multiple samples for precisely estimating model parameters such as local error rates and dispersion and prior knowledge, e.g. from variation data bases such as COSMIC. biocViews: GeneticVariability, SNP, Sequencing, Genetics, DataImport Author: Moritz Gerstung and Niko Beerenwinkel Maintainer: Moritz Gerstung URL: http://www.cbg.ethz.ch/software/deepSNV VignetteBuilder: knitr source.ver: src/contrib/deepSNV_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/deepSNV_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/deepSNV_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/deepSNV_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/deepSNV_1.10.0.tgz vignettes: vignettes/deepSNV/inst/doc/deepSNV.pdf, vignettes/deepSNV/inst/doc/shearwater.pdf vignetteTitles: An R package for detecting low frequency variants in deep sequencing experiments, Subclonal variant calling with multiple samples and prior knowledge using shearwater hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/deepSNV/inst/doc/deepSNV.R, vignettes/deepSNV/inst/doc/shearwater.R suggestsMe: GenomicFiles Package: DEGraph Version: 1.16.0 Depends: R (>= 2.10.0), R.utils Imports: graph, KEGGgraph, lattice, mvtnorm, R.methodsS3, RBGL, Rgraphviz, rrcov, NCIgraph Suggests: corpcor, fields, graph, KEGGgraph, lattice, marray, RBGL, rrcov, Rgraphviz, NCIgraph License: GPL-3 MD5sum: 522c10632986de9b8e71ffab8ade440d NeedsCompilation: no Title: Two-sample tests on a graph Description: DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results. biocViews: Microarray, DifferentialExpression, GraphAndNetwork, Network, NetworkEnrichment Author: Laurent Jacob, Pierre Neuvial and Sandrine Dudoit Maintainer: Laurent Jacob source.ver: src/contrib/DEGraph_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DEGraph_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DEGraph_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DEGraph_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DEGraph_1.16.0.tgz vignettes: vignettes/DEGraph/inst/doc/DEGraph.pdf vignetteTitles: DEGraph: differential expression testing for gene networks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEGraph/inst/doc/DEGraph.R suggestsMe: graphite Package: DEGseq Version: 1.18.0 Depends: R (>= 2.8.0), qvalue, samr, methods Imports: graphics, grDevices, methods, stats, utils License: LGPL (>=2) Archs: i386, x64 MD5sum: b6c255d61076ecfd6bb8525ca4c3967b NeedsCompilation: yes Title: Identify Differentially Expressed Genes from RNA-seq data Description: DEGseq is an R package to identify differentially expressed genes from RNA-Seq data. biocViews: RNASeq, Preprocessing, GeneExpression, DifferentialExpression Author: Likun Wang and Xi Wang . Maintainer: Likun Wang source.ver: src/contrib/DEGseq_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DEGseq_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DEGseq_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DEGseq_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DEGseq_1.18.0.tgz vignettes: vignettes/DEGseq/inst/doc/DEGseq.pdf vignetteTitles: DEGseq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEGseq/inst/doc/DEGseq.R Package: deltaGseg Version: 1.4.0 Depends: R (>= 2.15.1), methods, ggplot2, changepoint, wavethresh, tseries, pvclust, fBasics, grid, reshape, scales Suggests: knitr License: GPL-2 MD5sum: d20509303fb6c4c0d2462a725a8111ea NeedsCompilation: no Title: deltaGseg Description: Identifying distinct subpopulations through multiscale time series analysis biocViews: Proteomics, TimeCourse, Visualization, Clustering Author: Diana Low, Efthymios Motakis Maintainer: Diana Low VignetteBuilder: knitr source.ver: src/contrib/deltaGseg_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/deltaGseg_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/deltaGseg_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/deltaGseg_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/deltaGseg_1.4.0.tgz vignettes: vignettes/deltaGseg/inst/doc/deltaGseg.pdf vignetteTitles: deltaGseg hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/deltaGseg/inst/doc/deltaGseg.R Package: DESeq Version: 1.16.0 Depends: BiocGenerics (>= 0.7.5), Biobase (>= 2.21.7), locfit, lattice Imports: genefilter, geneplotter, methods, MASS, RColorBrewer Suggests: pasilla (>= 0.2.10), vsn, gplots License: GPL (>= 3) Archs: i386, x64 MD5sum: 9ac328135956a365350cd8b2ab7841b6 NeedsCompilation: yes Title: Differential gene expression analysis based on the negative binomial distribution Description: Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution biocViews: Sequencing, ChIPSeq, RNASeq, SAGE, DifferentialExpression Author: Simon Anders, EMBL Heidelberg Maintainer: Simon Anders URL: http://www-huber.embl.de/users/anders/DESeq source.ver: src/contrib/DESeq_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DESeq_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DESeq_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DESeq_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DESeq_1.16.0.tgz vignettes: vignettes/DESeq/inst/doc/DESeq.pdf vignetteTitles: Analysing RNA-Seq data with the "DESeq" package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq/inst/doc/DESeq.R dependsOnMe: DBChIP, metaseqR, SeqGSEA, TCC, tRanslatome importsMe: ampliQueso, ArrayExpressHTS, easyRNASeq, EDASeq, EDDA, HTSFilter, rnaSeqMap suggestsMe: BitSeq, compcodeR, DESeq2, dexus, DiffBind, EDASeq, ELBOW, gage, gCMAP, genefilter, GenomicAlignments, GenomicRanges, oneChannelGUI, SSPA Package: DESeq2 Version: 1.4.5 Depends: GenomicRanges, IRanges, Rcpp (>= 0.10.1), RcppArmadillo (>= 0.3.4.4) Imports: BiocGenerics (>= 0.7.5), methods, locfit, genefilter, geneplotter, RColorBrewer, lattice LinkingTo: Rcpp, RcppArmadillo Suggests: RUnit, gplots, knitr, Biobase, BiocStyle, parathyroidSE, pasilla (>= 0.2.10), DESeq, vsn, GenomicAlignments, GenomicFeatures, Rsamtools, biomaRt License: GPL (>= 3) Archs: i386, x64 MD5sum: fa6375dbc3375a274d67d62353a347f6 NeedsCompilation: yes Title: Differential gene expression analysis based on the negative binomial distribution Description: Estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution biocViews: Sequencing, ChIPSeq, RNASeq, SAGE, DifferentialExpression Author: Michael Love (HSPH Boston), Simon Anders, Wolfgang Huber (EMBL Heidelberg) Maintainer: Michael Love VignetteBuilder: knitr source.ver: src/contrib/DESeq2_1.4.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/DESeq2_1.4.5.zip win64.binary.ver: bin/windows64/contrib/3.1/DESeq2_1.4.5.zip mac.binary.ver: bin/macosx/contrib/3.1/DESeq2_1.4.5.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DESeq2_1.4.5.tgz vignettes: vignettes/DESeq2/inst/doc/beginner.pdf, vignettes/DESeq2/inst/doc/DESeq2.pdf vignetteTitles: Beginner's guide to the "DESeq2" package, Analyzing RNA-Seq data with the "DESeq2" package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq2/inst/doc/beginner.R, vignettes/DESeq2/inst/doc/DESeq2.R dependsOnMe: DEXSeq, MLSeq, TCC importsMe: HTSFilter, phyloseq, ReportingTools suggestsMe: BiocGenerics, compcodeR, DiffBind, gage Package: DEXSeq Version: 1.10.8 Depends: Biobase, GenomicRanges, IRanges, DESeq2 (>= 1.3.69), BiocParallel Imports: BiocGenerics, biomaRt, hwriter, methods, stringr, Rsamtools, statmod, geneplotter, genefilter, RColorBrewer Suggests: GenomicFeatures (>= 1.13.29), pasilla (>= 0.2.22), parathyroidSE, BiocStyle, knitr Enhances: parallel License: GPL (>= 3) MD5sum: 9c34c44ab10e09a8785b98bf7278bfcc NeedsCompilation: no Title: Inference of differential exon usage in RNA-Seq Description: The package is focused on finding differential exon usage using RNA-seq exon counts between samples with different experimental designs. It provides functions that allows the user to make the necessary statistical tests based on a model that uses the negative binomial distribution to estimate the variance between biological replicates and generalized linear models for testing. The package also provides functions for the visualization and exploration of the results. biocViews: Sequencing, RNASeq, DifferentialExpression Author: Simon Anders and Alejandro Reyes , both at EMBL Heidelberg Maintainer: Alejandro Reyes VignetteBuilder: knitr source.ver: src/contrib/DEXSeq_1.10.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/DEXSeq_1.10.8.zip win64.binary.ver: bin/windows64/contrib/3.1/DEXSeq_1.10.8.zip mac.binary.ver: bin/macosx/contrib/3.1/DEXSeq_1.10.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DEXSeq_1.10.8.tgz vignettes: vignettes/DEXSeq/inst/doc/DEXSeq.pdf vignetteTitles: Analyzing RNA-seq data for differential exon usage with the "DEXSeq" package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DEXSeq/inst/doc/DEXSeq.R suggestsMe: GenomicRanges, oneChannelGUI Package: dexus Version: 1.4.0 Depends: R (>= 2.15), methods, BiocGenerics Suggests: parallel, statmod, stats, DESeq, RColorBrewer License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 3f097edae0eb3615adfb1d0d44ea7b48 NeedsCompilation: yes Title: DEXUS - Identifying Differential Expression in RNA-Seq Studies with Unknown Conditions or without Replicates Description: DEXUS identifies differentially expressed genes in RNA-Seq data under all possible study designs such as studies without replicates, without sample groups, and with unknown conditions. DEXUS works also for known conditions, for example for RNA-Seq data with two or multiple conditions. RNA-Seq read count data can be provided both by the S4 class Count Data Set and by read count matrices. Differentially expressed transcripts can be visualized by heatmaps, in which unknown conditions, replicates, and samples groups are also indicated. This software is fast since the core algorithm is written in C. For very large data sets, a parallel version of DEXUS is provided in this package. DEXUS is a statistical model that is selected in a Bayesian framework by an EM algorithm. DEXUS does not need replicates to detect differentially expressed transcripts, since the replicates (or conditions) are estimated by the EM method for each transcript. The method provides an informative/non-informative value to extract differentially expressed transcripts at a desired significance level or power. biocViews: Sequencing, Mus_musculus, Homo_sapiens, Zea_Mays, Macaca_mulatta, Pan_troglodytes, RNASeq, GeneExpression, DifferentialExpression, CellBiology, HapMap, RNAseqData, Classification, QualityControl Author: Guenter Klambauer Maintainer: Guenter Klambauer source.ver: src/contrib/dexus_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/dexus_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/dexus_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/dexus_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/dexus_1.4.0.tgz vignettes: vignettes/dexus/inst/doc/dexus.pdf vignetteTitles: dexus: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dexus/inst/doc/dexus.R Package: DFP Version: 1.22.0 Depends: methods, Biobase (>= 2.5.5) License: GPL-2 MD5sum: 1a699db432a929b8646ce3807d3f7b12 NeedsCompilation: no Title: Gene Selection Description: This package provides a supervised technique able to identify differentially expressed genes, based on the construction of \emph{Fuzzy Patterns} (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values. biocViews: Microarray, DifferentialExpression Author: R. Alvarez-Gonzalez, D. Glez-Pena, F. Diaz, F. Fdez-Riverola Maintainer: Rodrigo Alvarez-Glez source.ver: src/contrib/DFP_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DFP_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DFP_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DFP_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DFP_1.22.0.tgz vignettes: vignettes/DFP/inst/doc/DFP.pdf vignetteTitles: Howto: Discriminat Fuzzy Pattern hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DFP/inst/doc/DFP.R Package: DiffBind Version: 1.10.2 Depends: R (>= 2.15.0), GenomicRanges, limma, GenomicAlignments Imports: RColorBrewer, amap, edgeR (>= 2.3.58), gplots, grDevices, stats, utils, IRanges, zlibbioc, lattice LinkingTo: Rsamtools Suggests: DESeq, Rsamtools, DESeq2, BiocStyle Enhances: rgl, parallel, BiocParallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 2ad7cc3477cfef878f85af4a0d8722b7 NeedsCompilation: yes Title: Differential Binding Analysis of ChIP-Seq peak data Description: Compute differentially bound sites from multiple ChIP-seq experiments using affinity (quantitative) data. Also enables occupancy (overlap) analysis and plotting functions. biocViews: Sequencing, ChIPSeq Author: Rory Stark, Gordon Brown Maintainer: Rory Stark source.ver: src/contrib/DiffBind_1.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/DiffBind_1.10.2.zip win64.binary.ver: bin/windows64/contrib/3.1/DiffBind_1.10.2.zip mac.binary.ver: bin/macosx/contrib/3.1/DiffBind_1.10.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DiffBind_1.10.2.tgz vignettes: vignettes/DiffBind/inst/doc/DiffBind.pdf vignetteTitles: DiffBind: Differential binding analysis of ChIP-Seq peak data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DiffBind/inst/doc/DiffBind.R dependsOnMe: ChIPQC Package: diffGeneAnalysis Version: 1.46.0 Imports: graphics, grDevices, minpack.lm (>= 1.0-4), stats, utils License: GPL MD5sum: ad214a89f49d20b0db5ab87190cfe510 NeedsCompilation: no Title: Performs differential gene expression Analysis Description: Analyze microarray data biocViews: Microarray, DifferentialExpression Author: Choudary Jagarlamudi Maintainer: Choudary Jagarlamudi source.ver: src/contrib/diffGeneAnalysis_1.46.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/diffGeneAnalysis_1.46.0.zip win64.binary.ver: bin/windows64/contrib/3.1/diffGeneAnalysis_1.46.0.zip mac.binary.ver: bin/macosx/contrib/3.1/diffGeneAnalysis_1.46.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/diffGeneAnalysis_1.46.0.tgz vignettes: vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.pdf vignetteTitles: Documentation on diffGeneAnalysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/diffGeneAnalysis/inst/doc/diffGeneAnalysis.R Package: DirichletMultinomial Version: 1.6.0 Depends: IRanges Imports: stats4, methods Suggests: lattice, parallel, MASS, RColorBrewer, xtable License: LGPL-3 Archs: i386, x64 MD5sum: 02e348eb02f405a650995a56ea852b42 NeedsCompilation: yes Title: Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data Description: Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial. biocViews: Sequencing, Clustering, Classification Author: Martin Morgan Maintainer: Martin Morgan SystemRequirements: gsl source.ver: src/contrib/DirichletMultinomial_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DirichletMultinomial_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DirichletMultinomial_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DirichletMultinomial_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DirichletMultinomial_1.6.0.tgz vignettes: vignettes/DirichletMultinomial/inst/doc/DirichletMultinomial.pdf vignetteTitles: An introduction to DirichletMultinomial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE importsMe: TFBSTools Package: dks Version: 1.10.0 Depends: R (>= 2.8) Imports: cubature License: GPL MD5sum: b0b862cf46432530ebd2e0a6c50f5791 NeedsCompilation: no Title: The double Kolmogorov-Smirnov package for evaluating multiple testing procedures. Description: The dks package consists of a set of diagnostic functions for multiple testing methods. The functions can be used to determine if the p-values produced by a multiple testing procedure are correct. These functions are designed to be applied to simulated data. The functions require the entire set of p-values from multiple simulated studies, so that the joint distribution can be evaluated. biocViews: MultipleComparison, QualityControl Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/dks_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/dks_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/dks_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/dks_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/dks_1.10.0.tgz vignettes: vignettes/dks/inst/doc/dks.pdf vignetteTitles: dksTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dks/inst/doc/dks.R Package: DMRcate Version: 1.0.2 Depends: R (>= 3.1.0), limma, minfi, DMRcatedata Imports: methods, graphics Suggests: knitr, RUnit, BiocGenerics, IlluminaHumanMethylation450kanno.ilmn12.hg19, GenomicRanges License: file LICENSE MD5sum: 43f599acbd390c10b034e4a9301a55c4 NeedsCompilation: no Title: Illumina 450K methylation array spatial analysis methods Description: De novo identification and extraction of differentially methylated regions (DMRs) in the human genome using Illumina Infinium HumanMethylation450 BeadChip array data. Provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. Includes bedGraph generation, GRanges generation and plotting functions. biocViews: DifferentialMethylation, GeneExpression, Microarray, MethylationArray, Genetics, DifferentialExpression, GenomeAnnotation, DNAMethylation, OneChannel, TwoChannel, MultipleComparison, QualityControl, TimeCourse Author: Tim Peters Maintainer: Tim Peters VignetteBuilder: knitr source.ver: src/contrib/DMRcate_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/DMRcate_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/DMRcate_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/DMRcate_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DMRcate_1.0.2.tgz vignettes: vignettes/DMRcate/inst/doc/DMRcate.pdf vignetteTitles: The DMRcate package user's guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/DMRcate/inst/doc/DMRcate.R Package: DMRforPairs Version: 1.0.2 Depends: R (>= 2.15.2), Gviz (>= 1.2.1), R2HTML (>= 2.2.1), GenomicRanges (>= 1.10.7), parallel License: GPL (>= 2) MD5sum: 84f410e2cb9323b22e43f780c4136fca NeedsCompilation: no Title: DMRforPairs: identifying Differentially Methylated Regions between unique samples using array based methylation profiles Description: DMRforPairs (formerly DMR2+) allows researchers to compare n>=2 unique samples with regard to their methylation profile. The (pairwise) comparison of n unique single samples distinguishes DMRforPairs from other existing pipelines as these often compare groups of samples in either single CpG locus or region based analysis. DMRforPairs defines regions of interest as genomic ranges with sufficient probes located in close proximity to each other. Probes in one region are optionally annotated to the same functional class(es). Differential methylation is evaluated by comparing the methylation values within each region between individual samples and (if the difference is sufficiently large), testing this difference formally for statistical significance. biocViews: Microarray, DNAMethylation, DifferentialMethylation, ReportWriting, Visualization, Annotation Author: Martin Rijlaarsdam [aut, cre], Yvonne vd Zwan [aut], Lambert Dorssers [aut], Leendert Looijenga [aut] Maintainer: Martin Rijlaarsdam URL: http://www.martinrijlaarsdam.nl, http://www.erasmusmc.nl/pathologie/research/lepo/3898639/ source.ver: src/contrib/DMRforPairs_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/DMRforPairs_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/DMRforPairs_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/DMRforPairs_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DMRforPairs_1.0.2.tgz vignettes: vignettes/DMRforPairs/inst/doc/DMRforPairs_vignette.pdf vignetteTitles: DMRforPairs_vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DMRforPairs/inst/doc/DMRforPairs_vignette.R Package: DNAcopy Version: 1.38.1 License: GPL (>= 2) Archs: i386, x64 MD5sum: 73d440a71c9a8229d7ecb3008fd4246a NeedsCompilation: yes Title: DNA copy number data analysis Description: Segments DNA copy number data using circular binary segmentation to detect regions with abnormal copy number biocViews: Microarray, CopyNumberVariation Author: Venkatraman E. Seshan, Adam Olshen Maintainer: Venkatraman E. Seshan source.ver: src/contrib/DNAcopy_1.38.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/DNAcopy_1.38.1.zip win64.binary.ver: bin/windows64/contrib/3.1/DNAcopy_1.38.1.zip mac.binary.ver: bin/macosx/contrib/3.1/DNAcopy_1.38.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DNAcopy_1.38.1.tgz vignettes: vignettes/DNAcopy/inst/doc/DNAcopy.pdf vignetteTitles: DNAcopy hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DNAcopy/inst/doc/DNAcopy.R dependsOnMe: CGHcall, cghMCR, Clonality, CNVrd2, CopyNumber450k, CRImage, MEDIPS, snapCGH, SomatiCA importsMe: ADaCGH2, ArrayTV, ChAMP, Clonality, CNAnorm, cn.farms, GWASTools, MEDIPS, MinimumDistance, QDNAseq, Repitools, snapCGH, SomatiCA suggestsMe: beadarraySNP, Clonality, cn.mops, fastseg, genoset Package: DNaseR Version: 1.2.0 Depends: R (>= 2.10.0), IRanges Imports: Rsamtools, GenomicRanges Suggests: RUnit, BiocGenerics License: GPL-2 + file LICENSE MD5sum: 7e01a561b2e067bd41d38e8c6dd8d51b NeedsCompilation: no Title: DNase I footprinting analysis of DNase-seq data Description: Strand-specific digital genomic footprinting in DNase-seq data. The cumulative Skellam distribution function (package 'skellam') is used to detect significant normalized count differences of opposed sign at each DNA strand. This is done in order to determine the protein-binding footprint flanks. Preprocessing of the mapped reads is recommended before running DNaseR (e.g., quality checking and removal of sequence-specific bias). biocViews: Transcription, Genetics Author: Pedro Madrigal Maintainer: Pedro Madrigal source.ver: src/contrib/DNaseR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DNaseR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DNaseR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DNaseR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DNaseR_1.2.0.tgz vignettes: vignettes/DNaseR/inst/doc/DNaseR.pdf vignetteTitles: DNaseR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/DNaseR/inst/doc/DNaseR.R Package: domainsignatures Version: 1.24.0 Depends: R (>= 2.4.0), KEGG.db, prada, biomaRt, methods Imports: AnnotationDbi License: Artistic-2.0 MD5sum: e642aad1174d8095b16c867f8bf4ce85 NeedsCompilation: no Title: Geneset enrichment based on InterPro domain signatures Description: Find significantly enriched gene classifications in a list of functionally undescribed genes based on their InterPro domain structure. biocViews: Annotation, Pathways, GeneSetEnrichment Author: Florian Hahne, Tim Beissbarth Maintainer: Florian Hahne source.ver: src/contrib/domainsignatures_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/domainsignatures_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/domainsignatures_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/domainsignatures_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/domainsignatures_1.24.0.tgz vignettes: vignettes/domainsignatures/inst/doc/domainenrichment.pdf vignetteTitles: Gene set enrichment using InterPro domain signatures hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/domainsignatures/inst/doc/domainenrichment.R Package: DOSE Version: 2.2.1 Depends: R (>= 2.10), ggplot2 Imports: methods, plyr, qvalue, stats4, AnnotationDbi, DO.db, igraph, scales, reshape2, graphics, GOSemSim, grid Suggests: clusterProfiler, ReactomePA, knitr, org.Hs.eg.db License: Artistic-2.0 MD5sum: ca30538e9d35fd711bc9172e2632bc88 NeedsCompilation: no Title: Disease Ontology Semantic and Enrichment analysis Description: Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring DO semantic similarities, and hypergeometric test for enrichment analysis. biocViews: Annotation Author: Guangchuang Yu, Li-Gen Wang Maintainer: Guangchuang Yu VignetteBuilder: knitr source.ver: src/contrib/DOSE_2.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/DOSE_2.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/DOSE_2.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/DOSE_2.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DOSE_2.2.1.tgz vignettes: vignettes/DOSE/inst/doc/DOSE.pdf vignetteTitles: DOSE - an R package for Disease Ontology Semantic and Enrichment hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DOSE/inst/doc/DOSE.R importsMe: clusterProfiler, ReactomePA suggestsMe: ChIPseeker, GOSemSim Package: DriverNet Version: 1.4.0 Depends: R (>= 2.10), methods License: GPL-3 MD5sum: e217dbd31ce32ed57ce44edc52df3513 NeedsCompilation: no Title: Drivernet: uncovering somatic driver mutations modulating transcriptional networks in cancer Description: DriverNet is a package to predict functional important driver genes in cancer by integrating genome data (mutation and copy number variation data) and transcriptome data (gene expression data). The different kinds of data are combined by an influence graph, which is a gene-gene interaction network deduced from pathway data. A greedy algorithm is used to find the possible driver genes, which may mutated in a larger number of patients and these mutations will push the gene expression values of the connected genes to some extreme values. biocViews: Network Author: Ali Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab Shah Maintainer: Jiarui Ding source.ver: src/contrib/DriverNet_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DriverNet_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DriverNet_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DriverNet_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DriverNet_1.4.0.tgz vignettes: vignettes/DriverNet/inst/doc/DriverNet-Overview.pdf vignetteTitles: An introduction to DriverNet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DriverNet/inst/doc/DriverNet-Overview.R Package: DrugVsDisease Version: 2.4.0 Depends: R (>= 2.10), affy, limma, biomaRt, ArrayExpress, GEOquery, DrugVsDiseasedata, cMap2data, qvalue Imports: annotate, hgu133a.db, hgu133a2.db, hgu133plus2.db, RUnit, BiocGenerics, xtable License: GPL-3 MD5sum: 35804d826aef159fd0feaeacc2f5ea13 NeedsCompilation: no Title: Comparison of disease and drug profiles using Gene set Enrichment Analysis Description: This package generates ranked lists of differential gene expression for either disease or drug profiles. Input data can be downloaded from Array Express or GEO, or from local CEL files. Ranked lists of differential expression and associated p-values are calculated using Limma. Enrichment scores (Subramanian et al. PNAS 2005) are calculated to a reference set of default drug or disease profiles, or a set of custom data supplied by the user. Network visualisation of significant scores are output in Cytoscape format. biocViews: Microarray, GeneExpression, Clustering Author: C. Pacini Maintainer: j. Saez-Rodriguez source.ver: src/contrib/DrugVsDisease_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DrugVsDisease_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DrugVsDisease_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DrugVsDisease_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DrugVsDisease_2.4.0.tgz vignettes: vignettes/DrugVsDisease/inst/doc/DrugVsDisease.pdf vignetteTitles: DrugVsDisease hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DrugVsDisease/inst/doc/DrugVsDisease.R Package: DSS Version: 2.2.0 Depends: Biobase, locfdr Imports: methods,bsseq,edgeR License: GPL MD5sum: 669724a94da89344a15564af0c51ccbd NeedsCompilation: no Title: Dispersion shrinakge for sequencing data. Description: DSS is an R library performing differntial analysis for count-based sequencing data. It detectes differentially expressed genes (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from bisulfite sequencing (BS-seq). The core of DSS is a new dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions. biocViews: Sequencing, RNASeq, ChIPSeq, DNAMethylation, DifferentialExpression Author: Hao Wu Maintainer: Hao Wu source.ver: src/contrib/DSS_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DSS_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DSS_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DSS_2.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DSS_2.2.0.tgz vignettes: vignettes/DSS/inst/doc/DSS.pdf vignetteTitles: Differential expression for RNA-seq data with dispersion shrinkage hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DSS/inst/doc/DSS.R suggestsMe: compcodeR Package: DTA Version: 2.10.0 Depends: R (>= 2.10), LSD Imports: scatterplot3d License: Artistic-2.0 MD5sum: fc8111bd719c3429282f51ebca6f7ba4 NeedsCompilation: no Title: Dynamic Transcriptome Analysis Description: Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements. biocViews: Microarray, DifferentialExpression, GeneExpression, Transcription Author: Bjoern Schwalb, Benedikt Zacher, Sebastian Duemcke, Achim Tresch Maintainer: Bjoern Schwalb source.ver: src/contrib/DTA_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DTA_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DTA_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DTA_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DTA_2.10.0.tgz vignettes: vignettes/DTA/inst/doc/DTA.pdf vignetteTitles: A guide to Dynamic Transcriptome Analysis (DTA) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DTA/inst/doc/DTA.R Package: dualKS Version: 1.24.0 Depends: R (>= 2.6.0), Biobase (>= 1.15.0), affy, methods Imports: graphics License: LGPL (>= 2.0) MD5sum: 84ba6b368bb4801613ea1530718fd9e8 NeedsCompilation: no Title: Dual KS Discriminant Analysis and Classification Description: This package implements a Kolmogorov Smirnov rank-sum based algorithm for training (i.e. discriminant analysis--identification of genes that discriminate between classes) and classification of gene expression data sets. One of the chief strengths of this approach is that it is amenable to the "multiclass" problem. That is, it can discriminate between more than 2 classes. biocViews: Microarray, Classification Author: Eric J. Kort, Yarong Yang Maintainer: Eric J. Kort , Yarong Yang source.ver: src/contrib/dualKS_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/dualKS_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/dualKS_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/dualKS_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/dualKS_1.24.0.tgz vignettes: vignettes/dualKS/inst/doc/dualKS.pdf vignetteTitles: dualKS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dualKS/inst/doc/dualKS.R Package: dyebias Version: 1.22.0 Depends: R (>= 1.4.1), marray, Biobase Suggests: limma, convert, GEOquery, dyebiasexamples, methods License: GPL-3 MD5sum: 1f38929a71bd1f80f29b0261d6f576c4 NeedsCompilation: no Title: The GASSCO method for correcting for slide-dependent gene-specific dye bias Description: Many two-colour hybridizations suffer from a dye bias that is both gene-specific and slide-specific. The former depends on the content of the nucleotide used for labeling; the latter depends on the labeling percentage. The slide-dependency was hitherto not recognized, and made addressing the artefact impossible. Given a reasonable number of dye-swapped pairs of hybridizations, or of same vs. same hybridizations, both the gene- and slide-biases can be estimated and corrected using the GASSCO method (Margaritis et al., Mol. Sys. Biol. 5:266 (2009), doi:10.1038/msb.2009.21) biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Philip Lijnzaad and Thanasis Margaritis Maintainer: Philip Lijnzaad URL: http://www.holstegelab.nl/publications/margaritis_lijnzaad source.ver: src/contrib/dyebias_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/dyebias_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/dyebias_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/dyebias_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/dyebias_1.22.0.tgz vignettes: vignettes/dyebias/inst/doc/dyebias-vignette.pdf vignetteTitles: dye bias correction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/dyebias/inst/doc/dyebias-vignette.R Package: DynDoc Version: 1.42.0 Depends: methods, utils Imports: methods License: Artistic-2.0 MD5sum: 0225bb72c9c819a38cb55428a6a11862 NeedsCompilation: no Title: Dynamic document tools Description: A set of functions to create and interact with dynamic documents and vignettes. biocViews: ReportWriting, Infrastructure Author: R. Gentleman, Jeff Gentry Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/DynDoc_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/DynDoc_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/DynDoc_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/DynDoc_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/DynDoc_1.42.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: tkWidgets Package: EasyqpcR Version: 1.7.0 Imports: plyr, matrixStats, plotrix, gWidgetsRGtk2 Suggests: SLqPCR, qpcrNorm, qpcR, knitr License: GPL (>=2) MD5sum: 08f1c7321f98eb0231585b65fe2668f0 NeedsCompilation: no Title: EasyqpcR for low-throughput real-time quantitative PCR data analysis Description: This package is based on the qBase algorithms published by Hellemans et al. in 2007. The EasyqpcR package allows you to import easily qPCR data files as described in the vignette. Thereafter, you can calculate amplification efficiencies, relative quantities and their standard errors, normalization factors based on the best reference genes choosen (using the SLqPCR package), and then the normalized relative quantities, the NRQs scaled to your control and their standard errors. This package has been created for low-throughput qPCR data analysis. biocViews: qPCR, GeneExpression Author: Le Pape Sylvain Maintainer: Le Pape Sylvain source.ver: src/contrib/EasyqpcR_1.7.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EasyqpcR_1.7.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EasyqpcR_1.7.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EasyqpcR_1.7.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EasyqpcR_1.7.0.tgz vignettes: vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.pdf vignetteTitles: EasyqpcR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EasyqpcR/inst/doc/vignette_EasyqpcR.R Package: easyRNASeq Version: 2.0.8 Imports: Biobase (>= 2.24.0), BiocGenerics (>= 0.10.0), biomaRt (>= 2.20.0), Biostrings (>= 2.32.1), DESeq (>= 1.16.0), edgeR (>= 3.6.6), genomeIntervals (>= 1.20.1), GenomicAlignments (>= 1.0.2), GenomicRanges (>= 1.16.3), graphics, IRanges (>= 1.22.9), LSD (>= 2.5), methods, parallel, Rsamtools (>= 1.16.1), ShortRead (>= 1.22.0), utils Suggests: BiocStyle (>= 1.2.0), BSgenome (>= 1.32.0), BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.1000), GenomicFeatures (>= 1.16.2), RnaSeqTutorial (>= 0.2.0), RUnit (>= 0.4.26) License: Artistic-2.0 MD5sum: 16b42680ffff6b71b03960da00a88050 NeedsCompilation: no Title: Count summarization and normalization for RNA-Seq data. Description: Calculates the coverage of high-throughput short-reads against a genome of reference and summarizes it per feature of interest (e.g. exon, gene, transcript). The data can be normalized as 'RPKM' or by the 'DESeq' or 'edgeR' package. biocViews: GeneExpression, RNASeq, Genetics, Preprocessing Author: Nicolas Delhomme, Ismael Padioleau, Bastian Schiffthaler Maintainer: Nicolas Delhomme source.ver: src/contrib/easyRNASeq_2.0.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/easyRNASeq_2.0.8.zip win64.binary.ver: bin/windows64/contrib/3.1/easyRNASeq_2.0.8.zip mac.binary.ver: bin/macosx/contrib/3.1/easyRNASeq_2.0.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/easyRNASeq_2.0.8.tgz vignettes: vignettes/easyRNASeq/inst/doc/easyRNASeq.pdf vignetteTitles: easyRNASeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/easyRNASeq/inst/doc/easyRNASeq.R suggestsMe: SeqGSEA Package: EBarrays Version: 2.28.0 Depends: R (>= 1.8.0), Biobase, lattice, methods Imports: Biobase, cluster, graphics, grDevices, lattice, methods, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: b8d963fd7d7fa417be25a8afdd690a44 NeedsCompilation: yes Title: Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification Description: EBarrays provides tools for the analysis of replicated/unreplicated microarray data. biocViews: Clustering, DifferentialExpression Author: Ming Yuan, Michael Newton, Deepayan Sarkar and Christina Kendziorski Maintainer: Ming Yuan source.ver: src/contrib/EBarrays_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EBarrays_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EBarrays_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EBarrays_2.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EBarrays_2.28.0.tgz vignettes: vignettes/EBarrays/inst/doc/vignette.pdf vignetteTitles: Introduction to EBarrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBarrays/inst/doc/vignette.R dependsOnMe: EBcoexpress, gaga, geNetClassifier importsMe: casper suggestsMe: Category Package: EBcoexpress Version: 1.8.0 Depends: EBarrays, mclust, minqa Suggests: graph, igraph, colorspace License: GPL (>= 2) Archs: i386, x64 MD5sum: 810f603b6e9f07b0f88507f4e5288dd3 NeedsCompilation: yes Title: EBcoexpress for Differential Co-Expression Analysis Description: An Empirical Bayesian Approach to Differential Co-Expression Analysis at the Gene-Pair Level biocViews: Bayesian Author: John A. Dawson Maintainer: John A. Dawson source.ver: src/contrib/EBcoexpress_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EBcoexpress_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EBcoexpress_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EBcoexpress_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EBcoexpress_1.8.0.tgz vignettes: vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.pdf vignetteTitles: EBcoexpress Demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBcoexpress/inst/doc/EBcoexpressVignette.R Package: EBImage Version: 4.6.0 Imports: BiocGenerics (>= 0.7.1), methods, graphics, stats, abind, tiff, jpeg, png, locfit Suggests: BiocStyle License: LGPL Archs: i386, x64 MD5sum: 3852945c46db6144e64a0a5b1053a4fd NeedsCompilation: yes Title: Image processing toolbox for R Description: EBImage is an R package which provides general purpose functionality for the reading, writing, processing and analysis of images. Furthermore, in the context of microscopy based cellular assays, EBImage offers tools to transform the images, segment cells and extract quantitative cellular descriptors. biocViews: Visualization Author: Gregoire Pau, Andrzej Oles, Mike Smith, Oleg Sklyar, Wolfgang Huber Maintainer: Andrzej Oles source.ver: src/contrib/EBImage_4.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EBImage_4.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EBImage_4.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EBImage_4.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EBImage_4.6.0.tgz vignettes: vignettes/EBImage/inst/doc/EBImage-introduction.pdf vignetteTitles: Introduction to EBImage hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBImage/inst/doc/EBImage-introduction.R dependsOnMe: CRImage, imageHTS suggestsMe: HilbertVis Package: EBSeq Version: 1.4.0 Depends: blockmodeling, gplots, R (>= 3.0.0) License: Artistic-2.0 MD5sum: 806b2b03d5e9b206994e74b98fe94731 NeedsCompilation: no Title: An R package for gene and isoform differential expression analysis of RNA-seq data Description: Differential Expression analysis at both gene and isoform level using RNA-seq data biocViews: StatisticalMethod, DifferentialExpression, MultipleComparison, RNASeq, Sequencing Author: Ning Leng Maintainer: Ning Leng source.ver: src/contrib/EBSeq_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EBSeq_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EBSeq_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EBSeq_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EBSeq_1.4.0.tgz vignettes: vignettes/EBSeq/inst/doc/EBSeq_Vignette.pdf vignetteTitles: EBSeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBSeq/inst/doc/EBSeq_Vignette.R suggestsMe: compcodeR Package: ecolitk Version: 1.36.0 Depends: R (>= 2.10) Imports: Biobase, graphics, methods Suggests: ecoliLeucine, ecolicdf, graph, multtest, affy License: GPL (>= 2) MD5sum: 9b0af6c28edb5148b02a2c281fd25691 NeedsCompilation: no Title: Meta-data and tools for E. coli Description: Meta-data and tools to work with E. coli. The tools are mostly plotting functions to work with circular genomes. They can used with other genomes/plasmids. biocViews: Annotation, Visualization Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/ecolitk_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ecolitk_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ecolitk_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ecolitk_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ecolitk_1.36.0.tgz vignettes: vignettes/ecolitk/inst/doc/ecolitk.pdf vignetteTitles: ecolitk hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ecolitk/inst/doc/ecolitk.R Package: EDASeq Version: 1.10.0 Depends: BiocGenerics (>= 0.1.3), Biobase (>= 2.15.1), ShortRead (>= 1.11.42), Rsamtools (>= 1.5.75), aroma.light Imports: methods, graphics, BiocGenerics, IRanges (>= 1.13.9), DESeq Suggests: yeastRNASeq, leeBamViews, edgeR, DESeq License: Artistic-2.0 MD5sum: 1f368539ce5479a96126b2231a168a81 NeedsCompilation: no Title: Exploratory Data Analysis and Normalization for RNA-Seq Description: Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010). biocViews: Sequencing, RNASeq, Preprocessing, QualityControl, DifferentialExpression Author: Davide Risso and Sandrine Dudoit Maintainer: Davide Risso source.ver: src/contrib/EDASeq_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/EDASeq_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/EDASeq_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/EDASeq_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EDASeq_1.10.0.tgz vignettes: vignettes/EDASeq/inst/doc/EDASeq.pdf vignetteTitles: EDASeq: Exploratory Data Analysis and Normalization for RNA-Seq data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EDASeq/inst/doc/EDASeq.R dependsOnMe: metaseqR suggestsMe: HTSFilter, oneChannelGUI Package: EDDA Version: 1.0.2.1 Depends: Rcpp (>= 0.10.4),parallel,methods,ROCR,DESeq,baySeq,snow,edgeR Imports: graphics, stats, utils, parallel, methods, ROCR, DESeq, baySeq, snow, edgeR LinkingTo: Rcpp License: GPL (>= 2) Archs: i386, x64 MD5sum: 864dd2ea7bcda42c1d6e9c00fecc1b8e NeedsCompilation: yes Title: Experimental Design in Differential Abundance analysis Description: EDDA can aid in the design of a range of common experiments such as RNA-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. biocViews: Sequencing, ExperimentalDesign, Normalization, RNASeq, ChIPSeq Author: Li Juntao, Luo Huaien, Chia Kuan Hui Burton, Niranjan Nagarajan Maintainer: Chia Kuan Hui Burton , Niranjan Nagarajan source.ver: src/contrib/EDDA_1.0.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/EDDA_1.0.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/EDDA_1.0.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/EDDA_1.0.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/EDDA_1.0.2.1.tgz vignettes: vignettes/EDDA/inst/doc/EDDA.pdf vignetteTitles: EDDA Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EDDA/inst/doc/EDDA.R Package: edgeR Version: 3.6.8 Depends: R (>= 2.15.0), limma Imports: methods Suggests: MASS, statmod, splines, locfit, KernSmooth License: GPL (>=2) Archs: i386, x64 MD5sum: db37a933960facab951ae4b1d3e20893 NeedsCompilation: yes Title: Empirical analysis of digital gene expression data in R Description: Differential expression analysis of RNA-seq and digital gene expression profiles with biological replication. Uses empirical Bayes estimation and exact tests based on the negative binomial distribution. Also useful for differential signal analysis with other types of genome-scale count data. biocViews: GeneExpression, Transcription, AlternativeSplicing, Coverage, DifferentialExpression, DifferentialSplicing, GeneSetEnrichment, Genetics, Bayesian, Clustering, Regression, TimeCourse, SAGE, Sequencing, ChIPSeq, RNASeq, BatchEffect, MultipleComparison, Normalization, QualityControl Author: Yunshun Chen , Davis McCarthy , Aaron Lun , Mark Robinson , Xiaobei Zhou , Gordon Smyth Maintainer: Yunshun Chen , Mark Robinson , Davis McCarthy , Gordon Smyth URL: http://bioinf.wehi.edu.au/edgeR source.ver: src/contrib/edgeR_3.6.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/edgeR_3.6.8.zip win64.binary.ver: bin/windows64/contrib/3.1/edgeR_3.6.8.zip mac.binary.ver: bin/macosx/contrib/3.1/edgeR_3.6.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/edgeR_3.6.8.tgz vignettes: vignettes/edgeR/inst/doc/edgeR.pdf, vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf vignetteTitles: edgeR Vignette, edgeRUsersGuide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/edgeR/inst/doc/edgeR.R dependsOnMe: DBChIP, manta, methylMnM, MLSeq, TCC, tRanslatome importsMe: ampliQueso, ArrayExpressHTS, compcodeR, DiffBind, easyRNASeq, EDDA, HTSFilter, MEDIPS, metaseqR, msmsTests, Repitools, rnaSeqMap, tweeDEseq suggestsMe: baySeq, BitSeq, clonotypeR, cqn, EDASeq, gage, GenomicAlignments, GenomicRanges, goseq, GSVA, oneChannelGUI, SSPA Package: eiR Version: 1.4.7 Depends: R (>= 2.10.0), ChemmineR (>= 2.15.15), methods, DBI Imports: snow, tools, snowfall, RUnit, methods,ChemmineR,RCurl,digest, BiocGenerics LinkingTo: BH Suggests: RCurl,snow,BiocStyle,knitcitations,knitr License: Artistic-2.0 MD5sum: 70bdf9dc525f80c16e67b40f632de473 NeedsCompilation: yes Title: Accelerated similarity searching of small molecules Description: The eiR package provides utilities for accelerated structure similarity searching of very large small molecule data sets using an embedding and indexing approach. biocViews: Infrastructure, DataImport, Clustering, Proteomics Author: Kevin Horan Maintainer: Kevin Horan VignetteBuilder: knitr source.ver: src/contrib/eiR_1.4.7.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/eiR_1.4.7.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/eiR_1.4.7.tgz vignettes: vignettes/eiR/inst/doc/ hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/eiR/inst/doc/eiR.R htmlDocs: vignettes/eiR/inst/doc/eiR.html htmlTitles: "eiR" Package: eisa Version: 1.16.0 Depends: isa2, Biobase (>= 2.17.8), AnnotationDbi, methods Imports: BiocGenerics, Category, genefilter, DBI Suggests: igraph (>= 0.6), Matrix, GOstats, GO.db, KEGG.db, biclust, MASS, xtable, ALL, hgu95av2.db, targetscan.Hs.eg.db, org.Hs.eg.db License: GPL (>= 2) MD5sum: 606120eed4e94b1f83dbc3f40ef4a815 NeedsCompilation: no Title: Expression data analysis via the Iterative Signature Algorithm Description: The Iterative Signature Algorithm (ISA) is a biclustering method; it finds correlated blocks (transcription modules) in gene expression (or other tabular) data. The ISA is capable of finding overlapping modules and it is resilient to noise. This package provides a convenient interface to the ISA, using standard BioConductor data structures; and also contains various visualization tools that can be used with other biclustering algorithms. biocViews: Classification, Visualization, Microarray, GeneExpression Author: Gabor Csardi Maintainer: Gabor Csardi source.ver: src/contrib/eisa_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/eisa_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/eisa_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/eisa_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/eisa_1.16.0.tgz vignettes: vignettes/eisa/inst/doc/EISA_biclust.pdf, vignettes/eisa/inst/doc/EISA_tutorial.pdf vignetteTitles: The eisa and the biclust packages, The Iterative Signature Algorithm for Gene Expression Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/eisa/inst/doc/EISA_biclust.R, vignettes/eisa/inst/doc/EISA_tutorial.R dependsOnMe: ExpressionView importsMe: ExpressionView Package: ELBOW Version: 1.0.0 Depends: R (>= 2.15.0) Suggests: DESeq, GEOquery, limma, simpleaffy, affyPLM, RColorBrewer License: file LICENSE License_is_FOSS: yes License_restricts_use: no MD5sum: 245b3018c3867e678b90d9bb02f389ff NeedsCompilation: no Title: ELBOW - Evaluating foLd change By the lOgit Way Description: Elbow an improved fold change test that uses cluster analysis and pattern recognition to set cut off limits that are derived directly from intrareplicate variance without assuming a normal distribution for as few as 2 biological replicates. Elbow also provides the same consistency as fold testing in cross platform analysis. Elbow has lower false positive and false negative rates than standard fold testing when both are evaluated using T testing and Statistical Analysis of Microarray using 12 replicates (six replicates each for initial and final conditions). Elbow provides a null value based on initial condition replicates and gives error bounds for results to allow better evaluation of significance. biocViews: Technology, Microarray, RNASeq, Sequencing, Sequencing, Software, MultiChannel, OneChannel, TwoChannel, GeneExpression Author: Xiangli Zhang, Natalie Bjorklund, Graham Alvare, Tom Ryzdak, Richard Sparling, Brian Fristensky Maintainer: Graham Alvare , Xiangli Zhang source.ver: src/contrib/ELBOW_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ELBOW_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ELBOW_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ELBOW_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ELBOW_1.0.0.tgz vignettes: vignettes/ELBOW/inst/doc/Elbow_tutorial_vignette.pdf vignetteTitles: Using ELBOW --- the definitive ELBOW tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ELBOW/inst/doc/Elbow_tutorial_vignette.R Package: ensemblVEP Version: 1.4.4 Depends: methods, BiocGenerics, GenomicRanges, VariantAnnotation Imports: Biostrings Suggests: RUnit License: Artistic-2.0 MD5sum: b807aac769cdfd2f1bdd9b8b8a9b7257 NeedsCompilation: no Title: R Interface to Ensembl Variant Effect Predictor Description: Query the Ensembl Variant Effect Predictor via the perl API biocViews: Annotation Author: Valerie Obenchain , Maintainer: Valerie Obenchain SystemRequirements: Ensembl VEP (API version 77) and the Perl package DBD::mysql must be installed. See the package README and Ensembl web site, http://www.ensembl.org/info/docs/tools/vep/index.html for installation instructions. source.ver: src/contrib/ensemblVEP_1.4.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/ensemblVEP_1.4.4.zip win64.binary.ver: bin/windows64/contrib/3.1/ensemblVEP_1.4.4.zip mac.binary.ver: bin/macosx/contrib/3.1/ensemblVEP_1.4.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ensemblVEP_1.4.4.tgz vignettes: vignettes/ensemblVEP/inst/doc/ensemblVEP.pdf vignetteTitles: ensemblVEP hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ensemblVEP/inst/doc/ensemblVEP.R Package: ENVISIONQuery Version: 1.12.0 Depends: rJava, XML, utils License: GPL-2 MD5sum: 5ce01e155d1eaad0c9be2f5082743cef NeedsCompilation: no Title: Retrieval from the ENVISION bioinformatics data portal into R Description: Tools to retrieve data from ENVISION, the Database for Annotation, Visualization and Integrated Discovery portal biocViews: Annotation Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/ENVISIONQuery_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ENVISIONQuery_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ENVISIONQuery_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ENVISIONQuery_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ENVISIONQuery_1.12.0.tgz vignettes: vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.pdf vignetteTitles: An R Package for retrieving data from EnVision into R objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ENVISIONQuery/inst/doc/ENVISIONQuery.R dependsOnMe: IdMappingRetrieval importsMe: IdMappingRetrieval Package: epigenomix Version: 1.4.1 Depends: R (>= 2.12.0), methods, Biobase, IRanges, GenomicRanges Imports: BiocGenerics, beadarray License: LGPL-3 MD5sum: e22d34e68053f464f3936ab6902f46ee NeedsCompilation: no Title: Epigenetic and gene transcription data normalization and integration with mixture models Description: A package for the integrative analysis of RNA-seq or microarray based gene transcription and histone modification data obtained by ChIP-seq. The package provides methods for data preprocessing and matching as well as methods for fitting bayesian mixture models in order to detect genes with differences in both data types. biocViews: ChIPSeq, GeneExpression, DifferentialExpression, Classification Author: Hans-Ulrich Klein, Martin Schaefer Maintainer: Hans-Ulrich Klein source.ver: src/contrib/epigenomix_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/epigenomix_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/epigenomix_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/epigenomix_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/epigenomix_1.4.1.tgz vignettes: vignettes/epigenomix/inst/doc/epigenomix.pdf vignetteTitles: epigenomix package vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/epigenomix/inst/doc/epigenomix.R Package: epivizr Version: 1.2.12 Depends: R (>= 3.0.1), methods, Biobase, GenomicRanges (>= 1.13.47) Imports: httpuv (>= 1.3.0), rjson, IRanges Suggests: testthat, roxygen2, knitr, antiProfilesData, hgu133plus2.db, knitrBootstrap License: GPL-3 MD5sum: 0f50750faee51902f380b49b0eb0552f NeedsCompilation: no Title: R Interface to epiviz web app Description: This package provides Websocket communication to the epiviz web app (http://epiviz.cbcb.umd.edu) for interactive visualization of genomic data. Objects in R/bioc interactive sessions can be displayed in genome browser tracks or plots to be explored by navigation through genomic regions. Fundamental Bioconductor data structures are supported (e.g., GenomicRanges and SummarizedExperiment objects), while providing an easy mechanism to support other data structures. Visualizations (using d3.js) can be easily added to the web app as well. biocViews: Visualization, Infrastructure, GUI Author: Hector Corrada Bravo, Florin Chelaru, Llewellyn Smith, Naomi Goldstein Maintainer: Hector Corrada Bravo VignetteBuilder: knitr source.ver: src/contrib/epivizr_1.2.12.tar.gz win.binary.ver: bin/windows/contrib/3.1/epivizr_1.2.12.zip win64.binary.ver: bin/windows64/contrib/3.1/epivizr_1.2.12.zip mac.binary.ver: bin/macosx/contrib/3.1/epivizr_1.2.12.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/epivizr_1.2.12.tgz vignettes: vignettes/epivizr/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/epivizr/inst/doc/IntroToEpivizr.R htmlDocs: vignettes/epivizr/inst/doc/IntroToEpivizr.html htmlTitles: "Introduction to epivizr" Package: ExiMiR Version: 2.6.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), affy (>= 1.26.1), limma Imports: affyio(>= 1.13.3), Biobase(>= 2.5.5), preprocessCore(>= 1.10.0) License: GPL-2 MD5sum: 804025a8a480e2f49eed708faf2dddcf NeedsCompilation: no Title: R functions for the normalization of Exiqon miRNA array data Description: This package contains functions for reading raw data in ImaGene TXT format obtained from Exiqon miRCURY LNA arrays, annotating them with appropriate GAL files, and normalizing them using a spike-in probe-based method. Other platforms and data formats are also supported. biocViews: Microarray, OneChannel, TwoChannel, Preprocessing, GeneExpression, Transcription Author: Sylvain Gubian , Alain Sewer , PMP SA Maintainer: Sylvain Gubian source.ver: src/contrib/ExiMiR_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ExiMiR_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ExiMiR_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ExiMiR_2.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ExiMiR_2.6.0.tgz vignettes: vignettes/ExiMiR/inst/doc/ExiMiR-vignette.pdf vignetteTitles: Description of ExiMiR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ExiMiR/inst/doc/ExiMiR-vignette.R Package: exomeCopy Version: 1.10.0 Depends: IRanges, GenomicRanges, Rsamtools Imports: stats4, methods Suggests: Biostrings License: GPL (>= 2) Archs: i386, x64 MD5sum: 340ce1c371bb4550ce935f08c17d2ce3 NeedsCompilation: yes Title: Copy number variant detection from exome sequencing read depth Description: Detection of copy number variants (CNV) from exome sequencing samples, including unpaired samples. The package implements a hidden Markov model which uses positional covariates, such as background read depth and GC-content, to simultaneously normalize and segment the samples into regions of constant copy count. biocViews: CopyNumberVariation, Sequencing, Genetics Author: Michael Love Maintainer: Michael Love source.ver: src/contrib/exomeCopy_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/exomeCopy_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/exomeCopy_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/exomeCopy_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/exomeCopy_1.10.0.tgz vignettes: vignettes/exomeCopy/inst/doc/exomeCopy.pdf vignetteTitles: Copy number variant detection in exome sequencing data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/exomeCopy/inst/doc/exomeCopy.R importsMe: Rariant Package: exomePeak Version: 1.2.0 Depends: Rsamtools, GenomicFeatures (>= 1.0.0), rtracklayer License: GPL-2 MD5sum: c7858d1e75b57fb400eead5dcc54f078 NeedsCompilation: no Title: exomePeak Description: The package is developed for the analysis of affinity-based epitranscriptome shortgun sequencing data from MeRIP-seq (maA-seq). It was built on the basis of the exomePeak MATLAB package (Meng, Jia, et al. "Exome-based analysis for RNA epigenome sequencing data." Bioinformatics 29.12 (2013): 1565-1567.) with new functions for differential analysis of two experimental conditions to unveil the dynamics in post-transcriptional regulation of the RNA methylome. The exomePeak R-package accepts and statistically supports multiple biological replicates, internally removes PCR artifacts and multi-mapping reads, outputs exome-based binding sites (RNA methylation sites) and detects differential post-transcriptional RNA modification sites between two experimental conditions in term of percentage rather the absolute amount. The package is still under active development, and we welcome all biology and computation scientist for all kinds of collaborations and communications. Please feel free to contact Dr. Jia Meng if you have any questions. biocViews: Sequencing, MethylSeq, RNASeq Author: Jia Meng Maintainer: Jia Meng source.ver: src/contrib/exomePeak_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/exomePeak_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/exomePeak_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/exomePeak_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/exomePeak_1.2.0.tgz vignettes: vignettes/exomePeak/inst/doc/exomePeak-Overview.pdf vignetteTitles: An introduction to exomePeak hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/exomePeak/inst/doc/exomePeak-Overview.R Package: explorase Version: 1.28.1 Depends: R (>= 2.6.2) Imports: limma, rggobi, RGtk2 Suggests: cairoDevice License: GPL-2 MD5sum: c57898ef78259e0b3cf67b7163cc8793 NeedsCompilation: no Title: GUI for exploratory data analysis of systems biology data Description: explore and analyze *omics data with R and GGobi biocViews: Visualization,Microarray,GUI Author: Michael Lawrence, Eun-kyung Lee, Dianne Cook, Jihong Kim, Hogeun An, and Dongshin Kim Maintainer: Michael Lawrence URL: http://www.metnetdb.org/MetNet_exploRase.htm source.ver: src/contrib/explorase_1.28.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/explorase_1.28.1.zip win64.binary.ver: bin/windows64/contrib/3.1/explorase_1.28.1.zip vignettes: vignettes/explorase/inst/doc/explorase.pdf vignetteTitles: Introduction to exploRase hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/explorase/inst/doc/explorase.R Package: ExpressionView Version: 1.16.1 Depends: caTools, bitops, methods, isa2, eisa, GO.db, KEGG.db, AnnotationDbi Imports: methods, isa2, eisa, GO.db, KEGG.db, AnnotationDbi Suggests: ALL, hgu95av2.db, biclust, affy License: GPL (>= 2) Archs: i386, x64 MD5sum: c07a232f3f5fa4e982acd11a6d1a6a5a NeedsCompilation: yes Title: Visualize biclusters identified in gene expression data Description: ExpressionView visualizes possibly overlapping biclusters in a gene expression matrix. It can use the result of the ISA method (eisa package) or the algorithms in the biclust package or others. The viewer itself was developed using Adobe Flex and runs in a flash-enabled web browser. biocViews: Classification, Visualization, Microarray, GeneExpression Author: Andreas Luscher Maintainer: Gabor Csardi source.ver: src/contrib/ExpressionView_1.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/ExpressionView_1.16.1.zip win64.binary.ver: bin/windows64/contrib/3.1/ExpressionView_1.16.1.zip mac.binary.ver: bin/macosx/contrib/3.1/ExpressionView_1.16.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ExpressionView_1.16.1.tgz vignettes: vignettes/ExpressionView/inst/doc/ExpressionView.format.pdf, vignettes/ExpressionView/inst/doc/ExpressionView.ordering.pdf, vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.pdf vignetteTitles: ExpressionView file format, How the ordering algorithm works, ExpressionView hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ExpressionView/inst/doc/ExpressionView.format.R, vignettes/ExpressionView/inst/doc/ExpressionView.ordering.R, vignettes/ExpressionView/inst/doc/ExpressionView.tutorial.R Package: fabia Version: 2.10.2 Depends: R (>= 2.8.0), Biobase Imports: methods, graphics, grDevices, stats, utils License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 37a529382b6a2915fcbf5cb4682d0b62 NeedsCompilation: yes Title: FABIA: Factor Analysis for Bicluster Acquisition Description: Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C. biocViews: StatisticalMethod, Microarray, DifferentialExpression, MultipleComparison, Clustering, Visualization Author: Sepp Hochreiter Maintainer: Sepp Hochreiter URL: http://www.bioinf.jku.at/software/fabia/fabia.html source.ver: src/contrib/fabia_2.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/fabia_2.10.2.zip win64.binary.ver: bin/windows64/contrib/3.1/fabia_2.10.2.zip mac.binary.ver: bin/macosx/contrib/3.1/fabia_2.10.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/fabia_2.10.2.tgz vignettes: vignettes/fabia/inst/doc/fabia.pdf vignetteTitles: FABIA: Manual for the R package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fabia/inst/doc/fabia.R dependsOnMe: hapFabia Package: factDesign Version: 1.40.0 Depends: Biobase (>= 2.5.5) Imports: stats Suggests: affy, genefilter, multtest License: LGPL MD5sum: 53a930237f3615e9164587b59aa42e43 NeedsCompilation: no Title: Factorial designed microarray experiment analysis Description: This package provides a set of tools for analyzing data from a factorial designed microarray experiment, or any microarray experiment for which a linear model is appropriate. The functions can be used to evaluate tests of contrast of biological interest and perform single outlier detection. biocViews: Microarray, DifferentialExpression Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/factDesign_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/factDesign_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/factDesign_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/factDesign_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/factDesign_1.40.0.tgz vignettes: vignettes/factDesign/inst/doc/factDesign.pdf vignetteTitles: factDesign hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/factDesign/inst/doc/factDesign.R Package: farms Version: 1.16.0 Depends: R (>= 2.8), affy (>= 1.20.0), MASS, methods Imports: affy, MASS, Biobase (>= 1.13.41), methods, graphics Suggests: affydata, Biobase, utils License: LGPL (>= 2.1) MD5sum: e25a7aaf40d30f1d6430032b50f32882 NeedsCompilation: no Title: FARMS - Factor Analysis for Robust Microarray Summarization Description: The package provides the summarization algorithm called Factor Analysis for Robust Microarray Summarization (FARMS) and a novel unsupervised feature selection criterion called "I/NI-calls" biocViews: GeneExpression, Microarray, Preprocessing, QualityControl Author: Djork-Arne Clevert Maintainer: Djork-Arne Clevert URL: http://www.bioinf.jku.at/software/farms/farms.html source.ver: src/contrib/farms_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/farms_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/farms_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/farms_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/farms_1.16.0.tgz vignettes: vignettes/farms/inst/doc/farms.pdf vignetteTitles: Using farms hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/farms/inst/doc/farms.R Package: fastLiquidAssociation Version: 1.0.0 Depends: methods, WGCNA, LiquidAssociation, parallel, stats Suggests: GOstats, yeastCC, org.Sc.sgd.db License: GPL-2 MD5sum: b100c685469f88f501249f415028ddbc NeedsCompilation: no Title: functions for genome-wide application of Liquid Association Description: This package extends the function of the LiquidAssociation package for genome-wide application. It integrates a screening method into the LA analysis to reduce the number of triplets to be examined for a high LA value and provides code for use in subsequent significance analyses. biocViews: Software, Bioinformatics Author: Tina Gunderson Maintainer: Tina Gunderson source.ver: src/contrib/fastLiquidAssociation_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/fastLiquidAssociation_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/fastLiquidAssociation_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/fastLiquidAssociation_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/fastLiquidAssociation_1.0.0.tgz vignettes: vignettes/fastLiquidAssociation/inst/doc/fastLiquidAssociation.pdf vignetteTitles: fastLiquidAssociation Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: fastseg Version: 1.10.0 Depends: R (>= 2.13), GenomicRanges, Biobase Imports: graphics, stats, IRanges, BiocGenerics Suggests: DNAcopy, oligo License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: 86af608743e85bf3266b83209f60396c NeedsCompilation: yes Title: fastseg - a fast segmentation algorithm Description: fastseg implements a very fast and efficient segmentation algorithm. It has similar functionality as DNACopy (Olshen and Venkatraman 2004), but is considerably faster and more flexible. fastseg can segment data from DNA microarrays and data from next generation sequencing for example to detect copy number segments. Further it can segment data from RNA microarrays like tiling arrays to identify transcripts. Most generally, it can segment data given as a matrix or as a vector. Various data formats can be used as input to fastseg like expression set objects for microarrays or GRanges for sequencing data. The segmentation criterion of fastseg is based on a statistical test in a Bayesian framework, namely the cyber t-test (Baldi 2001). The speed-up arises from the facts, that sampling is not necessary in for fastseg and that a dynamic programming approach is used for calculation of the segments' first and higher order moments. biocViews: Classification, CopyNumberVariation Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/fastseg/fastseg.html source.ver: src/contrib/fastseg_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/fastseg_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/fastseg_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/fastseg_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/fastseg_1.10.0.tgz vignettes: vignettes/fastseg/inst/doc/fastseg.pdf vignetteTitles: fastseg: Manual for the R package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fastseg/inst/doc/fastseg.R Package: fdrame Version: 1.36.0 Imports: tcltk, graphics, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 7ddcc0f526f3a467339fb38531133f2c NeedsCompilation: yes Title: FDR adjustments of Microarray Experiments (FDR-AME) Description: This package contains two main functions. The first is fdr.ma which takes normalized expression data array, experimental design and computes adjusted p-values It returns the fdr adjusted p-values and plots, according to the methods described in (Reiner, Yekutieli and Benjamini 2002). The second, is fdr.gui() which creates a simple graphic user interface to access fdr.ma biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Yoav Benjamini, Effi Kenigsberg, Anat Reiner, Daniel Yekutieli Maintainer: Effi Kenigsberg source.ver: src/contrib/fdrame_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/fdrame_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/fdrame_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/fdrame_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/fdrame_1.36.0.tgz vignettes: vignettes/fdrame/inst/doc/fdrame.pdf vignetteTitles: Annotation Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fdrame/inst/doc/fdrame.R Package: ffpe Version: 1.8.0 Depends: R (>= 2.10.0), TTR, methods Imports: Biobase, BiocGenerics, affy, lumi, methylumi, sfsmisc Suggests: genefilter, ffpeExampleData License: GPL (>2) MD5sum: a47c95606ea9e9ac9d252b055d02de83 NeedsCompilation: no Title: Quality assessment and control for FFPE microarray expression data Description: Identify low-quality data using metrics developed for expression data derived from Formalin-Fixed, Paraffin-Embedded (FFPE) data. Also a function for making Concordance at the Top plots (CAT-plots). biocViews: Microarray, GeneExpression, QualityControl Author: Levi Waldron Maintainer: Levi Waldron source.ver: src/contrib/ffpe_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ffpe_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ffpe_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ffpe_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ffpe_1.8.0.tgz vignettes: vignettes/ffpe/inst/doc/ffpe.pdf vignetteTitles: ffpe package user guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ffpe/inst/doc/ffpe.R Package: FGNet Version: 2.0.0 Depends: R (>= 2.15) Imports: igraph (>= 0.6), RCurl, hwriter, R.utils, XML Suggests: RUnit, BiocGenerics, org.Sc.sgd.db Enhances: RColorBrewer, png, RDAVIDWebService License: GPL (>= 2) MD5sum: 81fca060d2a64ad6ac39431c268b5f8c NeedsCompilation: no Title: Functional gene networks derived from biological enrichment analyses Description: Build and visualize functional gene networks from clustering of enrichment analyses in multiple annotation spaces. The package includes an interface to perform the analysis through David and GeneTerm Linker. biocViews: Annotation, GO, Pathways, GeneSetEnrichment, Networks, NetworkVisualization Author: Sara Aibar, Celia Fontanillo, Conrad Droste and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. Maintainer: Sara Aibar URL: http://gtlinker.cnb.csic.es source.ver: src/contrib/FGNet_2.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/FGNet_2.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/FGNet_2.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/FGNet_2.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/FGNet_2.0.0.tgz vignettes: vignettes/FGNet/inst/doc/FGNet-vignette.pdf vignetteTitles: FGNet-vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FGNet/inst/doc/FGNet-vignette.R Package: flagme Version: 1.20.1 Depends: gcspikelite, xcms Imports: gplots, graphics, MASS, methods, SparseM, stats, utils License: LGPL (>= 2) Archs: i386, x64 MD5sum: 02b340db9057b529b19008f262234dac NeedsCompilation: yes Title: Analysis of Metabolomics GC/MS Data Description: Fragment-level analysis of gas chromatography - mass spectrometry metabolomics data biocViews: DifferentialExpression, MassSpectrometry Author: Mark Robinson Maintainer: Mark Robinson , Riccardo Romoli source.ver: src/contrib/flagme_1.20.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/flagme_1.20.1.zip win64.binary.ver: bin/windows64/contrib/3.1/flagme_1.20.1.zip mac.binary.ver: bin/macosx/contrib/3.1/flagme_1.20.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flagme_1.20.1.tgz vignettes: vignettes/flagme/inst/doc/flagme.pdf vignetteTitles: Using flagme -- Fragment-level analysis of GCMS-based metabolomics data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flagme/inst/doc/flagme.R Package: flipflop Version: 1.2.2 Depends: R (>= 2.10.0) Imports: methods, Matrix, IRanges, GenomicRanges License: GPL-3 Archs: i386, x64 MD5sum: 19adfb7de09e3ae365ffc1af438d9891 NeedsCompilation: yes Title: Fast lasso-based isoform prediction as a flow problem Description: Flipflop discovers which isoforms of a gene are expressed in a given sample together with their abundances, based on RNA-Seq read data. biocViews: RNASeq Author: Elsa Bernard, Laurent Jacob, Julien Mairal and Jean-Philippe Vert Maintainer: Elsa Bernard source.ver: src/contrib/flipflop_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/flipflop_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.1/flipflop_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.1/flipflop_1.2.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flipflop_1.2.2.tgz vignettes: vignettes/flipflop/inst/doc/flipflop.pdf vignetteTitles: FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flipflop/inst/doc/flipflop.R Package: flowBeads Version: 1.2.0 Depends: R (>= 2.15.0), methods, Biobase, rrcov, flowCore Imports: flowCore, rrcov, knitr, xtable Suggests: flowViz License: Artistic-2.0 MD5sum: 5c389f898d080dac053a2b04daaa5189 NeedsCompilation: no Title: flowBeads: Analysis of flow bead data Description: This package extends flowCore to provide functionality specific to bead data. One of the goals of this package is to automate analysis of bead data for the purpose of normalisation. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: Nikolas Pontikos Maintainer: Nikolas Pontikos source.ver: src/contrib/flowBeads_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowBeads_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowBeads_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowBeads_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowBeads_1.2.0.tgz vignettes: vignettes/flowBeads/inst/doc/HowTo-flowBeads.pdf vignetteTitles: Analysis of Flow Cytometry Bead Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowBeads/inst/doc/HowTo-flowBeads.R Package: flowBin Version: 1.0.0 Depends: methods, flowCore, flowFP, R (>= 2.10) Imports: class, limma, snow, BiocGenerics Suggests: parallel License: Artistic-2.0 MD5sum: bccd86ab4ca6e02635681f05e2be54fe NeedsCompilation: no Title: Combining multitube flow cytometry data by binning Description: Software to combine flow cytometry data that has been multiplexed into multiple tubes with common markers between them, by establishing common bins across tubes in terms of the common markers, then determining expression within each tube for each bin in terms of the tube-specific markers. biocViews: CellBasedAssays, FlowCytometry Author: Kieran O'Neill Maintainer: Kieran O'Neill source.ver: src/contrib/flowBin_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowBin_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowBin_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowBin_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowBin_1.0.0.tgz vignettes: vignettes/flowBin/inst/doc/flowBin.pdf vignetteTitles: flowBin hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowBin/inst/doc/flowBin.R Package: flowCL Version: 1.0.0 Depends: R (>= 3.0.2), Rgraphviz, SPARQL Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 98e570d96ba2ef02fc29ffd05d5cd4fc NeedsCompilation: no Title: flowCL: Semantic labelling of flow cytometric cell populations Description: Semantic labelling of flow cytometric cell populations. biocViews: FlowCytometry, CellBiology Author: Justin Meskas, Radina Droumeva Maintainer: Justin Meskas source.ver: src/contrib/flowCL_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowCL_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowCL_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowCL_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowCL_1.0.0.tgz vignettes: vignettes/flowCL/inst/doc/flowCL.pdf vignetteTitles: flowCL package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowCL/inst/doc/flowCL.R Package: flowClust Version: 3.4.10 Depends: R(>= 2.5.0),methods, Biobase, graph, RBGL,ellipse, flowViz, mnormt, corpcor, flowCore, clue Imports: BiocGenerics, MCMCpack Suggests: parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 61dfeda48a8fd8be6e1892140ef258f9 NeedsCompilation: yes Title: Clustering for Flow Cytometry Description: Robust model-based clustering using a t-mixture model with Box-Cox transformation. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. biocViews: Clustering, Visualization, FlowCytometry Author: Raphael Gottardo , Kenneth Lo , Greg Finak Maintainer: Greg Finak , Mike Jiang source.ver: src/contrib/flowClust_3.4.10.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowClust_3.4.10.zip win64.binary.ver: bin/windows64/contrib/3.1/flowClust_3.4.10.zip mac.binary.ver: bin/macosx/contrib/3.1/flowClust_3.4.10.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowClust_3.4.10.tgz vignettes: vignettes/flowClust/inst/doc/flowClust.pdf vignetteTitles: flowClust package hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowClust/inst/doc/flowClust.R importsMe: flowPhyto, flowTrans, flowType suggestsMe: BiocGenerics Package: flowCore Version: 1.30.7 Depends: R (>= 2.10.0) Imports: Biobase, BiocGenerics (>= 0.1.14), graph, graphics, methods, rrcov, stats, utils, stats4, corpcor Suggests: Rgraphviz, flowViz, ncdf, flowStats License: Artistic-2.0 Archs: i386, x64 MD5sum: 7177a569f428f3f807c741eea909ca4e NeedsCompilation: yes Title: flowCore: Basic structures for flow cytometry data Description: Provides S4 data structures and basic functions to deal with flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: B. Ellis, P. Haaland, F. Hahne, N. Le Meur, N. Gopalakrishnan, J. Spidlen Maintainer: M.Jiang source.ver: src/contrib/flowCore_1.30.7.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowCore_1.30.7.zip win64.binary.ver: bin/windows64/contrib/3.1/flowCore_1.30.7.zip mac.binary.ver: bin/macosx/contrib/3.1/flowCore_1.30.7.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowCore_1.30.7.tgz vignettes: vignettes/flowCore/inst/doc/HowTo-flowCore.pdf vignetteTitles: Basic Functions for Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowCore/inst/doc/HowTo-flowCore.R htmlDocs: vignettes/flowCore/inst/doc/fcs3.html htmlTitles: "Data File Standard for Flow Cytometry, Version FCS3.0" dependsOnMe: flowBeads, flowBin, flowClust, flowFP, flowMatch, flowStats, flowTrans, flowUtils, flowViz, ncdfFlow, plateCore importsMe: flowBeads, flowFit, flowFlowJo, flowFP, flowMeans, flowPhyto, flowQ, flowStats, flowTrans, flowType, flowViz, plateCore, spade suggestsMe: flowQB, RchyOptimyx Package: flowCyBar Version: 1.0.0 Depends: R (>= 3.0.0) Imports: gplots, vegan, methods License: GPL-2 MD5sum: c55af5aeb19b6744141eba539a8df0ae NeedsCompilation: no Title: Analyze flow cytometric data using gate information Description: A package to analyze flow cytometric data using gate information to follow population/community dynamics biocViews: CellBasedAssays, Clustering, FlowCytometry, Software, Visualization Author: Joachim Schumann , Christin Koch , Susanne Günther , Ingo Fetzer , Susann Müller Maintainer: Joachim Schumann URL: http://www.ufz.de/index.php?de=16773 source.ver: src/contrib/flowCyBar_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowCyBar_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowCyBar_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowCyBar_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowCyBar_1.0.0.tgz vignettes: vignettes/flowCyBar/inst/doc/flowCyBar-manual.pdf vignetteTitles: Analyze flow cytometric data using gate information hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowCyBar/inst/doc/flowCyBar-manual.R Package: flowFit Version: 1.2.0 Depends: R (>= 2.12.2) Imports: flowCore, flowViz, graphics, methods, kza, minpack.lm, gplots Suggests: flowFitExampleData License: Artistic-2.0 MD5sum: d6c59b6bdc309f9776f2598570439264 NeedsCompilation: no Title: Estimate proliferation in cell-tracking dye studies Description: This package estimate the proliferation of a cell population in cell-tracking dye studies. The package uses an R implementation of the Levenberg-Marquardt algorithm (minpack.lm) to fit a set of peaks (corresponding to different generations of cells) over the proliferation-tracking dye distribution in a FACS experiment. biocViews: FlowCytometry, CellBasedAssays Author: Davide Rambaldi Maintainer: Davide Rambaldi source.ver: src/contrib/flowFit_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowFit_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowFit_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowFit_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowFit_1.2.0.tgz vignettes: vignettes/flowFit/inst/doc/HowTo-flowFit.pdf vignetteTitles: Fitting Functions for Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowFit/inst/doc/HowTo-flowFit.R Package: flowFlowJo Version: 1.22.0 Depends: R (>= 2.5.0), MASS, Imports: flowCore, XML (>= 1.96), methods, Biobase License: GPL (>=3) MD5sum: f4f409dc0c9a57cf3cc0c3a863db2356 NeedsCompilation: no Title: Tools for extracting information from a FlowJo workspace and working with the data in the flowCore paradigm. Description: FlowJo is a commercial GUI based software package from TreeStar Inc. for the visualization and analysis of flow cytometry data. One of the FlowJo standard export file types is the "FlowJo Workspace". This is an XML document that describes files and manipulations that have been performed in the FlowJo GUI environment. This package can take apart the FlowJo workspace and deliver the data into R in the flowCore paradigm. biocViews: FlowCytometry Author: John J. Gosink Maintainer: John J. Gosink source.ver: src/contrib/flowFlowJo_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowFlowJo_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowFlowJo_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowFlowJo_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowFlowJo_1.22.0.tgz vignettes: vignettes/flowFlowJo/inst/doc/flowFlowJo.pdf vignetteTitles: Basic Functions for working with FlowJo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowFlowJo/inst/doc/flowFlowJo.R Package: flowFP Version: 1.22.0 Depends: R (>= 2.10), flowCore, flowViz Imports: Biobase, BiocGenerics (>= 0.1.6), flowCore, flowViz, graphics, grDevices, methods, stats, stats4 Suggests: RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: f8860e08983e0b744ae616543ccb64bf NeedsCompilation: yes Title: Fingerprinting for Flow Cytometry Description: Fingerprint generation of flow cytometry data, used to facilitate the application of machine learning and datamining tools for flow cytometry. biocViews: FlowCytometry, CellBasedAssays, Clustering, Visualization Author: Herb Holyst , Wade Rogers Maintainer: Herb Holyst source.ver: src/contrib/flowFP_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowFP_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowFP_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowFP_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowFP_1.22.0.tgz vignettes: vignettes/flowFP/inst/doc/flowFP_HowTo.pdf vignetteTitles: Fingerprinting for Flow Cytometry hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowFP/inst/doc/flowFP_HowTo.R dependsOnMe: flowBin Package: flowMap Version: 1.99.2 Depends: R (>= 3.0.1), ade4(>= 1.5-2), doParallel(>= 1.0.3), abind(>= 1.4.0), reshape2(>= 1.2.2), ggplot2(>= 0.9.3.1), igraph (>= 0.7.1), scales(>= 0.2.3), Matrix(>= 1.1-4), gplots(>= 2.14.1), methods (>= 2.14) Suggests: BiocStyle, knitr License: GPL (>=2) MD5sum: 6441dc9e0cc33fb47d83efee209b0c12 NeedsCompilation: no Title: Mapping cell populations in flow cytometry data for cross-sample comparisons using the Friedman-Rafsky Test Description: flowMap quantifies the similarity of cell populations across multiple flow cytometry samples using a nonparametric multivariate statistical test. The method is able to map cell populations of different size, shape, and proportion across multiple flow cytometry samples. The algorithm can be incorporate in any flow cytometry work flow that requires accurat quantification of similarity between cell populations. biocViews: MultipleComparison, FlowCytometry Author: Chiaowen Joyce Hsiao, Yu Qian, and Richard H. Scheuermann Maintainer: Chiaowen Joyce Hsiao VignetteBuilder: knitr source.ver: src/contrib/flowMap_1.99.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowMap_1.99.2.zip win64.binary.ver: bin/windows64/contrib/3.1/flowMap_1.99.2.zip mac.binary.ver: bin/macosx/contrib/3.1/flowMap_1.99.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowMap_1.99.2.tgz vignettes: vignettes/flowMap/inst/doc/flowMap.pdf vignetteTitles: Multiple sample comparison in flow cytometry data with flowMap hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMap/inst/doc/flowMap.R Package: flowMatch Version: 1.1.2 Depends: R (>= 3.0.0), Rcpp (>= 0.11.0), methods, flowCore Imports: Biobase LinkingTo: Rcpp Suggests: healthyFlowData License: Artistic-2.0 Archs: i386, x64 MD5sum: 15bbfe672c7586f69887a3abcb5d0684 NeedsCompilation: yes Title: Matching and meta-clustering in flow cytometry Description: Matching cell populations and building meta-clusters and templates from a collection of FC samples. biocViews: Clustering, FlowCytometry Author: Ariful Azad Maintainer: Ariful Azad source.ver: src/contrib/flowMatch_1.1.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowMatch_1.1.2.zip win64.binary.ver: bin/windows64/contrib/3.1/flowMatch_1.1.2.zip mac.binary.ver: bin/macosx/contrib/3.1/flowMatch_1.1.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowMatch_1.1.2.tgz vignettes: vignettes/flowMatch/inst/doc/flowMatch.pdf vignetteTitles: flowMatch: Cell population matching and meta-clustering in Flow Cytometry hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMatch/inst/doc/flowMatch.R Package: flowMeans Version: 1.16.0 Depends: R (>= 2.10.0) Imports: Biobase, graphics, grDevices, methods, rrcov, stats, feature, flowCore License: Artistic-2.0 MD5sum: 692c026eb94877285568c0e7523f9874 NeedsCompilation: no Title: Non-parametric Flow Cytometry Data Gating Description: Identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection. Note: R 2.11.0 or newer is required. biocViews: FlowCytometry, CellBiology, Clustering, Cancer, FlowCytometry, StemCells, HIV Author: Nima Aghaeepour Maintainer: Nima Aghaeepour source.ver: src/contrib/flowMeans_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowMeans_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowMeans_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowMeans_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowMeans_1.16.0.tgz vignettes: vignettes/flowMeans/inst/doc/flowMeans.pdf vignetteTitles: flowMeans: Non-parametric Flow Cytometry Data Gating hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMeans/inst/doc/flowMeans.R importsMe: flowPhyto, flowType Package: flowMerge Version: 2.12.0 Depends: graph,feature,flowClust,Rgraphviz,foreach,snow Imports: rrcov,flowCore, graphics, methods, stats, utils Enhances: doMC, multicore License: Artistic-2.0 MD5sum: c13f2e2b79d1a920d64846fc4fdc2e59 NeedsCompilation: no Title: Cluster Merging for Flow Cytometry Data Description: Merging of mixture components for model-based automated gating of flow cytometry data using the flowClust framework. Note: users should have a working copy of flowClust 2.0 installed. biocViews: Clustering, FlowCytometry Author: Greg Finak , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowMerge_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowMerge_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowMerge_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowMerge_2.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowMerge_2.12.0.tgz vignettes: vignettes/flowMerge/inst/doc/flowMerge.pdf vignetteTitles: flowMerge package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMerge/inst/doc/flowMerge.R importsMe: flowType Package: flowPeaks Version: 1.6.0 Depends: R (>= 2.12.0) Enhances: flowCore License: Artistic-1.0 Archs: i386, x64 MD5sum: a34e6a5f5e2a725e15d507ffc03e0838 NeedsCompilation: yes Title: An R package for flow data clustering Description: A fast and automatic clustering to classify the cells into subpopulations based on finding the peaks from the overall density function generated by K-means. biocViews: FlowCytometry, Clustering, Gating Author: Yongchao Ge Maintainer: Yongchao Ge source.ver: src/contrib/flowPeaks_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowPeaks_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowPeaks_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowPeaks_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowPeaks_1.6.0.tgz vignettes: vignettes/flowPeaks/inst/doc/flowPeaks-guide.pdf vignetteTitles: Tutorial of flowPeaks package hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPeaks/inst/doc/flowPeaks-guide.R Package: flowPhyto Version: 1.16.0 Depends: R (>= 1.8.0) Imports: flowClust, flowCore, flowMeans, TTR, caroline(>= 0.6.6) Suggests: RPostgreSQL, zoo, maps, mapdata, plotrix License: Artistic-2.0 MD5sum: 692bd992d261fa0c58da1b020e445bea NeedsCompilation: no Title: Methods for Continuous Flow Cytometry Description: Automated Analysis of Continuous Flow Cytometry Data. biocViews: FlowCytometry, DataImport, QualityControl, Classification, Visualization, Clustering Author: Francois Ribalet Maintainer: Chris Berthiaume URL: http://seaflow.ocean.washington.edu source.ver: src/contrib/flowPhyto_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowPhyto_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowPhyto_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowPhyto_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowPhyto_1.16.0.tgz vignettes: vignettes/flowPhyto/inst/doc/flowPhyto.pdf vignetteTitles: flowPhyto hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPhyto/inst/doc/flowPhyto.R Package: flowPlots Version: 1.12.0 Depends: R (>= 2.13.0), methods Suggests: vcd License: Artistic-2.0 MD5sum: afa29dc1241c5e8aa8a6a7ac3e6d511d NeedsCompilation: no Title: flowPlots: analysis plots and data class for gated flow cytometry data Description: Graphical displays with embedded statistical tests for gated ICS flow cytometry data, and a data class which stores "stacked" data and has methods for computing summary measures on stacked data, such as marginal and polyfunctional degree data. biocViews: FlowCytometry, CellBasedAssays, Visualization, DataRepresentation Author: N. Hawkins, S. Self Maintainer: N. Hawkins source.ver: src/contrib/flowPlots_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowPlots_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowPlots_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowPlots_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowPlots_1.12.0.tgz vignettes: vignettes/flowPlots/inst/doc/flowPlots.pdf vignetteTitles: Plots with Embedded Tests for Gated Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowPlots/inst/doc/flowPlots.R Package: flowQ Version: 1.24.6 Depends: R (>= 2.10.0), methods, BiocGenerics, outliers, lattice, flowViz, mvoutlier, bioDist, parody, RColorBrewer, latticeExtra Imports: methods, BiocGenerics, geneplotter, flowCore, flowViz, IRanges Suggests: flowStats License: Artistic-2.0 MD5sum: 9b0653d2790105e53cabb04477272769 NeedsCompilation: no Title: Quality control for flow cytometry Description: Provides quality control and quality assessment tools for flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: R. Gentleman, F. Hahne, J. Kettman, N. Le Meur, N. Gopalakrishnan Maintainer: Mike Jiang SystemRequirements: ImageMagick source.ver: src/contrib/flowQ_1.24.6.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/flowQ_1.24.6.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowQ_1.24.6.tgz vignettes: vignettes/flowQ/inst/doc/DataQualityAssessment.pdf, vignettes/flowQ/inst/doc/Extending-flowQ.pdf vignetteTitles: Data Quality Assesment for Ungated Flow Cytometry Data, Basic Functions for Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowQ/inst/doc/DataQualityAssessment.R, vignettes/flowQ/inst/doc/Extending-flowQ.R Package: flowQB Version: 1.6.0 Imports: Biobase, graphics,methods, flowCore,stats,MASS Suggests: MASS, flowCore, xtable License: Artistic-2.0 MD5sum: 62f09d555089fd032fac75d736a42149 NeedsCompilation: no Title: Automated Quadratic Characterization of Flow Cytometer Instrument Sensitivity: Q, B and CVinstrinsic calculations. Description: flowQB is a fully automated R Bioconductor package to calculate automatically the detector efficiency (Q), optical background (B) and intrinsic CV of the beads. biocViews: FlowCytometry Author: Faysal El Khettabi Maintainer: Faysal El Khettabi source.ver: src/contrib/flowQB_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowQB_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowQB_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowQB_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowQB_1.6.0.tgz vignettes: vignettes/flowQB/inst/doc/AdvancedflowQBNIH2.pdf, vignettes/flowQB/inst/doc/AdvancedflowQBNIH3.pdf, vignettes/flowQB/inst/doc/IntroductoryflowQBNIH.pdf vignetteTitles: flowQB package, flowQB package, flowQB package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowQB/inst/doc/AdvancedflowQBNIH2.R, vignettes/flowQB/inst/doc/AdvancedflowQBNIH3.R, vignettes/flowQB/inst/doc/IntroductoryflowQBNIH.R Package: flowStats Version: 3.22.6 Depends: R (>= 2.10), flowCore, fda (>= 2.2.6), mvoutlier, cluster, flowWorkspace Imports: BiocGenerics, MASS, flowViz, flowCore, fda (>= 2.2.6), Biobase, methods, grDevices, graphics, stats, utils, KernSmooth, lattice,ks Suggests: xtable Enhances: RBGL,ncdfFlow,graph License: Artistic-2.0 MD5sum: 8f1476aadd064e990b6283ed6e5fe9bb NeedsCompilation: no Title: Statistical methods for the analysis of flow cytometry data Description: Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package. biocViews: FlowCytometry, CellBasedAssays Author: Florian Hahne, Nishant Gopalakrishnan, Alireza Hadj Khodabakhshi, Chao-Jen Wong, Kyongryun Lee Maintainer: Greg Finak and Mike Jiang source.ver: src/contrib/flowStats_3.22.6.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowStats_3.22.6.zip win64.binary.ver: bin/windows64/contrib/3.1/flowStats_3.22.6.zip mac.binary.ver: bin/macosx/contrib/3.1/flowStats_3.22.6.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowStats_3.22.6.tgz vignettes: vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.pdf vignetteTitles: flowStats Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowStats/inst/doc/GettingStartedWithFlowStats.R importsMe: plateCore suggestsMe: flowCore, flowQ Package: flowTrans Version: 1.16.0 Depends: R (>= 2.11.0), flowCore, flowViz,flowClust Imports: flowCore, methods, flowViz, stats, flowClust License: Artistic-2.0 MD5sum: 000181a607edeeb3c019c66b15807afe NeedsCompilation: no Title: Parameter Optimization for Flow Cytometry Data Transformation Description: Profile maximum likelihood estimation of parameters for flow cytometry data transformations. biocViews: FlowCytometry Author: Greg Finak , Juan Manuel-Perez , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowTrans_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowTrans_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowTrans_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowTrans_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowTrans_1.16.0.tgz vignettes: vignettes/flowTrans/inst/doc/flowTrans.pdf vignetteTitles: flowTrans package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowTrans/inst/doc/flowTrans.R Package: flowType Version: 2.2.0 Depends: R (>= 2.10), Rcpp (>= 0.10.4), BH (>= 1.51.0-3) Imports: Biobase, graphics, grDevices, methods, flowCore, flowMeans, sfsmisc, rrcov, flowClust, flowMerge, stats LinkingTo: Rcpp, BH Suggests: xtable License: Artistic-2.0 Archs: i386, x64 MD5sum: 4307ad7805898c291cf672c608075c0e NeedsCompilation: yes Title: Phenotyping Flow Cytometry Assays Description: Phenotyping Flow Cytometry Assays using multidimentional expansion of single dimentional partitions. biocViews: FlowCytometry Author: Nima Aghaeepour, Kieran O'Neill, Adrin Jalali Maintainer: Nima Aghaeepour source.ver: src/contrib/flowType_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowType_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowType_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowType_2.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowType_2.2.0.tgz vignettes: vignettes/flowType/inst/doc/flowType.pdf vignetteTitles: flowType package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowType/inst/doc/flowType.R importsMe: RchyOptimyx Package: flowUtils Version: 1.28.0 Depends: R (>= 2.2.0), flowCore (>= 1.29.20) Imports: Biobase, graph, methods, stats, utils, flowViz, corpcor, RUnit, XML Suggests: gatingMLData License: Artistic-2.0 MD5sum: ed9a5b797b7dfd3a49c28b4ec8e8f44d NeedsCompilation: no Title: Utilities for flow cytometry Description: Provides utilities for flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: N. Gopalakrishnan, F. Hahne, B. Ellis, R. Gentleman, M. Dalphin, N. Le Meur, B. Purcell, J. Spidlen. Maintainer: Josef Spidlen source.ver: src/contrib/flowUtils_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowUtils_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/flowUtils_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/flowUtils_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowUtils_1.28.0.tgz vignettes: vignettes/flowUtils/inst/doc/HowTo-flowUtils.pdf vignetteTitles: Gating-ML support in R hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowUtils/inst/doc/HowTo-flowUtils.R Package: flowViz Version: 1.28.22 Depends: R (>= 2.7.0), flowCore, lattice Imports: stats4, Biobase, flowCore, graphics, grDevices, grid, KernSmooth, lattice, latticeExtra, MASS, methods, RColorBrewer, stats, utils, hexbin,IDPmisc Suggests: colorspace, flowStats,knitr License: Artistic-2.0 MD5sum: d1226d404c7a852b2302ff080185ca70 NeedsCompilation: no Title: Visualization for flow cytometry Description: Provides visualization tools for flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays, Visualization Author: B. Ellis, R. Gentleman, F. Hahne, N. Le Meur, D. Sarkar Maintainer: Mike Jiang VignetteBuilder: knitr source.ver: src/contrib/flowViz_1.28.22.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowViz_1.28.22.zip win64.binary.ver: bin/windows64/contrib/3.1/flowViz_1.28.22.zip mac.binary.ver: bin/macosx/contrib/3.1/flowViz_1.28.22.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowViz_1.28.22.tgz vignettes: vignettes/flowViz/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowViz/inst/doc/filters.R htmlDocs: vignettes/flowViz/inst/doc/filters.html htmlTitles: "Visualizing Gates with Flow Cytometry Data" dependsOnMe: flowClust, flowFP, flowQ, ncdfFlow, plateCore importsMe: flowFit, flowFP, flowQ, flowStats, flowTrans, flowUtils suggestsMe: flowBeads, flowCore, spade Package: flowWorkspace Version: 3.10.09 Depends: R (>= 2.16.0),flowCore,flowViz,ncdfFlow,gridExtra Imports: Biobase, BiocGenerics, graph, graphics, lattice, methods, stats, stats4, utils, RBGL, graph, XML, Biobase, IDPmisc, Cairo, tools,hexbin,gridExtra,Rgraphviz ,data.table ,plyr ,latticeExtra ,Rcpp LinkingTo: Rcpp Suggests: testthat ,flowWorkspaceData ,RSVGTipsDevice License: Artistic-2.0 Archs: i386, x64 MD5sum: 6b9618c6e53b8a91f42fe1d65644d51b NeedsCompilation: yes Title: Import flowJo Workspaces into BioConductor and replicate flowJo gating with flowCore Description: This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis. biocViews: FlowCytometry, DataImport, Preprocessing, DataRepresentation Author: Greg Finak, Mike Jiang Maintainer: Greg Finak ,Mike Jiang source.ver: src/contrib/flowWorkspace_3.10.09.tar.gz win.binary.ver: bin/windows/contrib/3.1/flowWorkspace_3.10.09.zip win64.binary.ver: bin/windows64/contrib/3.1/flowWorkspace_3.10.09.zip mac.binary.ver: bin/macosx/contrib/3.1/flowWorkspace_3.10.09.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/flowWorkspace_3.10.09.tgz vignettes: vignettes/flowWorkspace/inst/doc/flowWorkspace.pdf vignetteTitles: Importing flowJo Workspaces into R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: TRUE hasLICENSE: FALSE Rfiles: vignettes/flowWorkspace/inst/doc/flowWorkspace.R dependsOnMe: flowStats suggestsMe: COMPASS Package: fmcsR Version: 1.6.5 Depends: R (>= 2.10.0), ChemmineR, methods Imports: RUnit, methods,ChemmineR, BiocGenerics,parallel Suggests: BiocStyle,knitr,knitcitations License: Artistic-2.0 Archs: i386, x64 MD5sum: 19cf0d0890a1f6d2844a14271f0971f3 NeedsCompilation: yes Title: Mismatch Tolerant Maximum Common Substructure Searching Description: The fmcsR package introduces an efficient maximum common substructure (MCS) algorithms combined with a novel matching strategy that allows for atom and/or bond mismatches in the substructures shared among two small molecules. The resulting flexible MCSs (FMCSs) are often larger than strict MCSs, resulting in the identification of more common features in their source structures, as well as a higher sensitivity in finding compounds with weak structural similarities. The fmcsR package provides several utilities to use the FMCS algorithm for pairwise compound comparisons, structure similarity searching and clustering. biocViews: MicrotitrePlateAssay, CellBasedAssays, Visualization, Infrastructure, DataImport, Clustering, Proteomics Author: Yan Wang, Tyler Backman, Kevin Horan, Thomas Girke Maintainer: ChemmineR Team URL: http://manuals.bioinformatics.ucr.edu/home/chemminer VignetteBuilder: knitr source.ver: src/contrib/fmcsR_1.6.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/fmcsR_1.6.5.zip win64.binary.ver: bin/windows64/contrib/3.1/fmcsR_1.6.5.zip mac.binary.ver: bin/macosx/contrib/3.1/fmcsR_1.6.5.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/fmcsR_1.6.5.tgz vignettes: vignettes/fmcsR/inst/doc/ hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fmcsR/inst/doc/fmcsR.R htmlDocs: vignettes/fmcsR/inst/doc/fmcsR.html htmlTitles: "fmcsR" importsMe: Rcpi Package: FRGEpistasis Version: 1.0.0 Depends: R (>= 2.15), MASS, fda, methods, stats Imports: utils License: GPL-2 MD5sum: 29987d18050b725581ec5cd777e7f049 NeedsCompilation: no Title: Epistasis Analysis for Quantitative Traits by Functional Regression Model Description: A Tool for Epistasis Analysis Based on Functional Regression Model biocViews: Genetics, NetworkInference, GeneticVariability, Software Author: Futao Zhang Maintainer: Futao Zhang source.ver: src/contrib/FRGEpistasis_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/FRGEpistasis_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/FRGEpistasis_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/FRGEpistasis_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/FRGEpistasis_1.0.0.tgz vignettes: vignettes/FRGEpistasis/inst/doc/FRGEpistasis.pdf vignetteTitles: FRGEpistasis: A Tool for Epistasis Analysis Based on Functional Regression Model hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FRGEpistasis/inst/doc/FRGEpistasis.R Package: frma Version: 1.16.0 Depends: R (>= 2.10.0), Biobase (>= 2.6.0) Imports: Biobase, MASS, DBI, affy, methods, oligo, oligoClasses, preprocessCore, utils, BiocGenerics Suggests: hgu133afrmavecs, frmaExampleData License: GPL (>= 2) MD5sum: e8d53f66c66cf5880b8766b9bd4118db NeedsCompilation: no Title: Frozen RMA and Barcode Description: Preprocessing and analysis for single microarrays and microarray batches. biocViews: Software, Microarray, Preprocessing Author: Matthew N. McCall , Rafael A. Irizarry , with contributions from Terry Therneau Maintainer: Matthew N. McCall URL: http://bioconductor.org source.ver: src/contrib/frma_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/frma_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/frma_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/frma_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/frma_1.16.0.tgz vignettes: vignettes/frma/inst/doc/frma.pdf vignetteTitles: frma: Preprocessing for single arrays and array batches hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/frma/inst/doc/frma.R importsMe: ChIPXpress suggestsMe: frmaTools Package: frmaTools Version: 1.16.0 Depends: R (>= 2.10.0), affy Imports: Biobase, DBI, methods, preprocessCore, stats, utils Suggests: oligo, pd.huex.1.0.st.v2, pd.hugene.1.0.st.v1, frma, affyPLM, hgu133aprobe, hgu133atagprobe, hgu133plus2probe, hgu133acdf, hgu133atagcdf, hgu133plus2cdf, hgu133afrmavecs, frmaExampleData License: GPL (>= 2) MD5sum: 5c206f9057405099448eebf06dccbbfc NeedsCompilation: no Title: Frozen RMA Tools Description: Tools for advanced use of the frma package. biocViews: Software, Microarray, Preprocessing Author: Matthew N. McCall , Rafael A. Irizarry Maintainer: Matthew N. McCall URL: http://bioconductor.org source.ver: src/contrib/frmaTools_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/frmaTools_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/frmaTools_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/frmaTools_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/frmaTools_1.16.0.tgz vignettes: vignettes/frmaTools/inst/doc/frmaTools.pdf vignetteTitles: frmaTools: Create packages containing the vectors used by frma. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/frmaTools/inst/doc/frmaTools.R Package: FunciSNP Version: 1.6.0 Depends: R (>= 2.14.0), ggplot2, TxDb.Hsapiens.UCSC.hg19.knownGene, FunciSNP.data Imports: AnnotationDbi, IRanges, Rsamtools (>= 1.6.1), rtracklayer(>= 1.14.1), methods, ChIPpeakAnno (>= 2.2.0), GenomicRanges, VariantAnnotation, plyr, org.Hs.eg.db, snpStats, ggplot2 (>= 0.9.0), reshape (>= 0.8.4), scales Enhances: parallel License: GPL-3 MD5sum: 8240f7e41c6dec70b12dd458669e28bd NeedsCompilation: no Title: Integrating Functional Non-coding Datasets with Genetic Association Studies to Identify Candidate Regulatory SNPs Description: FunciSNP integrates information from GWAS, 1000genomes and chromatin feature to identify functional SNP in coding or non-coding regions. biocViews: Infrastructure, DataRepresentation, DataImport, SequenceMatching, Annotation Author: Simon G. Coetzee and Houtan Noushmehr, PhD Maintainer: Simon G. Coetzee URL: http://coetzeeseq.usc.edu/publication/Coetzee_SG_et_al_2012/ source.ver: src/contrib/FunciSNP_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/FunciSNP_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/FunciSNP_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/FunciSNP_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/FunciSNP_1.6.0.tgz vignettes: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.pdf vignetteTitles: FunciSNP Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.R Package: gaga Version: 2.10.0 Depends: R (>= 2.8.0), Biobase, coda, EBarrays, mgcv Enhances: parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: dce145926cfc557fe6c34ccea4156392 NeedsCompilation: yes Title: GaGa hierarchical model for high-throughput data analysis Description: Implements the GaGa model for high-throughput data analysis, including differential expression analysis, supervised gene clustering and classification. Additionally, it performs sequential sample size calculations using the GaGa and LNNGV models (the latter from EBarrays package). biocViews: OneChannel, MassSpectrometry, MultipleComparison, DifferentialExpression, Classification Author: David Rossell . Maintainer: David Rossell source.ver: src/contrib/gaga_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gaga_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gaga_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gaga_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gaga_2.10.0.tgz vignettes: vignettes/gaga/inst/doc/gagamanual.pdf vignetteTitles: Manual for the gaga library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaga/inst/doc/gagamanual.R importsMe: casper Package: gage Version: 2.14.4 Depends: R (>= 2.10) Imports: graph, KEGGREST, AnnotationDbi Suggests: pathview, gageData, GO.db, org.Hs.eg.db, hgu133a.db, GSEABase, Rsamtools, GenomicAlignments, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq, DESeq2, edgeR, limma License: GPL (>=2.0) MD5sum: 1e7bd8170afda306ea4c965e2dd57e8e NeedsCompilation: no Title: Generally Applicable Gene-set Enrichment for Pathway Analysis Description: GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods. biocViews: Pathways, GO, DifferentialExpression, Microarray, OneChannel, TwoChannel, RNASeq, Genetics, MultipleComparison, GeneSetEnrichment, GeneExpression, SystemsBiology, Sequencing Author: Weijun Luo Maintainer: Weijun Luo URL: http://www.biomedcentral.com/1471-2105/10/161 source.ver: src/contrib/gage_2.14.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/gage_2.14.4.zip win64.binary.ver: bin/windows64/contrib/3.1/gage_2.14.4.zip mac.binary.ver: bin/macosx/contrib/3.1/gage_2.14.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gage_2.14.4.tgz vignettes: vignettes/gage/inst/doc/dataPrep.pdf, vignettes/gage/inst/doc/gage.pdf, vignettes/gage/inst/doc/RNA-seqWorkflow.pdf vignetteTitles: Gene set and data preparation, Generally Applicable Gene-set/Pathway Analysis, RNA-Seq Data Pathway and Gene-set Analysis Workflows hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gage/inst/doc/dataPrep.R, vignettes/gage/inst/doc/gage.R, vignettes/gage/inst/doc/RNA-seqWorkflow.R suggestsMe: pathview Package: gaggle Version: 1.32.0 Depends: R (>= 2.3.0), rJava (>= 0.4), graph (>= 1.10.2), RUnit (>= 0.4.17) License: GPL version 2 or newer MD5sum: c36a31aff6b7dd162d7f9ed0c1cc0122 NeedsCompilation: no Title: Broadcast data between R and Gaggle Description: This package contains functions enabling data exchange between R and Gaggle enabled bioinformatics software, including Cytoscape, Firegoose and Gaggle Genome Browser. biocViews: ThirdPartyClient, Visualization, Annotation, GraphAndNetwork, DataImport Author: Paul Shannon Maintainer: Christopher Bare URL: http://gaggle.systemsbiology.net/docs/geese/r/ source.ver: src/contrib/gaggle_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gaggle_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gaggle_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gaggle_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gaggle_1.32.0.tgz vignettes: vignettes/gaggle/inst/doc/gaggle.pdf vignetteTitles: Gaggle Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaggle/inst/doc/gaggle.R Package: gaia Version: 2.8.0 Depends: R (>= 2.10) License: GPL-2 MD5sum: 7e34603494fd8fd9a2e34f546dc6b827 NeedsCompilation: no Title: GAIA: An R package for genomic analysis of significant chromosomal aberrations. Description: This package allows to assess the statistical significance of chromosomal aberrations. biocViews: aCGH, CopyNumberVariation Author: Sandro Morganella et al. Maintainer: S. Morganella source.ver: src/contrib/gaia_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gaia_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gaia_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gaia_2.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gaia_2.8.0.tgz vignettes: vignettes/gaia/inst/doc/gaia.pdf vignetteTitles: gaia hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaia/inst/doc/gaia.R Package: gaucho Version: 1.0.0 Depends: R (>= 3.0.0), compiler, GA, graph, heatmap.plus, png, Rgraphviz Suggests: knitr License: GPL-3 MD5sum: d5cfab3fda56d7c69d7bf181912de942 NeedsCompilation: no Title: Genetic Algorithms for Understanding Clonal Heterogeneity and Ordering Description: Use genetic algorithms to determine the relationship between clones in heterogenous populations such as cancer sequencing samples biocViews: Software,Genetics,SNP,Sequencing,SomaticMutation Author: Alex Murison [aut, cre], Christopher Wardell [aut, cre] Maintainer: Alex Murison , Christopher Wardell VignetteBuilder: knitr source.ver: src/contrib/gaucho_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gaucho_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gaucho_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gaucho_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gaucho_1.0.0.tgz vignettes: vignettes/gaucho/inst/doc/gaucho_vignette.pdf vignetteTitles: An introduction to gaucho hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gaucho/inst/doc/gaucho_vignette.R Package: gCMAP Version: 1.8.0 Depends: GSEABase, limma (>= 3.15.14) Imports: Biobase, BiocGenerics, methods, GSEAlm, Category, Matrix (>= 1.0.9), parallel, annotate, genefilter, AnnotationDbi Suggests: DESeq, KEGG.db, reactome.db, RUnit, GO.db, mgsa Enhances: bigmemory, bigmemoryExtras (>= 1.1.2) License: Artistic-2.0 MD5sum: 193423c8492aec438a72cb8789a41a60 NeedsCompilation: no Title: Tools for Connectivity Map-like analyses Description: The gCMAP package provides a toolkit for comparing differential gene expression profiles through gene set enrichment analysis. Starting from normalized microarray or RNA-seq gene expression values (stored in lists of ExpressionSet and CountDataSet objects) the package performs differential expression analysis using the limma or DESeq packages. Supplying a simple list of gene identifiers, global differential expression profiles or data from complete experiments as input, users can use a unified set of several well-known gene set enrichment analysis methods to retrieve experiments with similar changes in gene expression. To take into account the directionality of gene expression changes, gCMAPQuery introduces the SignedGeneSet class, directly extending GeneSet from the GSEABase package. To increase performance of large queries, multiple gene sets are stored as sparse incidence matrices within CMAPCollection eSets. gCMAP offers implementations of 1. Fisher's exact test (Fisher, J R Stat Soc, 1922) 2. The "connectivity map" method (Lamb et al, Science, 2006) 3. Parametric and non-parametric t-statistic summaries (Jiang & Gentleman, Bioinformatics, 2007) and 4. Wilcoxon / Mann-Whitney rank sum statistics (Wilcoxon, Biometrics Bulletin, 1945) as well as wrappers for the 5. camera (Wu & Smyth, Nucleic Acid Res, 2012) 6. mroast and romer (Wu et al, Bioinformatics, 2010) functions from the limma package and 7. wraps the gsea method from the mgsa package (Bauer et al, NAR, 2010). All methods return CMAPResult objects, an S4 class inheriting from AnnotatedDataFrame, containing enrichment statistics as well as annotation data and providing simple high-level summary plots. biocViews: Microarray, Software, Pathways, Annotation Author: Thomas Sandmann , Richard Bourgon and Sarah Kummerfeld Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAP_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gCMAP_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gCMAP_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gCMAP_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gCMAP_1.8.0.tgz vignettes: vignettes/gCMAP/inst/doc/diffExprAnalysis.pdf, vignettes/gCMAP/inst/doc/gCMAP.pdf vignetteTitles: Creating reference datasets, gCMAP classes and methods hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gCMAP/inst/doc/diffExprAnalysis.R, vignettes/gCMAP/inst/doc/gCMAP.R dependsOnMe: gCMAPWeb Package: gCMAPWeb Version: 1.4.0 Depends: brew, gCMAP (>= 1.3.0), R (>= 2.15.0), yaml, Rook Imports: Biobase, annotate, AnnotationDbi, BiocGenerics, brew, graphics, grDevices, GSEABase, hwriter, IRanges, methods, parallel, stats, utils Suggests: org.Hs.eg.db, org.Mm.eg.db, ArrayExpress, affy, hgfocus.db, ArrayExpress, hgu133a.db, mgug4104a.db, RUnit Enhances: bigmemory, bigmemoryExtras License: Artistic-2.0 MD5sum: 99debdfbb245950b359d5f2eb97c93b0 NeedsCompilation: no Title: A web interface for gene-set enrichment analyses Description: The gCMAPWeb R package provides a graphical user interface for the gCMAP package. gCMAPWeb uses the Rook package and can be used either on a local machine, leveraging R's internal web server, or run on a dedicated rApache web server installation. gCMAPWeb allows users to search their own data sources and instructions to generate reference datasets from public repositories are included with the package. The package supports three common types of analyses, specifically queries with 1. one or two sets of query gene identifiers, whose members are expected to show changes in gene expression in a consistent direction. For example, an up-regulated gene set might contain genes activated by a transcription factor, a down-regulated geneset targets repressed by the same factor. 2. a single set of query gene identifiers, whose members are expected to show divergent differential expression (non-directional query). For example, members of a particular signaling pathway, some of which may be up- some down-regulated in response to a stimulus. 3. a query with the complete results of a differential expression profiling experiment. For example, gene identifiers and z-scores from a previous perturbation experiment. gCMAPWeb accepts three types of identifiers: EntreIds, gene Symbols and microarray probe ids and can be configured to work with any species supported by Bioconductor. For each query submission, significantly similar reference datasets will be identified and reported in graphical and tabular form. biocViews: GUI, GeneSetEnrichment, Visualization Author: Thomas Sandmann Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAPWeb_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gCMAPWeb_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gCMAPWeb_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gCMAPWeb_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gCMAPWeb_1.4.0.tgz vignettes: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.pdf, vignettes/gCMAPWeb/inst/doc/referenceDatasets.pdf vignetteTitles: gCMAPWeb configuration, Recreating the Broad Connectivity Map v1 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.R, vignettes/gCMAPWeb/inst/doc/referenceDatasets.R Package: gcrma Version: 2.36.0 Depends: R (>= 2.6.0), affy (>= 1.23.2), graphics, methods, stats, utils Imports: Biobase, affy (>= 1.23.2), affyio (>= 1.13.3), XVector, Biostrings (>= 2.11.32), splines, BiocInstaller Suggests: affydata, tools, splines, hgu95av2cdf, hgu95av2probe License: LGPL Archs: i386, x64 MD5sum: 83670f84d95af4c514aef8453b6dab1b NeedsCompilation: yes Title: Background Adjustment Using Sequence Information Description: Background adjustment using sequence information biocViews: Microarray, OneChannel, Preprocessing Author: Jean(ZHIJIN) Wu, Rafael Irizarry with contributions from James MacDonald Jeff Gentry Maintainer: Z. Wu source.ver: src/contrib/gcrma_2.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gcrma_2.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gcrma_2.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gcrma_2.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gcrma_2.36.0.tgz vignettes: vignettes/gcrma/inst/doc/gcrma2.0.pdf vignetteTitles: gcrma1.2 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gcrma/inst/doc/gcrma2.0.R dependsOnMe: affyILM, affylmGUI, affyPLM, bgx, maskBAD, simpleaffy, webbioc importsMe: affycoretools, simpleaffy, virtualArray suggestsMe: AffyExpress, ArrayTools, BiocCaseStudies, panp Package: genArise Version: 1.40.0 Depends: R (>= 1.7.1), locfit, tkrplot, methods Imports: graphics, grDevices, methods, stats, tcltk, utils, xtable License: file LICENSE License_restricts_use: yes MD5sum: a7e2621a4436d2fd49cd5cf416a2f319 NeedsCompilation: no Title: Microarray Analysis tool Description: genArise is an easy to use tool for dual color microarray data. Its GUI-Tk based environment let any non-experienced user performs a basic, but not simple, data analysis just following a wizard. In addition it provides some tools for the developer. biocViews: Microarray, TwoChannel, Preprocessing Author: Ana Patricia Gomez Mayen ,\\ Gustavo Corral Guille , \\ Lina Riego Ruiz ,\\ Gerardo Coello Coutino Maintainer: IFC Development Team URL: http://www.ifc.unam.mx/genarise source.ver: src/contrib/genArise_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/genArise_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/genArise_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/genArise_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genArise_1.40.0.tgz vignettes: vignettes/genArise/inst/doc/genArise.pdf vignetteTitles: genAriseGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/genArise/inst/doc/genArise.R Package: GeneAnswers Version: 2.6.2 Depends: R (>= 3.0.0), igraph, RCurl, annotate, Biobase (>= 1.12.0), methods, XML, RSQLite, MASS, Heatplus, RColorBrewer Imports: RBGL, annotate Suggests: GO.db, KEGG.db, reactome.db, biomaRt, AnnotationDbi, org.Hs.eg.db, org.Rn.eg.db, org.Mm.eg.db, org.Dm.eg.db, graph License: LGPL (>= 2) MD5sum: 9b0365b530f516213a55aa8328fd644a NeedsCompilation: no Title: Integrated Interpretation of Genes Description: GeneAnswers provides an integrated tool for biological or medical interpretation of the given one or more groups of genes by means of statistical test. biocViews: Infrastructure, DataRepresentation, Visualization, GraphsAndNetworks Author: Gang Feng, Pan Du, Tian Xia, Warren Kibbe and Simon Lin Maintainer: Gang Feng , Pan Du and Tian Xia source.ver: src/contrib/GeneAnswers_2.6.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneAnswers_2.6.2.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneAnswers_2.6.2.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneAnswers_2.6.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneAnswers_2.6.2.tgz vignettes: vignettes/GeneAnswers/inst/doc/geneAnswers.pdf vignetteTitles: GeneAnswers hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneAnswers/inst/doc/geneAnswers.R Package: GENE.E Version: 1.4.1 Depends: R (>= 2.7.0), rhdf5 (>= 2.8.0), RCurl (>= 1.6-6) Imports: rhdf5, RCurl Suggests: RUnit, BiocGenerics, knitr, golubEsets (>= 1.0) License: GPL-2 MD5sum: 357db0a3581ba96013e925816410740d NeedsCompilation: no Title: Interact with GENE-E from R Description: Interactive exploration of matrices in GENE-E. biocViews: ThirdPartyClient Author: Joshua Gould Maintainer: Joshua Gould URL: http://www.broadinstitute.org/cancer/software/GENE-E SystemRequirements: GENE-E software. VignetteBuilder: knitr source.ver: src/contrib/GENE.E_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GENE.E_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GENE.E_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GENE.E_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GENE.E_1.4.1.tgz vignettes: vignettes/GENE.E/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GENE.E/inst/doc/GENE.E-vignette.R htmlDocs: vignettes/GENE.E/inst/doc/GENE.E-vignette.html htmlTitles: "GENE.E Overview" Package: GeneExpressionSignature Version: 1.10.0 Depends: R (>= 2.13), Biobase, PGSEA Suggests: apcluster,GEOquery License: GPL-2 MD5sum: 130206ff3f88fdf7a6e7ddf2ca274147 NeedsCompilation: no Title: Gene Expression Signature based Similarity Metric Description: This package gives the implementations of the gene expression signature and its distance to each. Gene expression signature is represented as a list of genes whose expression is correlated with a biological state of interest. And its distance is defined using a nonparametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov statistic. Gene expression signature and its distance can be used to detect similarities among the signatures of drugs, diseases, and biological states of interest. biocViews: GeneExpression Author: Yang Cao Maintainer: Yang Cao , Fei Li ,Lu Han source.ver: src/contrib/GeneExpressionSignature_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneExpressionSignature_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneExpressionSignature_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneExpressionSignature_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneExpressionSignature_1.10.0.tgz vignettes: vignettes/GeneExpressionSignature/inst/doc/GeneExpressionSignature.pdf vignetteTitles: GeneExpressionSignature hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: genefilter Version: 1.46.1 Imports: AnnotationDbi, annotate (>= 1.13.7), Biobase (>= 1.99.10), graphics, methods, stats, survival Suggests: Biobase (>= 1.99.10), class, hgu95av2.db, methods, tkWidgets, ALL, ROC, DESeq, pasilla License: Artistic-2.0 Archs: i386, x64 MD5sum: 4b4e0e82045422f1e80d6c99a8c8b5e7 NeedsCompilation: yes Title: genefilter: methods for filtering genes from microarray experiments Description: Some basic functions for filtering genes biocViews: Microarray Author: R. Gentleman, V. Carey, W. Huber, F. Hahne Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/genefilter_1.46.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/genefilter_1.46.1.zip win64.binary.ver: bin/windows64/contrib/3.1/genefilter_1.46.1.zip mac.binary.ver: bin/macosx/contrib/3.1/genefilter_1.46.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genefilter_1.46.1.tgz vignettes: vignettes/genefilter/inst/doc/howtogenefilter.pdf, vignettes/genefilter/inst/doc/howtogenefinder.pdf, vignettes/genefilter/inst/doc/independent_filtering.pdf, vignettes/genefilter/inst/doc/independent_filtering_plots.pdf vignetteTitles: Using the genefilter function to filter genes from a microarray dataset, How to find genes whose expression profile is similar to that of specified genes, Diagnostics for independent filtering, Additional plots for: Independent filtering increases power for detecting differentially expressed genes,, Bourgon et al.,, PNAS (2010) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genefilter/inst/doc/howtogenefilter.R, vignettes/genefilter/inst/doc/howtogenefinder.R, vignettes/genefilter/inst/doc/independent_filtering_plots.R, vignettes/genefilter/inst/doc/independent_filtering.R dependsOnMe: a4Base, cellHTS, cellHTS2, charm, CNTools, GeneMeta, MLInterfaces, simpleaffy importsMe: affycoretools, affyQCReport, annmap, arrayQualityMetrics, Category, DESeq, DESeq2, DEXSeq, eisa, gCMAP, GGBase, GSRI, methyAnalysis, methylumi, minfi, PECA, phenoTest, Ringo, simpleaffy, tilingArray, XDE suggestsMe: AffyExpress, annotate, ArrayTools, BiocCaseStudies, BioNet, Category, categoryCompare, clusterStab, codelink, compcodeR, factDesign, ffpe, GenomicFiles, GOstats, GSEAlm, GSVA, logicFS, lumi, MCRestimate, npGSEA, oligo, oneChannelGUI, phyloseq, pvac, qpgraph, rtracklayer, siggenes, SSPA, topGO, VanillaICE, XDE Package: genefu Version: 1.14.0 Depends: survcomp, mclust, biomaRt, R (>= 2.10) Imports: amap Suggests: GeneMeta, breastCancerVDX, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerUNT, breastCancerNKI, rmeta, Biobase, xtable License: Artistic-2.0 MD5sum: e186455b7272d8ba8f578593aee1df44 NeedsCompilation: no Title: Relevant Functions for Gene Expression Analysis, Especially in Breast Cancer. Description: Description: This package contains functions implementing various tasks usually required by gene expression analysis, especially in breast cancer studies: gene mapping between different microarray platforms, identification of molecular subtypes, implementation of published gene signatures, gene selection, survival analysis, ... biocViews: DifferentialExpression, GeneExpression, Visualization, Clustering, Classification Author: Benjamin Haibe-Kains, Markus Schroeder, Gianluca Bontempi, Christos Sotiriou, John Quackenbush Maintainer: Benjamin Haibe-Kains , Markus Schroeder URL: http://compbio.dfci.harvard.edu source.ver: src/contrib/genefu_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/genefu_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/genefu_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/genefu_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genefu_1.14.0.tgz vignettes: vignettes/genefu/inst/doc/genefu.pdf vignetteTitles: genefu An Introduction (HowTo) hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genefu/inst/doc/genefu.R Package: GeneGA Version: 1.14.0 Depends: seqinr, hash, methods License: GPL version 2 MD5sum: 4d43dc790dc78a3ab331cdcdd0605ade NeedsCompilation: no Title: Design gene based on both mRNA secondary structure and codon usage bias using Genetic algorithm Description: R based Genetic algorithm for gene expression optimization by considering both mRNA secondary structure and codon usage bias, GeneGA includes the information of highly expressed genes of almost 200 genomes. Meanwhile, Vienna RNA Package is needed to ensure GeneGA to function properly. biocViews: GeneExpression Author: Zhenpeng Li and Haixiu Huang Maintainer: Zhenpeng Li URL: http://www.tbi.univie.ac.at/~ivo/RNA/ source.ver: src/contrib/GeneGA_1.14.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/GeneGA_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneGA_1.14.0.tgz vignettes: vignettes/GeneGA/inst/doc/GeneGA.pdf vignetteTitles: GeneGA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneGA/inst/doc/GeneGA.R Package: GeneMeta Version: 1.36.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), genefilter Imports: methods, Biobase (>= 2.5.5) Suggests: RColorBrewer License: Artistic-2.0 MD5sum: 48b9429650cc0cb88153b948b923cfa4 NeedsCompilation: no Title: MetaAnalysis for High Throughput Experiments Description: A collection of meta-analysis tools for analysing high throughput experimental data biocViews: Sequencing Author: Lara Lusa , R. Gentleman, M. Ruschhaupt Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GeneMeta_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneMeta_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneMeta_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneMeta_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneMeta_1.36.0.tgz vignettes: vignettes/GeneMeta/inst/doc/GeneMeta.pdf vignetteTitles: GeneMeta Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneMeta/inst/doc/GeneMeta.R suggestsMe: genefu, XDE Package: GeneNetworkBuilder Version: 1.6.1 Depends: R (>= 2.15.1), Rcpp (>= 0.9.13), graph Imports: plyr, graph LinkingTo: Rcpp Suggests: RUnit, BiocGenerics, Rgraphviz, XML, RCytoscape, RBGL License: GPL (>= 2) Archs: i386, x64 MD5sum: 01e2c297c36d6441f7179fda3f4b0c5b NeedsCompilation: yes Title: Build Regulatory Network from ChIP-chip/ChIP-seq and Expression Data Description: Appliation for discovering direct or indirect targets of transcription factors using ChIP-chip or ChIP-seq, and microarray or RNA-seq gene expression data. Inputting a list of genes of potential targets of one TF from ChIP-chip or ChIP-seq, and the gene expression results, GeneNetworkBuilder generates a regulatory network of the TF. biocViews: Sequencing, Microarray, GraphAndNetwork Author: Jianhong Ou and Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/GeneNetworkBuilder_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneNetworkBuilder_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneNetworkBuilder_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneNetworkBuilder_1.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneNetworkBuilder_1.6.1.tgz vignettes: vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.pdf vignetteTitles: GeneNetworkBuilder Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneNetworkBuilder/inst/doc/GeneNetworkBuilder.R Package: GeneOverlap Version: 1.0.0 Imports: stats, RColorBrewer, gplots, methods Suggests: RUnit, BiocGenerics, BiocStyle License: GPL-3 MD5sum: 5be2b6992a1489954915ba8558cd196b NeedsCompilation: no Title: Test and visualize gene overlaps Description: Test two sets of gene lists and visualize the results. biocViews: MultipleComparison, Visualization Author: Li Shen, Mount Sinai Maintainer: Li Shen, Mount Sinai URL: http://shenlab-sinai.github.io/shenlab-sinai/ source.ver: src/contrib/GeneOverlap_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneOverlap_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneOverlap_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneOverlap_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneOverlap_1.0.0.tgz vignettes: vignettes/GeneOverlap/inst/doc/GeneOverlap.pdf vignetteTitles: Testing and visualizing gene overlaps with the "GeneOverlap" package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneOverlap/inst/doc/GeneOverlap.R Package: geneplotter Version: 1.42.0 Depends: R (>= 2.10), methods, Biobase, BiocGenerics, lattice, annotate Imports: AnnotationDbi, graphics, grDevices, grid, RColorBrewer, stats, utils Suggests: Rgraphviz, fibroEset, hgu95av2.db, hu6800.db, hgu133a.db License: Artistic-2.0 MD5sum: 456d94044f57a6dab466f0f922626f40 NeedsCompilation: no Title: Graphics related functions for Bioconductor Description: Functions for plotting genomic data biocViews: Visualization Author: R. Gentleman, Biocore Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/geneplotter_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/geneplotter_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/geneplotter_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/geneplotter_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/geneplotter_1.42.0.tgz vignettes: vignettes/geneplotter/inst/doc/byChroms.pdf, vignettes/geneplotter/inst/doc/visualize.pdf vignetteTitles: How to assemble a chromLocation object, Visualization of Microarray Data hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geneplotter/inst/doc/byChroms.R, vignettes/geneplotter/inst/doc/visualize.R dependsOnMe: HMMcopy importsMe: biocGraph, DESeq, DESeq2, DEXSeq, flowQ, IsoGeneGUI, MethylSeekR, RNAinteract, RNAither suggestsMe: BiocCaseStudies, biocGraph, Category, GOstats Package: geneRecommender Version: 1.36.0 Depends: R (>= 1.8.0), Biobase (>= 1.4.22), methods Imports: Biobase, methods, stats License: GPL (>= 2) MD5sum: be3752d69fb6160ef734b19a41ca94e1 NeedsCompilation: no Title: A gene recommender algorithm to identify genes coexpressed with a query set of genes Description: This package contains a targeted clustering algorithm for the analysis of microarray data. The algorithm can aid in the discovery of new genes with similar functions to a given list of genes already known to have closely related functions. biocViews: Microarray, Clustering Author: Gregory J. Hather , with contributions from Art B. Owen and Terence P. Speed Maintainer: Greg Hather source.ver: src/contrib/geneRecommender_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/geneRecommender_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/geneRecommender_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/geneRecommender_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/geneRecommender_1.36.0.tgz vignettes: vignettes/geneRecommender/inst/doc/geneRecommender.pdf vignetteTitles: Using the geneRecommender Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geneRecommender/inst/doc/geneRecommender.R Package: GeneRegionScan Version: 1.20.0 Depends: methods, Biobase (>= 2.5.5), Biostrings Imports: Biobase (>= 2.5.5), affxparser, RColorBrewer, Biostrings Suggests: BSgenome, affy, AnnotationDbi License: GPL (>= 2) MD5sum: d144dd46f799dfcf662df7cf161cf096 NeedsCompilation: no Title: GeneRegionScan Description: A package with focus on analysis of discrete regions of the genome. This package is useful for investigation of one or a few genes using Affymetrix data, since it will extract probe level data using the Affymetrix Power Tools application and wrap these data into a ProbeLevelSet. A ProbeLevelSet directly extends the expressionSet, but includes additional information about the sequence of each probe and the probe set it is derived from. The package includes a number of functions used for plotting these probe level data as a function of location along sequences of mRNA-strands. This can be used for analysis of variable splicing, and is especially well suited for use with exon-array data. biocViews: Microarray, DataImport, SNP, OneChannel, Visualization Author: Lasse Folkersen, Diego Diez Maintainer: Lasse Folkersen source.ver: src/contrib/GeneRegionScan_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneRegionScan_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneRegionScan_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneRegionScan_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneRegionScan_1.20.0.tgz vignettes: vignettes/GeneRegionScan/inst/doc/GeneRegionScan.pdf vignetteTitles: GeneRegionScan hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneRegionScan/inst/doc/GeneRegionScan.R Package: geneRxCluster Version: 1.0.0 Depends: GenomicRanges,IRanges Suggests: RUnit, BiocGenerics License: GPL (>= 2) Archs: i386, x64 MD5sum: 2611cac0d33f09017dc124090764d407 NeedsCompilation: yes Title: gRx Differential Clustering Description: Detect Differential Clustering of Genomic Sites such as gene therapy integrations. The package provides some functions for exploring genomic insertion sites originating from two different sources. Possibly, the two sources are two different gene therapy vectors. Vectors are preferred that target sensitive regions less frequently, motivating the search for localized clusters of insertions and comparison of the clusters formed by integration of different vectors. Scan statistics allow the discovery of spatial differences in clustering and calculation of False Discovery Rates (FDRs) providing statistical methods for comparing retroviral vectors. A scan statistic for comparing two vectors using multiple window widths to detect clustering differentials and compute FDRs is implemented here. biocViews: Sequencing, Clustering, Genetics Author: Charles Berry Maintainer: Charles Berry source.ver: src/contrib/geneRxCluster_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/geneRxCluster_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/geneRxCluster_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/geneRxCluster_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/geneRxCluster_1.0.0.tgz vignettes: vignettes/geneRxCluster/inst/doc/tutorial.pdf vignetteTitles: Using geneRxCluster hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geneRxCluster/inst/doc/tutorial.R Package: GeneSelectMMD Version: 2.8.1 Depends: R (>= 2.13.2), Biobase Imports: Biobase, MASS, graphics, stats, survival, limma Suggests: ALL License: GPL (>= 2) Archs: i386, x64 MD5sum: 4e19c6317523f525d13dd24381cbce58 NeedsCompilation: yes Title: Gene selection based on the marginal distributions of gene profiles that characterized by a mixture of three-component multivariate distributions Description: Gene selection based on a mixture of marginal distributions biocViews: DifferentialExpression Author: Jarrett Morrow , Weiliang Qiu , Wenqing He , Xiaogang Wang , Ross Lazarus . Maintainer: Weiliang Qiu source.ver: src/contrib/GeneSelectMMD_2.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneSelectMMD_2.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneSelectMMD_2.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneSelectMMD_2.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneSelectMMD_2.8.1.tgz vignettes: vignettes/GeneSelectMMD/inst/doc/gsMMD.pdf vignetteTitles: Gene Selection based on a mixture of marginal distributions hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneSelectMMD/inst/doc/gsMMD.R Package: GeneSelector Version: 2.14.0 Depends: R (>= 2.5.1), methods, stats, Biobase Imports: multtest, siggenes, samr, limma Suggests: multtest, siggenes, samr, limma License: GPL (>= 2) Archs: i386, x64 MD5sum: c83faa8b3650faeafd238608ffb8fcaa NeedsCompilation: yes Title: Stability and Aggregation of ranked gene lists Description: The term 'GeneSelector' refers to a filter selecting those genes which are consistently identified as differentially expressed using various statistical procedures. 'Selected' genes are those present at the top of the list in various ranking methods (currently 14). In addition, the stability of the findings can be taken into account in the final ranking by examining perturbed versions of the original data set, e.g. by leaving samples, swapping class labels, generating bootstrap replicates or adding noise. Given multiple ranked lists, one can use aggregation methods in order to find a synthesis. biocViews: StatisticalMethod, DifferentialExpression Author: Martin Slawski , Anne-Laure Boulesteix . Maintainer: Martin Slawski source.ver: src/contrib/GeneSelector_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneSelector_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneSelector_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneSelector_2.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneSelector_2.14.0.tgz vignettes: vignettes/GeneSelector/inst/doc/GeneSelector.pdf vignetteTitles: GeneSelector.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneSelector/inst/doc/GeneSelector.R Package: geNetClassifier Version: 1.4.0 Depends: R (>= 2.10.1), Biobase (>= 2.5.5), EBarrays, minet, methods Imports: e1071, ipred, graphics Suggests: leukemiasEset, RUnit, BiocGenerics Enhances: RColorBrewer, igraph License: GPL (>= 2) MD5sum: bb0a3526e774ede08e18b25ff40fbacb NeedsCompilation: no Title: classify diseases and build associated gene networks using gene expression profiles Description: Comprehensive package to automatically train a multi-class SVM classifier based on gene expression data. Provides transparent selection of gene markers, their coexpression networks, and an interface to query the classifier. biocViews: Classification, Microarray, GeneExpression, Leukemia, Cancer Author: Sara Aibar, Celia Fontanillo and Javier De Las Rivas. Bioinformatics and Functional Genomics Group. Cancer Research Center (CiC-IBMCC, CSIC/USAL). Salamanca. Spain. Maintainer: Sara Aibar URL: http://bioinfow.dep.usal.es/ source.ver: src/contrib/geNetClassifier_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/geNetClassifier_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/geNetClassifier_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/geNetClassifier_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/geNetClassifier_1.4.0.tgz vignettes: vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.pdf vignetteTitles: geNetClassifier-vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.R Package: GeneticsDesign Version: 1.32.0 Imports: gmodels, graphics, gtools (>= 2.4.0), mvtnorm, stats License: GPL-2 MD5sum: 2241ff6e21cd604c2345e800030507e9 NeedsCompilation: no Title: Functions for designing genetics studies Description: This package contains functions useful for designing genetics studies, including power and sample-size calculations. biocViews: Genetics Author: Gregory Warnes David Duffy , Michael Man Weiliang Qiu Ross Lazarus Maintainer: The R Genetics Project source.ver: src/contrib/GeneticsDesign_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneticsDesign_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneticsDesign_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneticsDesign_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GeneticsDesign_1.32.0.tgz vignettes: vignettes/GeneticsDesign/inst/doc/GPC.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GeneticsDesign/inst/doc/GPC.R Package: GeneticsPed Version: 1.26.0 Depends: R (>= 2.4.0), gdata (>= 2.3.0), genetics (>= 1.3.0), MASS Suggests: RUnit, gtools License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: e3610c37688dd8eaff7af157ab538dfb NeedsCompilation: yes Title: Pedigree and genetic relationship functions Description: Classes and methods for handling pedigree data. It also includes functions to calculate genetic relationship measures as relationship and inbreeding coefficients and other utilities. Note that package is not yet stable. Use it with care! biocViews: Genetics Author: Gregor Gorjanc and David A. Henderson , with code contributions by Brian Kinghorn and Andrew Percy (see file COPYING) Maintainer: David Henderson URL: http://rgenetics.org source.ver: src/contrib/GeneticsPed_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GeneticsPed_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GeneticsPed_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GeneticsPed_1.26.0.tgz vignettes: vignettes/GeneticsPed/inst/doc/geneticRelatedness.pdf, vignettes/GeneticsPed/inst/doc/pedigreeHandling.pdf, vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.pdf vignetteTitles: Calculation of genetic relatedness/relationship between individuals in the pedigree, Pedigree handling, Quantitative genetic (animal) model example in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GeneticsPed/inst/doc/geneticRelatedness.R, vignettes/GeneticsPed/inst/doc/pedigreeHandling.R, vignettes/GeneticsPed/inst/doc/quanGenAnimalModel.R Package: genoCN Version: 1.16.0 Imports: graphics, stats, utils License: GPL (>=2) Archs: i386, x64 MD5sum: 66864ace2d9ae29005c65c81f0a4e3f6 NeedsCompilation: yes Title: genotyping and copy number study tools Description: Simultaneous identification of copy number states and genotype calls for regions of either copy number variations or copy number aberrations biocViews: Microarray, Genetics Author: Wei Sun and ZhengZheng Tang Maintainer: Wei Sun source.ver: src/contrib/genoCN_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/genoCN_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/genoCN_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/genoCN_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genoCN_1.16.0.tgz vignettes: vignettes/genoCN/inst/doc/genoCN.pdf vignetteTitles: add stuff hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genoCN/inst/doc/genoCN.R Package: GenomeGraphs Version: 1.24.0 Depends: R (>= 2.10), methods, biomaRt, grid License: Artistic-2.0 MD5sum: 283281a723234a09665b87b4ed6e2bc4 NeedsCompilation: no Title: Plotting genomic information from Ensembl Description: Genomic data analyses requires integrated visualization of known genomic information and new experimental data. GenomeGraphs uses the biomaRt package to perform live annotation queries to Ensembl and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. Another strength of GenomeGraphs is to plot different data types such as array CGH, gene expression, sequencing and other data, together in one plot using the same genome coordinate system. biocViews: Visualization, Microarray Author: Steffen Durinck , James Bullard Maintainer: Steffen Durinck source.ver: src/contrib/GenomeGraphs_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomeGraphs_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomeGraphs_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomeGraphs_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomeGraphs_1.24.0.tgz vignettes: vignettes/GenomeGraphs/inst/doc/GenomeGraphs.pdf vignetteTitles: The GenomeGraphs users guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomeGraphs/inst/doc/GenomeGraphs.R dependsOnMe: Genominator, waveTiling suggestsMe: rMAT, triplex Package: GenomeInfoDb Version: 1.0.2 Depends: R (>= 3.1) Suggests: BiocGenerics, IRanges, BSgenome, BSgenome.Scerevisiae.UCSC.sacCer2, BSgenome.Hsapiens.NCBI.GRCh38, TxDb.Dmelanogaster.UCSC.dm3.ensGene, RUnit, BiocStyle, knitr License: Artistic-2.0 MD5sum: 82f4b1fefb6286ec3e31122dc561513c NeedsCompilation: no Title: Utilities for manipulating chromosome and other 'seqname' identifiers Description: The Seqnames package contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., "chr1" versus "1"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order. biocViews: Genetics, DataRepresentation, Annotation Author: Sonali Arora, Martin Morgan, Marc Carlson, H. Pages Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/GenomeInfoDb_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomeInfoDb_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomeInfoDb_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomeInfoDb_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomeInfoDb_1.0.2.tgz vignettes: vignettes/GenomeInfoDb/inst/doc/Accept-organism-for-GenomeInfoDb.pdf, vignettes/GenomeInfoDb/inst/doc/GenomeInfoDb.pdf vignetteTitles: GenomeInfoDb: Submitting your organism to GenomeInfoDb, GenomeInfoDb :Introduction to GenomeInfoDb hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomeInfoDb/inst/doc/GenomeInfoDb.R, vignettes/GenomeInfoDb/inst/doc/Seqnames.R dependsOnMe: AnnotationDbi, GenomicRanges, Rsamtools importsMe: GenomicFeatures, SomaticSignatures, VariantTools suggestsMe: BSgenome, QDNAseq Package: genomeIntervals Version: 1.20.1 Depends: R (>= 2.15.0), methods, intervals (>= 0.14.0), BiocGenerics (>= 0.10.0) License: Artistic-2.0 MD5sum: 10a092f5d2df223cf5e8646ab36995ab NeedsCompilation: no Title: Operations on genomic intervals Description: This package defines classes for representing genomic intervals and provides functions and methods for working with these. Note: The package provides the basic infrastructure for and is enhanced by the package 'girafe'. biocViews: DataImport, Infrastructure, Genetics Author: Julien Gagneur , Joern Toedling, Richard Bourgon, Nicolas Delhomme Maintainer: Julien Gagneur source.ver: src/contrib/genomeIntervals_1.20.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/genomeIntervals_1.20.1.zip win64.binary.ver: bin/windows64/contrib/3.1/genomeIntervals_1.20.1.zip mac.binary.ver: bin/macosx/contrib/3.1/genomeIntervals_1.20.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genomeIntervals_1.20.1.tgz vignettes: vignettes/genomeIntervals/inst/doc/genomeIntervals.pdf vignetteTitles: Overview of the genomeIntervals package. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genomeIntervals/inst/doc/genomeIntervals.R dependsOnMe: girafe importsMe: easyRNASeq Package: genomes Version: 2.10.0 Depends: R (>= 2.11), XML, RCurl, GenomicRanges, IRanges, Biostrings License: Artistic-2.0 MD5sum: a9f8dfbc2d98389eecbbc294bd595e9b NeedsCompilation: no Title: Genome sequencing project metadata Description: Collects genome sequencing project data from NCBI and the ENA. biocViews: Annotation, Genetics Author: Chris Stubben Maintainer: Chris Stubben source.ver: src/contrib/genomes_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/genomes_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/genomes_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/genomes_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genomes_2.10.0.tgz vignettes: vignettes/genomes/inst/doc/genome-tables.pdf vignetteTitles: Introduction to genome projects hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genomes/inst/doc/genome-tables.R Package: GenomicAlignments Version: 1.0.6 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.7.7), IRanges (>= 1.21.25), GenomicRanges (>= 1.15.32), Biostrings (>= 2.31.10), Rsamtools (>= 1.15.26), BSgenome (>= 1.31.12) Imports: methods, stats, BiocGenerics, IRanges, GenomicRanges, Biostrings, Rsamtools, BiocParallel LinkingTo: IRanges Suggests: rtracklayer, GenomicFeatures, RNAseqData.HNRNPC.bam.chr14, pasillaBamSubset, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Dmelanogaster.UCSC.dm3.ensGene, BSgenome.Dmelanogaster.UCSC.dm3, BSgenome.Hsapiens.UCSC.hg19, DESeq, edgeR, RUnit, BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: a5c186ec5981de85b5bad15aa962f5f9 NeedsCompilation: yes Title: Representation and manipulation of short genomic alignments Description: Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working with the nucleotide content of the alignments. biocViews: Genetics, Infrastructure, DataImport, Sequencing, RNASeq, SNP Author: Herv\'e Pag\`es, Valerie Obenchain, Martin Morgan Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicAlignments_1.0.6.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomicAlignments_1.0.6.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomicAlignments_1.0.6.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomicAlignments_1.0.6.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomicAlignments_1.0.6.tgz vignettes: vignettes/GenomicAlignments/inst/doc/OverlapEncodings.pdf, vignettes/GenomicAlignments/inst/doc/summarizeOverlaps.pdf, vignettes/GenomicAlignments/inst/doc/WorkingWithAlignedNucleotides.pdf vignetteTitles: Overlap encodings, Counting reads with summarizeOverlaps, Working with aligned nucleotides hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicAlignments/inst/doc/OverlapEncodings.R, vignettes/GenomicAlignments/inst/doc/summarizeOverlaps.R, vignettes/GenomicAlignments/inst/doc/WorkingWithAlignedNucleotides.R dependsOnMe: AllelicImbalance, chimera, DiffBind, prebs, RIPSeeker, rnaSeqMap, ShortRead, SplicingGraphs importsMe: biovizBase, ChIPQC, CNEr, customProDB, easyRNASeq, GenomicFiles, ggbio, gmapR, Gviz, HTSeqGenie, PICS, QuasR, Repitools, roar, rtracklayer, SplicingGraphs, trackViewer suggestsMe: DESeq2, gage, GenomicRanges, Rsamtools, Streamer Package: GenomicFeatures Version: 1.16.3 Depends: BiocGenerics (>= 0.1.0), IRanges (>= 1.17.13), GenomicRanges (>= 1.15.25), AnnotationDbi (>= 1.25.7) Imports: methods, DBI (>= 0.2-5), RSQLite (>= 0.8-1), Biostrings (>= 2.23.2), rtracklayer (>= 1.15.1), biomaRt (>= 2.17.1), RCurl, utils, Biobase (>= 2.15.1), GenomeInfoDb Suggests: org.Mm.eg.db, BSgenome, BSgenome.Hsapiens.UCSC.hg18 (>= 1.3.14), BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.17), BSgenome.Celegans.UCSC.ce2, BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.17), mirbase.db, FDb.UCSC.tRNAs, TxDb.Hsapiens.UCSC.hg18.knownGene, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Dmelanogaster.UCSC.dm3.ensGene (>= 2.7.1), Rsamtools, pasillaBamSubset (>= 0.0.5), seqnames.db, RUnit, BiocStyle, knitr License: Artistic-2.0 MD5sum: f9add92a7d35899508620c35daf3e504 NeedsCompilation: no Title: Tools for making and manipulating transcript centric annotations Description: A set of tools and methods for making and manipulating transcript centric annotations. With these tools the user can easily download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database (more sources will be supported in the future). This information is then stored in a local database that keeps track of the relationship between transcripts, exons, cds and genes. Flexible methods are provided for extracting the desired features in a convenient format. biocViews: Genetics, Infrastructure, Annotation, Sequencing Author: M. Carlson, H. Pages, P. Aboyoun, S. Falcon, M. Morgan, D. Sarkar, M. Lawrence Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/GenomicFeatures_1.16.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomicFeatures_1.16.3.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomicFeatures_1.16.3.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomicFeatures_1.16.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomicFeatures_1.16.3.tgz vignettes: vignettes/GenomicFeatures/inst/doc/GenomicFeatures.pdf vignetteTitles: Making and Utilizing TranscriptDb Objects hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicFeatures/inst/doc/GenomicFeatures.R dependsOnMe: exomePeak, OrganismDbi, SplicingGraphs importsMe: AllelicImbalance, biovizBase, casper, ChIPpeakAnno, ChIPseeker, CompGO, customProDB, ggbio, gmapR, Gviz, HTSeqGenie, lumi, MEDIPS, methyAnalysis, QuasR, SplicingGraphs, trackViewer, VariantAnnotation, VariantTools suggestsMe: biomvRCNS, Biostrings, chipseq, DESeq2, DEXSeq, easyRNASeq, GenomicAlignments, GenomicRanges, MiRaGE, RIPSeeker, Rsamtools, ShortRead Package: GenomicFiles Version: 1.0.1 Depends: R (>= 3.1.0), methods, BiocGenerics, BiocParallel, Rsamtools, rtracklayer (>= 1.23.16) Imports: GenomicAlignments Suggests: genefilter, deepSNV, BiocStyle, IRanges, RUnit, RNAseqData.HNRNPC.bam.chr14, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: 7ae084abebfb46a2edd5c771dffbe62d NeedsCompilation: no Title: Parallel queries distributed by file or by range Description: This package provides infrastructure for parallel queries distributed 'by file' or 'by range'. User defined map and reduce functions provide added flexibility for data combination and manipulation. biocViews: Infrastructure, DataImport Author: Valerie Obenchain, Michael Love, Martin Morgan Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicFiles_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomicFiles_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomicFiles_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomicFiles_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomicFiles_1.0.1.tgz vignettes: vignettes/GenomicFiles/inst/doc/GenomicFiles.pdf vignetteTitles: Introduction to GenomicFiles hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicFiles/inst/doc/GenomicFiles.R Package: GenomicRanges Version: 1.16.4 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.7.7), IRanges (>= 1.21.33), GenomeInfoDb (>= 0.99.17) Imports: methods, utils, stats, BiocGenerics, IRanges, XVector LinkingTo: IRanges, XVector (>= 0.3.4) Suggests: AnnotationDbi (>= 1.21.1), AnnotationHub, BSgenome, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Scerevisiae.UCSC.sacCer2, Biostrings (>= 2.25.3), Rsamtools (>= 1.13.53), GenomicAlignments, rtracklayer, KEGG.db, KEGGgraph, GenomicFeatures, TxDb.Dmelanogaster.UCSC.dm3.ensGene, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Athaliana.BioMart.plantsmart21, seqnames.db, org.Sc.sgd.db, VariantAnnotation, edgeR, DESeq, DEXSeq, pasilla, pasillaBamSubset, RUnit, digest, BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: 406963a4a54c323940541356b74450ef NeedsCompilation: yes Title: Representation and manipulation of genomic intervals Description: The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyze high-throughput sequencing data (a.k.a. NGS data). The package defines general purpose containers for storing genomic intervals. Specialized containers for representing and manipulating short alignments against a reference genome are defined in the GenomicAlignments package. biocViews: Genetics, Infrastructure, Sequencing, Annotation Author: P. Aboyoun, H. Pages and M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicRanges_1.16.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/GenomicRanges_1.16.4.zip win64.binary.ver: bin/windows64/contrib/3.1/GenomicRanges_1.16.4.zip mac.binary.ver: bin/macosx/contrib/3.1/GenomicRanges_1.16.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GenomicRanges_1.16.4.tgz vignettes: vignettes/GenomicRanges/inst/doc/GenomicRangesHOWTOs.pdf, vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.pdf vignetteTitles: GenomicRanges HOWTOs, An Introduction to GenomicRanges hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GenomicRanges/inst/doc/GenomicRangesHOWTOs.R, vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.R, vignettes/GenomicRanges/inst/doc/GenomicRangesUseCases.R, vignettes/GenomicRanges/inst/doc/OverlapEncodings.R, vignettes/GenomicRanges/inst/doc/summarizeOverlaps.R dependsOnMe: AllelicImbalance, annmap, Basic4Cseq, baySeq, biomvRCNS, BiSeq, BSgenome, bsseq, bumphunter, CAFE, casper, chimera, chipseq, cleanUpdTSeq, cn.mops, COPDSexualDimorphism, CSAR, DASiR, deepSNV, DESeq2, DEXSeq, DiffBind, DMRforPairs, ensemblVEP, epigenomix, epivizr, exomeCopy, fastseg, genomes, GenomicAlignments, GenomicFeatures, genoset, gmapR, GOTHiC, HiTC, htSeqTools, intansv, methyAnalysis, minfi, PING, QuasR, R453Plus1Toolbox, Rcade, rfPred, RIPSeeker, Rsamtools, rSFFreader, RSVSim, rtracklayer, segmentSeq, seqbias, SigFuge, SomatiCA, SplicingGraphs, trackViewer, VariantAnnotation, VariantTools, vtpnet importsMe: AnnotationHub, ArrayExpressHTS, beadarray, BEAT, biovizBase, BiSeq, BSgenome, CAGEr, CexoR, chipenrich, ChIPQC, ChIPseeker, chipseq, ChIPseqR, CNEr, copynumber, customProDB, DNaseR, easyRNASeq, flipflop, FunciSNP, GenomicAlignments, ggbio, GGtools, Gviz, gwascat, h5vc, HTSeqGenie, HTSFilter, lumi, MEDIPS, methyAnalysis, MethylSeekR, MinimumDistance, NarrowPeaks, nucleR, oligoClasses, PICS, prebs, QuasR, Rariant, Repitools, rnaSeqMap, roar, rSFFreader, rtracklayer, segmentSeq, SeqArray, SeqVarTools, ShortRead, SNPchip, SomatiCA, SomaticSignatures, spliceR, SplicingGraphs, TFBSTools, triplex, VanillaICE, VariantFiltering, waveTiling suggestsMe: BiocGenerics, DMRcate, IRanges, metaseqR, methylumi, MiRaGE, NarrowPeaks, QDNAseq, SeqGSEA Package: Genominator Version: 1.18.0 Depends: R (>= 2.10), methods, RSQLite, DBI (>= 0.2-5), BiocGenerics (>= 0.1.0), IRanges, GenomeGraphs Imports: graphics, stats, utils Suggests: biomaRt, ShortRead, yeastRNASeq License: Artistic-2.0 MD5sum: 9d717ed9f6b46e7e29ed957d63574ca7 NeedsCompilation: no Title: Analyze, manage and store genomic data Description: Tools for storing, accessing, analyzing and visualizing genomic data. biocViews: Infrastructure Author: James Bullard, Kasper Daniel Hansen Maintainer: James Bullard source.ver: src/contrib/Genominator_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Genominator_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Genominator_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Genominator_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Genominator_1.18.0.tgz vignettes: vignettes/Genominator/inst/doc/Genominator.pdf, vignettes/Genominator/inst/doc/plotting.pdf, vignettes/Genominator/inst/doc/withShortRead.pdf vignetteTitles: The Genominator User Guide, Plotting with Genominator, Working with the ShortRead Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Genominator/inst/doc/Genominator.R, vignettes/Genominator/inst/doc/plotting.R, vignettes/Genominator/inst/doc/withShortRead.R suggestsMe: oneChannelGUI Package: genoset Version: 1.16.2 Depends: R (>= 2.10), BiocGenerics (>= 0.1.6), Biobase (>= 2.15.1), IRanges, GenomicRanges Imports: methods, graphics Suggests: RUnit, DNAcopy, stats, BSgenome, Biostrings Enhances: parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: df576860d50b8c512853471781c0abfc NeedsCompilation: yes Title: Provides classes similar to ExpressionSet for copy number analysis Description: Load, manipulate, and plot copynumber and BAF data. GenoSet class extends eSet by adding a "locData" slot for a RangedData or GRanegs object. This object contains feature genome location data and provides for efficient subsetting on genome location. CNSet and BAFSet extend GenoSet and require assayData matrices for Copy Number (cn) or Log-R Ratio (lrr) and B-Allele Frequency (baf) data. Implements and provides convenience functions for processing of copy number and B-Allele Frequency data. biocViews: Infrastructure, DataRepresentation, Microarray, SNP, CopyNumberVariation Author: Peter M. Haverty Maintainer: Peter M. Haverty source.ver: src/contrib/genoset_1.16.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/genoset_1.16.2.zip win64.binary.ver: bin/windows64/contrib/3.1/genoset_1.16.2.zip mac.binary.ver: bin/macosx/contrib/3.1/genoset_1.16.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/genoset_1.16.2.tgz vignettes: vignettes/genoset/inst/doc/genoset.pdf vignetteTitles: genoset hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/genoset/inst/doc/genoset.R dependsOnMe: VegaMC importsMe: methyAnalysis Package: GEOmetadb Version: 1.24.0 Depends: GEOquery,RSQLite License: Artistic-2.0 MD5sum: 043e3f31d9b88de1e4e60f3b7e0734af NeedsCompilation: no Title: A compilation of metadata from NCBI GEO Description: The NCBI Gene Expression Omnibus (GEO) represents the largest public repository of microarray data. However, finding data of interest can be challenging using current tools. GEOmetadb is an attempt to make access to the metadata associated with samples, platforms, and datasets much more feasible. This is accomplished by parsing all the NCBI GEO metadata into a SQLite database that can be stored and queried locally. GEOmetadb is simply a thin wrapper around the SQLite database along with associated documentation. Finally, the SQLite database is updated regularly as new data is added to GEO and can be downloaded at will for the most up-to-date metadata. GEOmetadb paper: http://bioinformatics.oxfordjournals.org/cgi/content/short/24/23/2798 . biocViews: Infrastructure Author: Jack Zhu and Sean Davis Maintainer: Jack Zhu URL: http://gbnci.abcc.ncifcrf.gov/geo/ source.ver: src/contrib/GEOmetadb_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GEOmetadb_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GEOmetadb_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GEOmetadb_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GEOmetadb_1.24.0.tgz vignettes: vignettes/GEOmetadb/inst/doc/GEOmetadb.pdf vignetteTitles: GEOmetadb hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOmetadb/inst/doc/GEOmetadb.R Package: GEOquery Version: 2.30.1 Depends: methods, Biobase Imports: XML, RCurl Suggests: limma License: GPL-2 MD5sum: d9404d31c641515160c3e0590398883a NeedsCompilation: no Title: Get data from NCBI Gene Expression Omnibus (GEO) Description: The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor. biocViews: Microarray, DataImport, OneChannel, TwoChannel, SAGE Author: Sean Davis Maintainer: Sean Davis URL: https://github.com/seandavi/GEOquery source.ver: src/contrib/GEOquery_2.30.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GEOquery_2.30.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GEOquery_2.30.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GEOquery_2.30.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GEOquery_2.30.1.tgz vignettes: vignettes/GEOquery/inst/doc/GEOquery.pdf vignetteTitles: GEOquery hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOquery/inst/doc/GEOquery.R dependsOnMe: DrugVsDisease, SCAN.UPC importsMe: ChIPXpress, SRAdb, virtualArray suggestsMe: dyebias, ELBOW, PGSEA, TargetScore Package: GEOsubmission Version: 1.16.0 Imports: affy, Biobase, utils License: GPL (>= 2) MD5sum: 320002da29dd9c80bd398d570880715d NeedsCompilation: no Title: Prepares microarray data for submission to GEO Description: Helps to easily submit a microarray dataset and the associated sample information to GEO by preparing a single file for upload (direct deposit). biocViews: Microarray Author: Alexandre Kuhn Maintainer: Alexandre Kuhn source.ver: src/contrib/GEOsubmission_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GEOsubmission_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GEOsubmission_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GEOsubmission_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GEOsubmission_1.16.0.tgz vignettes: vignettes/GEOsubmission/inst/doc/GEOsubmission.pdf vignetteTitles: GEOsubmission Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOsubmission/inst/doc/GEOsubmission.R Package: GEWIST Version: 1.8.0 Depends: R (>= 2.10), car License: GPL-2 MD5sum: f75d0f0ec1ea617dd4b0f49a6ccef182 NeedsCompilation: no Title: Gene Environment Wide Interaction Search Threshold Description: This 'GEWIST' package provides statistical tools to efficiently optimize SNP prioritization for gene-gene and gene-environment interactions. biocViews: MultipleComparison, Genetics Author: Wei Q. Deng, Guillaume Pare Maintainer: Wei Q. Deng source.ver: src/contrib/GEWIST_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GEWIST_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GEWIST_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GEWIST_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GEWIST_1.8.0.tgz vignettes: vignettes/GEWIST/inst/doc/GEWIST.pdf vignetteTitles: GEWIST.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEWIST/inst/doc/GEWIST.R Package: GGBase Version: 3.26.1 Depends: R (>= 2.14), methods, snpStats Imports: limma, genefilter, Biobase, BiocGenerics, Matrix, AnnotationDbi, digest Suggests: GGtools License: Artistic-2.0 MD5sum: 85aa827550f6d2f9b2abd024a6d4b64e NeedsCompilation: no Title: GGBase infrastructure for genetics of gene expression package GGtools Description: infrastructure biocViews: Genetics, Infrastructure Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/GGBase_3.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GGBase_3.26.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GGBase_3.26.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GGBase_3.26.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GGBase_3.26.1.tgz vignettes: vignettes/GGBase/inst/doc/ggbase.pdf vignetteTitles: GGBase -- infrastructure for GGtools,, genetics of gene expression hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GGBase/inst/doc/ggbase.R dependsOnMe: GGtools importsMe: qpgraph Package: ggbio Version: 1.12.10 Depends: methods, BiocGenerics, ggplot2 (>= 1.0.0) Imports: grid, grDevices, graphics, stats, utils, biovizBase(>= 1.12.1), reshape2, gtable, Biobase, IRanges (>= 1.21.19), GenomicRanges (>= 1.13.3), GenomicFeatures, Rsamtools (>= 1.13.1), GenomicAlignments, BSgenome, gridExtra, scales, VariantAnnotation, Hmisc, rtracklayer, Biostrings Suggests: vsn, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, chipseq, TxDb.Mmusculus.UCSC.mm9.knownGene, knitr, BiocStyle, Homo.sapiens License: Artistic-2.0 MD5sum: 822859e50351a2a27cb9f91c4c3cb3f6 NeedsCompilation: no Title: Visualization tools for genomic data. Description: The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries. biocViews: Infrastructure, Visualization Author: Tengfei Yin, Dianne Cook, Michael Lawrence Maintainer: Tengfei Yin URL: http://tengfei.github.com/ggbio/ VignetteBuilder: knitr source.ver: src/contrib/ggbio_1.12.10.tar.gz win.binary.ver: bin/windows/contrib/3.1/ggbio_1.12.10.zip win64.binary.ver: bin/windows64/contrib/3.1/ggbio_1.12.10.zip mac.binary.ver: bin/macosx/contrib/3.1/ggbio_1.12.10.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ggbio_1.12.10.tgz vignettes: vignettes/ggbio/inst/doc/ggbio.pdf vignetteTitles: Part 0: Introduction and quick start hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ggbio/inst/doc/ggbio.R dependsOnMe: CAFE, intansv importsMe: Rariant, ReportingTools, SomaticSignatures suggestsMe: beadarray, gwascat, interactiveDisplay Package: GGtools Version: 5.0.0 Depends: R (>= 2.14), GGBase (>= 3.19.7), data.table Imports: methods, utils, stats, BiocGenerics, snpStats, ff, Rsamtools, AnnotationDbi, Biobase, bit, VariantAnnotation, hexbin, rtracklayer, Gviz, stats4, IRanges, GenomicRanges, iterators, Biostrings, ROCR, biglm Suggests: GGdata, illuminaHumanv1.db, SNPlocs.Hsapiens.dbSNP.20120608, multtest Enhances: MatrixEQTL, Homo.sapiens, foreach, doParallel, gwascat, ggplot2, reshape2 License: Artistic-2.0 MD5sum: 5e7b26427a318dd41907b397b78c0047 NeedsCompilation: no Title: software and data for analyses in genetics of gene expression Description: software and data for analyses in genetics of gene expression and/or DNA methylation biocViews: Genetics, GeneExpression, GeneticVariability, SNP Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/GGtools_5.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GGtools_5.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GGtools_5.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GGtools_5.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GGtools_5.0.0.tgz vignettes: vignettes/GGtools/inst/doc/GGtools.pdf vignetteTitles: GGtools: software for eQTL identification hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GGtools/inst/doc/GGtools.R suggestsMe: GGBase Package: girafe Version: 1.16.1 Depends: R (>= 2.10.0), methods, IRanges (>= 1.3.53), Rsamtools, ShortRead (>= 1.3.21), intervals (>= 0.13.1), genomeIntervals (>= 1.7.3), grid Imports: methods, Biobase, Biostrings, BSgenome, graphics, grDevices, stats, utils, IRanges Suggests: MASS, org.Mm.eg.db, RColorBrewer Enhances: genomeIntervals License: Artistic-2.0 Archs: i386, x64 MD5sum: 1a31ca115449f4ef387a50024eaa62ae NeedsCompilation: yes Title: Genome Intervals and Read Alignments for Functional Exploration Description: The package 'girafe' deals with the genome-level representation of aligned reads from next-generation sequencing data. It contains an object class for enabling a detailed description of genome intervals with aligned reads and functions for comparing, visualising, exporting and working with such intervals and the aligned reads. As such, the package interacts with and provides a link between the packages ShortRead, IRanges and genomeIntervals. biocViews: Sequencing Author: Joern Toedling, with contributions from Constance Ciaudo, Olivier Voinnet, Edith Heard, Emmanuel Barillot, and Wolfgang Huber Maintainer: J. Toedling source.ver: src/contrib/girafe_1.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/girafe_1.16.1.zip win64.binary.ver: bin/windows64/contrib/3.1/girafe_1.16.1.zip mac.binary.ver: bin/macosx/contrib/3.1/girafe_1.16.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/girafe_1.16.1.tgz vignettes: vignettes/girafe/inst/doc/girafe.pdf vignetteTitles: Genome intervals and read alignments for functional exploration hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/girafe/inst/doc/girafe.R Package: GLAD Version: 2.28.1 Depends: R (>= 2.10) Suggests: aws, tcltk License: GPL-2 Archs: i386, x64 MD5sum: 4ed5f84d5410180d31e7271b99ee3d1b NeedsCompilation: yes Title: Gain and Loss Analysis of DNA Description: Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified. biocViews: Microarray, CopyNumberVariation Author: Philippe Hupe Maintainer: Philippe Hupe URL: http://bioinfo.curie.fr SystemRequirements: gsl. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. source.ver: src/contrib/GLAD_2.28.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GLAD_2.28.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GLAD_2.28.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GLAD_2.28.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GLAD_2.28.1.tgz vignettes: vignettes/GLAD/inst/doc/GLAD.pdf vignetteTitles: GLAD hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GLAD/inst/doc/GLAD.R dependsOnMe: ITALICS, MANOR, seqCNA importsMe: ADaCGH2, ITALICS, MANOR, snapCGH Package: GlobalAncova Version: 3.32.0 Depends: methods, corpcor, globaltest Imports: annotate, AnnotationDbi Suggests: Biobase, annotate, GO.db, KEGG.db, golubEsets, hu6800.db, vsn, GSEABase, Rgraphviz License: GPL (>= 2) Archs: i386, x64 MD5sum: 2f9389f2ac06e62c63d49ebb7415c625 NeedsCompilation: yes Title: Calculates a global test for differential gene expression between groups Description: We give the following arguments in support of the GlobalAncova approach: After appropriate normalisation, gene-expression-data appear rather symmetrical and outliers are no real problem, so least squares should be rather robust. ANCOVA with interaction yields saturated data modelling e.g. different means per group and gene. Covariate adjustment can help to correct for possible selection bias. Variance homogeneity and uncorrelated residuals cannot be expected. Application of ordinary least squares gives unbiased, but no longer optimal estimates (Gauss-Markov-Aitken). Therefore, using the classical F-test is inappropriate, due to correlation. The test statistic however mirrors deviations from the null hypothesis. In combination with a permutation approach, empirical significance levels can be approximated. Alternatively, an approximation yields asymptotic p-values. This work was supported by the NGFN grant 01 GR 0459, BMBF, Germany. biocViews: Microarray, OneChannel, DifferentialExpression, Pathways Author: U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel Maintainer: Manuela Hummel source.ver: src/contrib/GlobalAncova_3.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GlobalAncova_3.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GlobalAncova_3.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GlobalAncova_3.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GlobalAncova_3.32.0.tgz vignettes: vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.pdf, vignettes/GlobalAncova/inst/doc/GlobalAncova.pdf vignetteTitles: GlobalAncovaDecomp.pdf, GlobalAncova.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.R, vignettes/GlobalAncova/inst/doc/GlobalAncova.R Package: globaltest Version: 5.18.0 Depends: methods Imports: Biobase, survival, AnnotationDbi, annotate, multtest, graphics Suggests: vsn, golubEsets, KEGG.db, hu6800.db, Rgraphviz, GO.db, lungExpression, org.Hs.eg.db, annotate, Biobase, survival, GSEABase, penalized, gss, MASS, boot, rpart License: GPL (>= 2) MD5sum: dd62bd3870c7b6d55dd34cb1f43799b5 NeedsCompilation: no Title: Testing groups of covariates/features for association with a response variable, with applications to gene set testing Description: The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms. biocViews: Microarray, OneChannel, DifferentialExpression, GO, Pathways Author: Jelle Goeman and Jan Oosting, with contributions by Livio Finos and Aldo Solari Maintainer: Jelle Goeman URL: http://www.msbi.nl/goeman source.ver: src/contrib/globaltest_5.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/globaltest_5.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/globaltest_5.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/globaltest_5.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/globaltest_5.18.0.tgz vignettes: vignettes/globaltest/inst/doc/GlobalTest.pdf vignetteTitles: Global Test hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/globaltest/inst/doc/GlobalTest.R dependsOnMe: GlobalAncova importsMe: BiSeq, SIM suggestsMe: topGO Package: gmapR Version: 1.6.6 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: IRanges, Rsamtools (>= 1.7.4), rtracklayer (>= 1.17.15), GenomicFeatures, Biostrings, VariantAnnotation (>= 1.9.4), tools, Biobase, BSgenome, GenomicAlignments Suggests: RUnit, BSgenome.Dmelanogaster.UCSC.dm3, BSgenome.Scerevisiae.UCSC.sacCer3, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome.Hsapiens.UCSC.hg19, LungCancerLines License: Artistic-2.0 MD5sum: fd842ac473ce7f9c5a0e53adfabbb39e NeedsCompilation: yes Title: Provides convenience methods to work with GMAP and GSNAP from within R Description: GSNAP and GMAP are a pair of tools to align short-read data written by Tom Wu. This package provides convenience methods to work with GMAP and GSNAP from within R. In addition, it provides methods to tally alignment results on a per-nucleotide basis using the bam_tally tool. biocViews: Alignment Author: Cory Barr, Thomas Wu, Michael Lawrence Maintainer: Michael Lawrence source.ver: src/contrib/gmapR_1.6.6.tar.gz vignettes: vignettes/gmapR/inst/doc/gmapR.pdf vignetteTitles: gmapR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gmapR/inst/doc/gmapR.R dependsOnMe: HTSeqGenie importsMe: VariantTools Package: GOFunction Version: 1.12.0 Depends: R (>= 2.11.0), methods, Biobase (>= 2.8.0), graph (>= 1.26.0), Rgraphviz (>= 1.26.0), GO.db (>= 2.4.1), AnnotationDbi (>= 1.10.2), SparseM (>= 0.85) Imports: methods, Biobase, graph, Rgraphviz, GO.db, AnnotationDbi, SparseM License: GPL (>= 2) MD5sum: 0912922dd4c6b5da390e647d6064886f NeedsCompilation: no Title: GO-function: deriving biologcially relevant functions from statistically significant functions Description: The GO-function package provides a tool to address the redundancy that result from the GO structure or multiple annotation genes and derive biologically relevant functions from the statistically significant functions based on some intuitive assumption and statistical testing. biocViews: GO, Pathways, Microarray, GeneSetEnrichment Author: Jing Wang Maintainer: Jing Wang source.ver: src/contrib/GOFunction_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GOFunction_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GOFunction_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GOFunction_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GOFunction_1.12.0.tgz vignettes: vignettes/GOFunction/inst/doc/GOFunction.pdf vignetteTitles: GO-function hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOFunction/inst/doc/GOFunction.R Package: goProfiles Version: 1.26.0 Depends: Biobase, AnnotationDbi, GO.db Suggests: org.Hs.eg.db License: GPL-2 MD5sum: af2956f6e67610ade4266c229a3761af NeedsCompilation: no Title: goProfiles: an R package for the statistical analysis of functional profiles Description: The package implements methods to compare lists of genes based on comparing the corresponding 'functional profiles'. biocViews: Microarray, GO Author: Alex Sanchez, Jordi Ocana and Miquel Salicru Maintainer: Alex Sanchez source.ver: src/contrib/goProfiles_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/goProfiles_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/goProfiles_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/goProfiles_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/goProfiles_1.26.0.tgz vignettes: vignettes/goProfiles/inst/doc/goProfiles.pdf vignetteTitles: goProfiles Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/goProfiles/inst/doc/goProfiles.R Package: GOSemSim Version: 1.22.0 Depends: R (>= 2.10), Rcpp Imports: methods, AnnotationDbi, GO.db, org.Hs.eg.db, Rcpp LinkingTo: Rcpp Suggests: DOSE, clusterProfiler, BiocInstaller, knitr License: GPL-2 Archs: i386, x64 MD5sum: 94b75cbf01b0b45d9fa948be0e860618 NeedsCompilation: yes Title: GO-terms Semantic Similarity Measures Description: Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for estimating GO semantic similarities. Support many species, including Anopheles, Arabidopsis, Bovine, Canine, Chicken, Chimp, Coelicolor, E coli strain K12 and Sakai, Fly, Human, Malaria, Mouse, Pig, Rhesus, Rat, Worm, Xenopus, Yeast, and Zebrafish. biocViews: GO, Clustering, Pathways, Network Author: Guangchuang Yu Maintainer: Guangchuang Yu URL: http://bioinformatics.oxfordjournals.org/content/26/7/976.full VignetteBuilder: knitr source.ver: src/contrib/GOSemSim_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GOSemSim_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GOSemSim_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GOSemSim_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GOSemSim_1.22.0.tgz vignettes: vignettes/GOSemSim/inst/doc/GOSemSim.pdf vignetteTitles: An introduction to GOSemSim hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOSemSim/inst/doc/GOSemSim.R dependsOnMe: tRanslatome importsMe: clusterProfiler, DOSE, Rcpi suggestsMe: ChIPseeker, ReactomePA Package: goseq Version: 1.16.2 Depends: R (>= 2.11.0), BiasedUrn, geneLenDataBase Imports: mgcv, graphics, stats, utils, AnnotationDbi Suggests: GO.db, edgeR, org.Hs.eg.db, rtracklayer License: LGPL (>= 2) MD5sum: 1261d940aa858bf85f2f6d6396b2759f NeedsCompilation: no Title: Gene Ontology analyser for RNA-seq and other length biased data Description: Detects Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data biocViews: Sequencing, GO, GeneExpression, Transcription, RNASeq Author: Matthew Young Maintainer: Nadia Davidson source.ver: src/contrib/goseq_1.16.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/goseq_1.16.2.zip win64.binary.ver: bin/windows64/contrib/3.1/goseq_1.16.2.zip mac.binary.ver: bin/macosx/contrib/3.1/goseq_1.16.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/goseq_1.16.2.tgz vignettes: vignettes/goseq/inst/doc/goseq.pdf vignetteTitles: goseq User's Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/goseq/inst/doc/goseq.R suggestsMe: oneChannelGUI Package: GOSim Version: 1.6.0 Depends: GO.db, annotate, igraph Imports: org.Hs.eg.db, AnnotationDbi, topGO, cluster, flexmix, RBGL, graph, Matrix, corpcor, Rcpp, utils LinkingTo: Rcpp License: GPL (>= 2) Archs: i386, x64 MD5sum: 66ebbdab3720ea55f728c2f4524e44de NeedsCompilation: yes Title: Computation of functional similarities between GO terms and gene products; GO enrichment analysis Description: This package implements several functions useful for computing similarities between GO terms and gene products based on their GO annotation. Moreover it allows for computing a GO enrichment analysis biocViews: GO, Clustering, Software, Network Author: Holger Froehlich Maintainer: Holger Froehlich source.ver: src/contrib/GOSim_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GOSim_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GOSim_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GOSim_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GOSim_1.6.0.tgz vignettes: vignettes/GOSim/inst/doc/GOSim.pdf vignetteTitles: GOsim hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOSim/inst/doc/GOSim.R Package: GOstats Version: 2.30.0 Depends: R (>= 2.10), Biobase (>= 1.15.29), Category (>= 2.3.26), graph Imports: AnnotationDbi (>= 0.0.89), Biobase (>= 1.15.29), Category (>= 2.3.26), GO.db (>= 1.13.0), RBGL, annotate (>= 1.13.2), graph (>= 1.15.15), methods, stats , AnnotationForge Suggests: hgu95av2.db (>= 1.13.0), ALL, GO.db (>= 1.13.0), annotate, multtest, genefilter, RColorBrewer, Rgraphviz, xtable, SparseM, GSEABase, geneplotter, org.Hs.eg.db, RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 480bc0a7396da89f96f1fdb075d9a4a9 NeedsCompilation: no Title: Tools for manipulating GO and microarrays. Description: A set of tools for interacting with GO and microarray data. A variety of basic manipulation tools for graphs, hypothesis testing and other simple calculations. biocViews: Annotation, GO, MultipleComparison Author: R. Gentleman and S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GOstats_2.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GOstats_2.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GOstats_2.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GOstats_2.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GOstats_2.30.0.tgz vignettes: vignettes/GOstats/inst/doc/GOstatsForUnsupportedOrganisms.pdf, vignettes/GOstats/inst/doc/GOstatsHyperG.pdf, vignettes/GOstats/inst/doc/GOvis.pdf vignetteTitles: Hypergeometric tests for less common model organisms, Hypergeometric Tests Using GOstats, Visualizing Data Using GOstats hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOstats/inst/doc/GOstatsHyperG.R, vignettes/GOstats/inst/doc/GOvis.R dependsOnMe: attract, MineICA, RDAVIDWebService importsMe: affycoretools, attract, categoryCompare, ProCoNA suggestsMe: BiocCaseStudies, Category, eisa, fastLiquidAssociation, GSEAlm, HTSanalyzeR, interactiveDisplay, MineICA, MLP, MmPalateMiRNA, oneChannelGUI, phenoDist, safe Package: GOTHiC Version: 1.1.2 Depends: R (>= 2.15.1), methods, utils, stats, GenomicRanges, Biostrings, BSgenome, data.table Imports: BiocGenerics, IRanges, ShortRead, rtracklayer, ggplot2 Suggests: HiCDataLymphoblast Enhances: multicore License: GPL-3 MD5sum: 00dc19979d3349103e34de4a0574b1bb NeedsCompilation: no Title: Binomial test for Hi-C data analysis Description: This is a Hi-C analysis package using a cumulative binomial test to detect interactions between distal genomic loci that have significantly more reads than expected by chance in Hi-C experiments. It takes mapped paired NGS reads as input and gives back the list of significant interactions for a given bin size in the genome. biocViews: Sequencing, Preprocessing, Epigenetics Author: Borbala Mifsud and Robert Sugar Maintainer: Borbala Mifsud source.ver: src/contrib/GOTHiC_1.1.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/GOTHiC_1.1.2.zip win64.binary.ver: bin/windows64/contrib/3.1/GOTHiC_1.1.2.zip mac.binary.ver: bin/macosx/contrib/3.1/GOTHiC_1.1.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GOTHiC_1.1.2.tgz vignettes: vignettes/GOTHiC/inst/doc/package_vignettes.pdf vignetteTitles: package_vignettes.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: goTools Version: 1.38.0 Depends: GO.db Imports: AnnotationDbi, GO.db, graphics, grDevices Suggests: hgu133a.db License: GPL-2 MD5sum: a9df02e28b77cc72b9553f98377a9777 NeedsCompilation: no Title: Functions for Gene Ontology database Description: Wraper functions for description/comparison of oligo ID list using Gene Ontology database biocViews: Microarray,GO,Visualization Author: Yee Hwa (Jean) Yang , Agnes Paquet Maintainer: Agnes Paquet source.ver: src/contrib/goTools_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/goTools_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/goTools_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/goTools_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/goTools_1.38.0.tgz vignettes: vignettes/goTools/inst/doc/goTools.pdf vignetteTitles: goTools overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/goTools/inst/doc/goTools.R Package: gpls Version: 1.36.0 Imports: stats Suggests: MASS License: Artistic-2.0 MD5sum: e45729b3b77097d12ba3e7986dc75be5 NeedsCompilation: no Title: Classification using generalized partial least squares Description: Classification using generalized partial least squares for two-group and multi-group (more than 2 group) classification. biocViews: Classification, Microarray Author: Beiying Ding Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/gpls_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gpls_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gpls_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gpls_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gpls_1.36.0.tgz vignettes: vignettes/gpls/inst/doc/gpls.pdf vignetteTitles: gpls Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gpls/inst/doc/gpls.R suggestsMe: MCRestimate, MLInterfaces Package: gprege Version: 1.8.0 Depends: R (>= 2.8.0), gptk Suggests: spam License: AGPL-3 MD5sum: 218c5f02c875d3bf90ad5a85108e92a5 NeedsCompilation: no Title: Gaussian Process Ranking and Estimation of Gene Expression time-series Description: The gprege package implements the methodology described in Kalaitzis & Lawrence (2011) "A simple approach to ranking differentially expressed gene expression time-courses through Gaussian process regression". The software fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP kernel is initialised wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimised via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via ROC curves is performed against BATS (Angelini et.al, 2007). A detailed discussion of the ranking approach and dataset used can be found in the paper (http://www.biomedcentral.com/1471-2105/12/180). biocViews: Microarray, Preprocessing, DifferentialExpression, TimeCourse Author: Alfredo Kalaitzis Maintainer: Alfredo Kalaitzis source.ver: src/contrib/gprege_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gprege_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gprege_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gprege_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gprege_1.8.0.tgz vignettes: vignettes/gprege/inst/doc/gprege_quick.pdf vignetteTitles: gprege Quick Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gprege/inst/doc/gprege_quick.R Package: graph Version: 1.42.0 Depends: R (>= 2.10), methods Imports: methods, stats, stats4, tools, utils, BiocGenerics (>= 0.1.11) Suggests: SparseM (>= 0.36), XML, RBGL, RUnit, cluster Enhances: Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: a16db6406a20f9cd94eea569a72c1a7c NeedsCompilation: yes Title: graph: A package to handle graph data structures Description: A package that implements some simple graph handling capabilities. biocViews: GraphAndNetwork Author: R. Gentleman, Elizabeth Whalen, W. Huber, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/graph_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/graph_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/graph_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/graph_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/graph_1.42.0.tgz vignettes: vignettes/graph/inst/doc/clusterGraph.pdf, vignettes/graph/inst/doc/graphAttributes.pdf, vignettes/graph/inst/doc/GraphClass.pdf, vignettes/graph/inst/doc/graph.pdf, vignettes/graph/inst/doc/MultiGraphClass.pdf vignetteTitles: clusterGraph and distGraph, Attributes for Graph Objects, Graph Design, Graph, graphBAM and MultiGraph classes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/graph/inst/doc/clusterGraph.R, vignettes/graph/inst/doc/graphAttributes.R, vignettes/graph/inst/doc/GraphClass.R, vignettes/graph/inst/doc/graph.R, vignettes/graph/inst/doc/MultiGraphClass.R dependsOnMe: apComplex, biocGraph, BioMVCClass, BioNet, CellNOptR, clipper, CNORfeeder, ddgraph, flowClust, gaggle, gaucho, GeneNetworkBuilder, GOFunction, GOstats, GraphAT, GSEABase, hypergraph, KEGGgraph, maigesPack, MineICA, NCIgraph, nem, netresponse, NetSAM, pathRender, pkgDepTools, RbcBook1, RBGL, RBioinf, RCytoscape, RDAVIDWebService, Rgraphviz, ROntoTools, RpsiXML, Rtreemix, SRAdb, topGO, vtpnet importsMe: BiocCheck, biocGraph, biocViews, CAMERA, Category, categoryCompare, DEGraph, flowCore, flowUtils, flowWorkspace, gage, GeneNetworkBuilder, GOFunction, GOSim, GOstats, GraphAT, graphite, HTSanalyzeR, hyperdraw, KEGGgraph, keggorthology, NCIgraph, nem, OrganismDbi, pathview, PCpheno, pkgDepTools, ppiStats, qpgraph, RchyOptimyx, rsbml, Rtreemix, SplicingGraphs, Streamer, topGO suggestsMe: AnnotationDbi, BiocCaseStudies, Category, DEGraph, EBcoexpress, ecolitk, GeneAnswers, gwascat, mmnet, MmPalateMiRNA, rBiopaxParser, rTRM, SPIA, VariantTools Package: GraphAlignment Version: 1.28.0 License: file LICENSE License_restricts_use: yes Archs: i386, x64 MD5sum: 9c5aee815bee1d941f2c4252a8dec814 NeedsCompilation: yes Title: GraphAlignment Description: Graph alignment is an extension package for the R programming environment which provides functions for finding an alignment between two networks based on link and node similarity scores. (J. Berg and M. Laessig, "Cross-species analysis of biological networks by Bayesian alignment", PNAS 103 (29), 10967-10972 (2006)) biocViews: GraphAndNetwork, Network Author: Joern P. Meier , Michal Kolar, Ville Mustonen, Michael Laessig, and Johannes Berg. Maintainer: Joern P. Meier URL: http://www.thp.uni-koeln.de/~berg/GraphAlignment/ source.ver: src/contrib/GraphAlignment_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GraphAlignment_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GraphAlignment_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GraphAlignment_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GraphAlignment_1.28.0.tgz vignettes: vignettes/GraphAlignment/inst/doc/GraphAlignment.pdf vignetteTitles: GraphAlignment hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GraphAlignment/inst/doc/GraphAlignment.R Package: GraphAT Version: 1.36.0 Depends: R (>= 2.10), graph, methods Imports: graph, MCMCpack, methods, stats License: LGPL MD5sum: 29f9a34dbd7828b3342d2cda4e3159e3 NeedsCompilation: no Title: Graph Theoretic Association Tests Description: Functions and data used in Balasubramanian, et al. (2004) biocViews: Network, GraphAndNetwork Author: R. Balasubramanian, T. LaFramboise, D. Scholtens Maintainer: Thomas LaFramboise source.ver: src/contrib/GraphAT_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GraphAT_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GraphAT_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GraphAT_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GraphAT_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: graphite Version: 1.10.1 Depends: R (>= 2.10) Imports: AnnotationDbi, graph, graphics, methods, org.Hs.eg.db, stats, utils Suggests: BiocStyle, DEGraph (>= 1.4), hgu133plus2.db, RCytoscape (>= 1.6), SPIA (>= 2.2), topologyGSA (>= 1.4.0), clipper, ALL License: AGPL-3 MD5sum: 1f58e4c93e0aa82f76546ae687421462 NeedsCompilation: no Title: GRAPH Interaction from pathway Topological Environment Description: Graph objects from pathway topology derived from Biocarta, HumanCyc, KEGG, NCI, Panther, Reactome and SPIKE databases. biocViews: Pathways, ThirdPartyClient, GraphAndNetwork Author: Gabriele Sales , Enrica Calura , Chiara Romualdi Maintainer: Gabriele Sales source.ver: src/contrib/graphite_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/graphite_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/graphite_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/graphite_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/graphite_1.10.1.tgz vignettes: vignettes/graphite/inst/doc/graphite.pdf vignetteTitles: GRAPH Interaction from pathway Topological Environment hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/graphite/inst/doc/graphite.R importsMe: ReactomePA suggestsMe: clipper Package: GraphPAC Version: 1.6.0 Depends: R(>= 2.15),iPAC, igraph, TSP, RMallow Suggests: RUnit, BiocGenerics License: GPL-2 MD5sum: 653c7ccfa60355df7a3a89b150888c3c NeedsCompilation: no Title: Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach. Description: Identifies mutational clusters of amino acids in a protein while utilizing the proteins tertiary structure via a graph theoretical model. biocViews: Clustering, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/GraphPAC_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GraphPAC_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GraphPAC_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GraphPAC_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GraphPAC_1.6.0.tgz vignettes: vignettes/GraphPAC/inst/doc/GraphPAC.pdf vignetteTitles: iPAC: identification of Protein Amino acid Mutations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GraphPAC/inst/doc/GraphPAC.R Package: GRENITS Version: 1.16.1 Depends: R (>= 2.12.0), Rcpp (>= 0.8.6), RcppArmadillo (>= 0.2.8), ggplot2 (>= 0.9.0) Imports: graphics, grDevices, reshape2, stats, utils LinkingTo: Rcpp, RcppArmadillo Suggests: network License: GPL (>= 2) Archs: i386, x64 MD5sum: 01a8a1e229227b76db41b5710e8b8500 NeedsCompilation: yes Title: Gene Regulatory Network Inference Using Time Series Description: The package offers four network inference statistical models using Dynamic Bayesian Networks and Gibbs Variable Selection: a linear interaction model, two linear interaction models with added experimental noise (Gaussian and Student distributed) for the case where replicates are available and a non-linear interaction model. biocViews: NetworkInference, GeneRegulation, TimeCourse, GraphAndNetwork Author: Edward Morrissey Maintainer: Edward Morrissey source.ver: src/contrib/GRENITS_1.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GRENITS_1.16.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GRENITS_1.16.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GRENITS_1.16.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GRENITS_1.16.1.tgz vignettes: vignettes/GRENITS/inst/doc/GRENITS_package.pdf vignetteTitles: GRENITS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GRENITS/inst/doc/GRENITS_package.R Package: GSCA Version: 1.2.0 Depends: shiny, sp, gplots, ggplot2, reshape2, RColorBrewer, rhdf5 Imports: graphics Suggests: Affyhgu133aExpr, Affymoe4302Expr, Affyhgu133A2Expr, Affyhgu133Plus2Expr License: GPL(>=2) MD5sum: 60c2e9a0025c6e3f57ef8fe6e6bbb3fd NeedsCompilation: no Title: GSCA: Gene Set Context Analysis Description: GSCA takes as input several lists of activated and repressed genes. GSCA then searches through a compendium of publicly available gene expression profiles for biological contexts that are enriched with a specified pattern of gene expression. GSCA provides both traditional R functions and interactive, user-friendly user interface. biocViews: GeneExpression, Visualization, GUI Author: Zhicheng Ji, Hongkai Ji Maintainer: Zhicheng Ji source.ver: src/contrib/GSCA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GSCA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GSCA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GSCA_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GSCA_1.0.0.tgz vignettes: vignettes/GSCA/inst/doc/GSCA.pdf vignetteTitles: GSCA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSCA/inst/doc/GSCA.R Package: GSEABase Version: 1.26.0 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), annotate, methods, graph (>= 1.37.2) Imports: AnnotationDbi, XML Suggests: hgu95av2.db, GO.db, org.Hs.eg.db, Rgraphviz, ReportingTools License: Artistic-2.0 MD5sum: 4ee5caef78742e62fca5c354bd8546b3 NeedsCompilation: no Title: Gene set enrichment data structures and methods Description: This package provides classes and methods to support Gene Set Enrichment Analysis (GSEA). biocViews: Infrastructure Author: Martin Morgan, Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GSEABase_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GSEABase_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GSEABase_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GSEABase_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GSEABase_1.26.0.tgz vignettes: vignettes/GSEABase/inst/doc/GSEABase.pdf vignetteTitles: An introduction to GSEABase hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSEABase/inst/doc/GSEABase.R dependsOnMe: AGDEX, BicARE, gCMAP, GSVA, npGSEA, PROMISE importsMe: Category, categoryCompare, cellHTS2, gCMAPWeb, GSRI, GSVA, HTSanalyzeR, PCpheno, phenoTest, PROMISE, ReportingTools suggestsMe: BiocCaseStudies, gage, GlobalAncova, globaltest, GOstats, PGSEA, phenoTest Package: GSEAlm Version: 1.24.0 Depends: Biobase Suggests: GSEABase,Category, multtest, ALL, annotate, hgu95av2.db, genefilter, GOstats, RColorBrewer License: Artistic-2.0 MD5sum: 77efcbe571e563199ba6ba692b4ac91d NeedsCompilation: no Title: Linear Model Toolset for Gene Set Enrichment Analysis Description: Models and methods for fitting linear models to gene expression data, together with tools for computing and using various regression diagnostics. biocViews: Microarray Author: Assaf Oron, Robert Gentleman (with contributions from S. Falcon and Z. Jiang) Maintainer: Assaf Oron source.ver: src/contrib/GSEAlm_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GSEAlm_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GSEAlm_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GSEAlm_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GSEAlm_1.24.0.tgz vignettes: vignettes/GSEAlm/inst/doc/GSEAlm.pdf vignetteTitles: Linear models in GSEA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSEAlm/inst/doc/GSEAlm.R importsMe: gCMAP Package: GSRI Version: 2.12.0 Depends: R (>= 2.14.2), fdrtool Imports: methods, graphics, stats, utils, genefilter, Biobase, GSEABase, les (>= 1.1.6) Suggests: limma, hgu95av2.db Enhances: parallel License: GPL-3 MD5sum: 06e42fd267710d5f596b976df8b967a7 NeedsCompilation: no Title: Gene Set Regulation Index Description: The GSRI package estimates the number of differentially expressed genes in gene sets, utilizing the concept of the Gene Set Regulation Index (GSRI). biocViews: Microarray, Transcription, DifferentialExpression, Enrichment, GeneSetEnrichment Author: Julian Gehring, Kilian Bartholome, Clemens Kreutz, Jens Timmer Maintainer: Julian Gehring URL: http://julian-gehring.github.com/GSRI/ source.ver: src/contrib/GSRI_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GSRI_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GSRI_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GSRI_2.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GSRI_2.12.0.tgz vignettes: vignettes/GSRI/inst/doc/gsri.pdf vignetteTitles: Introduction to the GSRI package: Estimating Regulatory Effects utilizing the Gene Set Regulation Index hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSRI/inst/doc/gsri.R Package: GSVA Version: 1.12.0 Depends: R (>= 2.13.0), methods, GSEABase (>= 1.17.4) Imports: methods, BiocGenerics, Biobase, GSEABase Suggests: limma, RColorBrewer, genefilter, mclust, edgeR, GSVAdata Enhances: snow, parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: 5411ddaa92885bc8fd8998ae6afc298f NeedsCompilation: yes Title: Gene Set Variation Analysis for microarray and RNA-seq data Description: Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner. biocViews: Microarray, Pathways, GeneSetEnrichment Author: Justin Guinney with contributions from Robert Castelo Maintainer: Justin Guinney URL: http://www.sagebase.org source.ver: src/contrib/GSVA_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/GSVA_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/GSVA_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/GSVA_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GSVA_1.12.0.tgz vignettes: vignettes/GSVA/inst/doc/GSVA.pdf vignetteTitles: Gene Set Variation Analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GSVA/inst/doc/GSVA.R Package: Gviz Version: 1.8.4 Depends: R (>= 2.10.0), methods, grid, BiocGenerics (>= 0.1.4) Imports: IRanges (>= 1.19.5), XVector, rtracklayer (>= 1.15.5), lattice, RColorBrewer, biomaRt (>= 2.11.0), GenomicRanges (>= 1.7.14), AnnotationDbi (>= 1.17.11), Biobase (>= 2.15.3), GenomicFeatures (>= 1.9.7), BSgenome (>= 1.31.5), Biostrings (>= 2.31.8), biovizBase (>= 1.5.7), Rsamtools(>= 1.11.1), latticeExtra(>= 0.6-26), matrixStats(>= 0.8.14), GenomicAlignments (>= 0.99.11) Suggests: xtable, BSgenome.Hsapiens.UCSC.hg19, BiocStyle License: Artistic-2.0 MD5sum: a2dc8d12c4c59037fc4c35da1d5ba646 NeedsCompilation: no Title: Plotting data and annotation information along genomic coordinates Description: Genomic data analyses requires integrated visualization of known genomic information and new experimental data. Gviz uses the biomaRt and the rtracklayer packages to perform live annotation queries to Ensembl and UCSC and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. biocViews: Visualization, Microarray Author: Florian Hahne, Steffen Durinck, Robert Ivanek, Arne Mueller, Steve Lianoglou, Ge Tan , Lance Parsons Maintainer: Florian Hahne source.ver: src/contrib/Gviz_1.8.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/Gviz_1.8.4.zip win64.binary.ver: bin/windows64/contrib/3.1/Gviz_1.8.4.zip mac.binary.ver: bin/macosx/contrib/3.1/Gviz_1.8.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Gviz_1.8.4.tgz vignettes: vignettes/Gviz/inst/doc/Gviz.pdf vignetteTitles: Gviz users guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Gviz/inst/doc/Gviz.R dependsOnMe: biomvRCNS, cummeRbund, DMRforPairs importsMe: GGtools, methyAnalysis, PING, trackViewer suggestsMe: annmap, CNEr, gwascat, interactiveDisplay, QuasR, SplicingGraphs Package: gwascat Version: 1.8.0 Depends: R (>= 3.0.0) Imports: methods, Biostrings, IRanges, GenomicRanges, BiocGenerics, snpStats, Rsamtools, rtracklayer Suggests: DO.db, Gviz, ggbio, graph Enhances: SNPlocs.Hsapiens.dbSNP.20120608, pd.genomewidesnp.6 License: Artistic-2.0 MD5sum: 1d3389747866c206f4840b8c4b826a7e NeedsCompilation: no Title: representing and modeling data in the NHGRI GWAS catalog Description: representing and modeling data in the NHGRI GWAS catalog biocViews: Genetics Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/gwascat_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/gwascat_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/gwascat_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/gwascat_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/gwascat_1.8.0.tgz vignettes: vignettes/gwascat/inst/doc/gwascat.pdf vignetteTitles: gwascat -- exploring NHGRI GWAS catalog hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gwascat/inst/doc/gwascat.R suggestsMe: vtpnet Package: GWASTools Version: 1.10.1 Depends: Biobase, ncdf, gdsfmt, sandwich Imports: methods, DBI, RSQLite, GWASExactHW, DNAcopy, survival, lmtest, quantsmooth Suggests: GWASdata, BiocGenerics, RUnit, SNPRelate, snpStats, VariantAnnotation License: Artistic-2.0 MD5sum: 3eac5093c3f3588a17bff922c2fa3a70 NeedsCompilation: no Title: Tools for Genome Wide Association Studies Description: Classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis. biocViews: SNP, GeneticVariability, QualityControl, Microarray Author: Stephanie M. Gogarten, Cathy Laurie, Tushar Bhangale, Matthew P. Conomos, Cecelia Laurie, Caitlin McHugh, Ian Painter, Xiuwen Zheng, Jess Shen, Rohit Swarnkar, Adrienne Stilp Maintainer: Stephanie M. Gogarten , Adrienne Stilp source.ver: src/contrib/GWASTools_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/GWASTools_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/GWASTools_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/GWASTools_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/GWASTools_1.10.1.tgz vignettes: vignettes/GWASTools/inst/doc/Affymetrix.pdf, vignettes/GWASTools/inst/doc/DataCleaning.pdf, vignettes/GWASTools/inst/doc/Formats.pdf, vignettes/GWASTools/inst/doc/VCF.pdf vignetteTitles: Preparing Affymetrix Data, GWAS Data Cleaning, Data formats in GWASTools, Converting VCF data for use in GWASTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GWASTools/inst/doc/Affymetrix.R, vignettes/GWASTools/inst/doc/DataCleaning.R, vignettes/GWASTools/inst/doc/Formats.R, vignettes/GWASTools/inst/doc/VCF.R Package: h5vc Version: 1.4.0 Depends: grid, gridExtra, ggplot2 Imports: rhdf5, reshape, IRanges, Biostrings, Rsamtools, methods, GenomicRanges, abind, BiocParallel, BatchJobs, h5vcData Suggests: knitr, locfit, BSgenome.Hsapiens.UCSC.hg19, bit64 License: GPL (>= 3) Archs: i386, x64 MD5sum: 47551b03964675a00ca2e3fb6b1d8ff5 NeedsCompilation: yes Title: Managing alignment tallies using a hdf5 backend Description: This package contains functions to interact with tally data from NGS experiments that is stored in HDF5 files. For detail see the webpage at http://www.ebi.ac.uk/~pyl/h5vc. Author: Paul Theodor Pyl Maintainer: Paul Theodor Pyl VignetteBuilder: knitr source.ver: src/contrib/h5vc_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/h5vc_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/h5vc_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/h5vc_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/h5vc_1.4.0.tgz vignettes: vignettes/h5vc/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.R, vignettes/h5vc/inst/doc/h5vc.tour.R htmlDocs: vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.html, vignettes/h5vc/inst/doc/h5vc.tour.html htmlTitles: "Building a minimal genome browser with h5vc and shiny", "h5vc - Tour" importsMe: Rariant suggestsMe: SomaticSignatures Package: hapFabia Version: 1.6.3 Depends: R (>= 2.12.0), Biobase, fabia (>= 2.3.1) Imports: methods, graphics, grDevices, stats, utils License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 82ad7b8a62940f4f13832b28c764978c NeedsCompilation: yes Title: hapFabia: Identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data Description: A package to identify very short IBD segments in large sequencing data by FABIA biclustering. Two haplotypes are identical by descent (IBD) if they share a segment that both inherited from a common ancestor. Current IBD methods reliably detect long IBD segments because many minor alleles in the segment are concordant between the two haplotypes. However, many cohort studies contain unrelated individuals which share only short IBD segments. This package provides software to identify short IBD segments in sequencing data. Knowledge of short IBD segments are relevant for phasing of genotyping data, association studies, and for population genetics, where they shed light on the evolutionary history of humans. The package supports VCF formats, is based on sparse matrix operations, and provides visualization of haplotype clusters in different formats. biocViews: Genetics, GeneticVariability, SNP, Sequencing, Sequencing, Visualization, Clustering, SequenceMatching, Homo_sapiens, Software Author: Sepp Hochreiter Maintainer: Sepp Hochreiter URL: http://www.bioinf.jku.at/software/hapFabia/hapFabia.html source.ver: src/contrib/hapFabia_1.6.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/hapFabia_1.6.3.zip win64.binary.ver: bin/windows64/contrib/3.1/hapFabia_1.6.3.zip mac.binary.ver: bin/macosx/contrib/3.1/hapFabia_1.6.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/hapFabia_1.6.3.tgz vignettes: vignettes/hapFabia/inst/doc/hapfabia.pdf vignetteTitles: hapFabia: Manual for the R package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hapFabia/inst/doc/hapfabia.R Package: Harshlight Version: 1.36.0 Depends: R (>= 2.10) Imports: affy, altcdfenvs, Biobase, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: dcbe712d97085b282c111bebc4081849 NeedsCompilation: yes Title: A "corrective make-up" program for microarray chips Description: The package is used to detect extended, diffuse and compact blemishes on microarray chips. Harshlight automatically marks the areas in a collection of chips (affybatch objects) and a corrected AffyBatch object is returned, in which the defected areas are substituted with NAs or the median of the values of the same probe in the other chips in the collection. The new version handle the substitute value as whole matrix to solve the memory problem. biocViews: Microarray, QualityControl, Preprocessing, OneChannel, ReportWriting Author: Mayte Suarez-Farinas, Maurizio Pellegrino, Knut M. Wittkowski, Marcelo O. Magnasco Maintainer: Maurizio Pellegrino URL: http://asterion.rockefeller.edu/Harshlight/ source.ver: src/contrib/Harshlight_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Harshlight_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Harshlight_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Harshlight_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Harshlight_1.36.0.tgz vignettes: vignettes/Harshlight/inst/doc/Harshlight.pdf vignetteTitles: Harshlight hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Harshlight/inst/doc/Harshlight.R Package: HCsnip Version: 1.4.0 Depends: R(>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase License: GPL (>= 2) MD5sum: 290cef0337839003daab1b0209a879b5 NeedsCompilation: no Title: Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree Description: Decompose given hierarchical clustering tree into non-overlapping clusters in a semi-supervised way by using available patients follow-up information as guidance. Contains functions for snipping HC tree, various cluster quality evaluation criteria, assigning new patients to one of the two given HC trees, testing the significance of clusters with permutation argument and clusters visualization using sample's molecular entropy. biocViews: Microarray, aCGH, GeneExpression, Clustering Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/HCsnip_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HCsnip_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HCsnip_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HCsnip_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HCsnip_1.4.0.tgz vignettes: vignettes/HCsnip/inst/doc/HCsnip.pdf vignetteTitles: HCsnip hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HCsnip/inst/doc/HCsnip.R Package: Heatplus Version: 2.10.0 Imports: graphics, grDevices, stats Suggests: Biobase, hgu95av2.db, limma License: GPL (>= 2) MD5sum: 46b59c9d9d10dfad2a68b696788b17b3 NeedsCompilation: no Title: Heatmaps with row and/or column covariates and colored clusters Description: Display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot. biocViews: Microarray, Visualization Author: Alexander Ploner Maintainer: Alexander Ploner source.ver: src/contrib/Heatplus_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Heatplus_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Heatplus_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Heatplus_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Heatplus_2.10.0.tgz vignettes: vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.pdf, vignettes/Heatplus/inst/doc/annHeatmap.pdf, vignettes/Heatplus/inst/doc/oldHeatplus.pdf vignetteTitles: Commented package source, Annotated and regular heatmaps, Old functions (deprecated) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.R, vignettes/Heatplus/inst/doc/annHeatmap.R, vignettes/Heatplus/inst/doc/oldHeatplus.R dependsOnMe: GeneAnswers, phenoTest, tRanslatome Package: HELP Version: 1.22.0 Depends: R (>= 2.8.0), stats, graphics, grDevices, Biobase, methods License: GPL (>= 2) MD5sum: 713042c42987bbba9ff7a15dc3b6ecd5 NeedsCompilation: no Title: Tools for HELP data analysis Description: The package contains a modular pipeline for analysis of HELP microarray data, and includes graphical and mathematical tools with more general applications biocViews: CpGIsland, DNAMethylation, Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, Visualization Author: Reid F. Thompson , John M. Greally , with contributions from Mark Reimers Maintainer: Reid F. Thompson source.ver: src/contrib/HELP_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HELP_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HELP_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HELP_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HELP_1.22.0.tgz vignettes: vignettes/HELP/inst/doc/HELP.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HELP/inst/doc/HELP.R Package: HEM Version: 1.36.0 Depends: R (>= 2.1.0) Imports: Biobase, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: f95c6bb89821631983f98a9e3abc3a5d NeedsCompilation: yes Title: Heterogeneous error model for identification of differentially expressed genes under multiple conditions Description: This package fits heterogeneous error models for analysis of microarray data biocViews: Microarray, DifferentialExpression Author: HyungJun Cho and Jae K. Lee Maintainer: HyungJun Cho URL: http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/ source.ver: src/contrib/HEM_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HEM_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HEM_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HEM_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HEM_1.36.0.tgz vignettes: vignettes/HEM/inst/doc/HEM.pdf vignetteTitles: HEM Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HEM/inst/doc/HEM.R Package: HilbertVis Version: 1.22.0 Depends: R (>= 2.6.0), grid, lattice Suggests: IRanges, EBImage License: GPL (>= 3) Archs: i386, x64 MD5sum: 930b2160c8c5b213483b9770faae3ee7 NeedsCompilation: yes Title: Hilbert curve visualization Description: Functions to visualize long vectors of integer data by means of Hilbert curves biocViews: Visualization Author: Simon Anders Maintainer: Simon Anders URL: http://www.ebi.ac.uk/~anders/hilbert source.ver: src/contrib/HilbertVis_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HilbertVis_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HilbertVis_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HilbertVis_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HilbertVis_1.22.0.tgz vignettes: vignettes/HilbertVis/inst/doc/HilbertVis.pdf vignetteTitles: Visualising very long data vectors with the Hilbert curve hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HilbertVis/inst/doc/HilbertVis.R dependsOnMe: HilbertVisGUI importsMe: ChIPseqR Package: HilbertVisGUI Version: 1.22.0 Depends: R (>= 2.6.0), HilbertVis (>= 1.1.6) Suggests: lattice, IRanges License: GPL (>= 3) Archs: i386, x64 MD5sum: 8b43a3a006a88b6a2ae444909514d2fc NeedsCompilation: yes Title: HilbertVisGUI Description: An interactive tool to visualize long vectors of integer data by means of Hilbert curves biocViews: Visualization Author: Simon Anders Maintainer: Simon Anders URL: http://www.ebi.ac.uk/~anders/hilbert SystemRequirements: gtkmm-2.4 source.ver: src/contrib/HilbertVisGUI_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HilbertVisGUI_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HilbertVisGUI_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HilbertVisGUI_1.22.0.tgz vignettes: vignettes/HilbertVisGUI/inst/doc/HilbertVisGUI.pdf vignetteTitles: See vignette in package HilbertVis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: TRUE hasLICENSE: FALSE Rfiles: vignettes/HilbertVisGUI/inst/doc/HilbertVisGUI.R Package: HiTC Version: 1.8.1 Depends: R (>= 2.15.0), methods, IRanges, GenomicRanges Imports: Biostrings, graphics, grDevices, rtracklayer, RColorBrewer, Matrix Suggests: BiocStyle License: Artistic-2.0 MD5sum: 127d0020f9a3bb2c58293e336606725a NeedsCompilation: no Title: High Throughput Chromosome Conformation Capture analysis Description: The HiTC package was developed to explore high-throughput 'C' data such as 5C or Hi-C. biocViews: Sequencing, HighThroughputSequencing Author: Nicolas Servant Maintainer: Nicolas Servant source.ver: src/contrib/HiTC_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/HiTC_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/HiTC_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/HiTC_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HiTC_1.8.1.tgz vignettes: vignettes/HiTC/inst/doc/HiTC.pdf vignetteTitles: Hight-Throughput Chromosome Conformation Capture analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HiTC/inst/doc/HiTC.R Package: HMMcopy Version: 1.6.0 Depends: R (>= 2.10.0), IRanges (>= 1.4.16), geneplotter (>= 1.24.0) License: GPL-3 Archs: i386, x64 MD5sum: f6a75ae0846586362bf5f51bc76ef621 NeedsCompilation: yes Title: Copy number prediction with correction for GC and mappability bias for HTS data Description: Corrects GC and mappability biases for readcounts (i.e. coverage) in non-overlapping windows of fixed length for single whole genome samples, yielding a rough estimate of copy number for furthur analysis. Designed for rapid correction of high coverage whole genome tumour and normal samples. biocViews: Sequencing, Preprocessing, Visualization, CopyNumberVariation, Microarray Author: Daniel Lai, Gavin Ha, Sohrab Shah Maintainer: Daniel Lai , Gavin Ha , Sohrab Shah source.ver: src/contrib/HMMcopy_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HMMcopy_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HMMcopy_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HMMcopy_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HMMcopy_1.6.0.tgz vignettes: vignettes/HMMcopy/inst/doc/HMMcopy.pdf vignetteTitles: HMMcopy hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HMMcopy/inst/doc/HMMcopy.R dependsOnMe: TitanCNA Package: hopach Version: 2.24.0 Depends: R (>= 2.11.0), cluster, Biobase, methods Imports: Biobase, cluster, graphics, grDevices, methods, stats, utils, BiocGenerics License: GPL (>= 2) Archs: i386, x64 MD5sum: 916a20f958cfe15570fd61dbedd759fa NeedsCompilation: yes Title: Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH) Description: The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering). biocViews: Clustering Author: Katherine S. Pollard, with Mark J. van der Laan and Greg Wall Maintainer: Katherine S. Pollard URL: http://www.stat.berkeley.edu/~laan/, http://docpollard.org/ source.ver: src/contrib/hopach_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/hopach_2.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/hopach_2.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/hopach_2.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/hopach_2.24.0.tgz vignettes: vignettes/hopach/inst/doc/hopach.pdf vignetteTitles: hopach hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hopach/inst/doc/hopach.R importsMe: phenoTest suggestsMe: BiocCaseStudies Package: hpar Version: 1.6.0 Depends: R (>= 2.15) Suggests: org.Hs.eg.db, GO.db, knitr License: Artistic-2.0 MD5sum: 832f8c9215b0395ed0817e700a807ecf NeedsCompilation: no Title: Human Protein Atlas in R Description: A simple interface to and data from the Human Protein Atlas project. biocViews: Proteomics, Homo_sapiens, CellBiology Author: Laurent Gatto Maintainer: Laurent Gatto source.ver: src/contrib/hpar_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/hpar_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/hpar_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/hpar_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/hpar_1.6.0.tgz vignettes: vignettes/hpar/inst/doc/hpar.pdf vignetteTitles: hpar hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hpar/inst/doc/hpar.R Package: HTqPCR Version: 1.18.0 Depends: Biobase, RColorBrewer, limma Imports: affy, Biobase, gplots, graphics, grDevices, limma, methods, RColorBrewer, stats, stats4, utils Suggests: statmod License: Artistic-2.0 MD5sum: b1c0a54fda09622f1eb633ec8a9e3529 NeedsCompilation: no Title: Automated analysis of high-throughput qPCR data Description: Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays across multiple conditions or replicates. The input data can be from spatially-defined formats such ABI TaqMan Low Density Arrays or OpenArray; LightCycler from Roche Applied Science; the CFX plates from Bio-Rad Laboratories; conventional 96- or 384-well plates; or microfluidic devices such as the Dynamic Arrays from Fluidigm Corporation. HTqPCR handles data loading, quality assessment, normalization, visualization and parametric or non-parametric testing for statistical significance in Ct values between features (e.g. genes, microRNAs). biocViews: MicrotitrePlateAssay, DifferentialExpression, GeneExpression, DataImport, QualityControl, Preprocessing, Visualization, MultipleComparison, qPCR Author: Heidi Dvinge, Paul Bertone Maintainer: Heidi Dvinge URL: http://www.ebi.ac.uk/bertone/software source.ver: src/contrib/HTqPCR_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HTqPCR_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HTqPCR_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HTqPCR_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HTqPCR_1.18.0.tgz vignettes: vignettes/HTqPCR/inst/doc/HTqPCR.pdf vignetteTitles: qPCR analysis in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTqPCR/inst/doc/HTqPCR.R importsMe: nondetects, unifiedWMWqPCR Package: HTSanalyzeR Version: 2.16.0 Depends: R (>= 2.15), igraph, methods Imports: graph, igraph, GSEABase, BioNet, cellHTS2, AnnotationDbi, biomaRt, RankProd Suggests: KEGG.db, GO.db, org.Dm.eg.db, GOstats, org.Ce.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Hs.eg.db, snow License: Artistic-2.0 MD5sum: 436e6c0895ace7f6212dd9a683bf3134 NeedsCompilation: no Title: Gene set over-representation, enrichment and network analyses for high-throughput screens Description: This package provides classes and methods for gene set over-representation, enrichment and network analyses on high-throughput screens. The over-representation analysis is performed based on hypergeometric tests. The enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS 2005). The network analysis identifies enriched subnetworks based on algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A pipeline is also specifically designed for cellHTS2 object to perform integrative network analyses of high-throughput RNA interference screens. The users can build their own analysis pipeline for their own data set based on this package. biocViews: CellBasedAssays, MultipleComparison Author: Xin Wang , Camille Terfve , John C. Rose , Florian Markowetz Maintainer: Xin Wang source.ver: src/contrib/HTSanalyzeR_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HTSanalyzeR_2.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HTSanalyzeR_2.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HTSanalyzeR_2.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HTSanalyzeR_2.16.0.tgz vignettes: vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.pdf vignetteTitles: Main vignette:Gene set enrichment and network analysis of high-throughput RNAi screen data using HTSanalyzeR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.R importsMe: phenoTest suggestsMe: RTN Package: HTSeqGenie Version: 3.14.1 Depends: R (>= 3.0.0), gmapR (>= 1.4.3), ShortRead (>= 1.19.13), VariantAnnotation (>= 1.8.3) Imports: BiocGenerics (>= 0.2.0), IRanges (>= 1.14.3), GenomicRanges (>= 1.7.12), Rsamtools (>= 1.8.5), Biostrings (>= 2.24.1), chipseq (>= 1.6.1), hwriter (>= 1.3.0), Cairo (>= 1.5.5), GenomicFeatures (>= 1.9.31), BiocParallel, parallel, tools, rtracklayer (>= 1.17.19), GenomicAlignments, VariantTools (>= 1.3.6) Suggests: TxDb.Hsapiens.UCSC.hg19.knownGene, LungCancerLines, org.Hs.eg.db License: Artistic-2.0 MD5sum: df2a6c81897aa374b8a26b038a826b61 NeedsCompilation: no Title: A NGS analysis pipeline. Description: Libraries to perform NGS analysis. Author: Gregoire Pau, Jens Reeder Maintainer: Jens Reeder source.ver: src/contrib/HTSeqGenie_3.14.1.tar.gz vignettes: vignettes/HTSeqGenie/inst/doc/HTSeqGenie.pdf vignetteTitles: HTSeqGenie hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSeqGenie/inst/doc/HTSeqGenie.R Package: htSeqTools Version: 1.10.0 Depends: R (>= 2.12.2), methods, BiocGenerics (>= 0.1.0), Biobase, IRanges, methods, MASS, BSgenome, GenomicRanges Enhances: multicore License: GPL (>=2) MD5sum: d81e600c07566dd6ba1c58dfe3289f38 NeedsCompilation: no Title: Quality Control, Visualization and Processing for High-Throughput Sequencing data Description: We provide efficient, easy-to-use tools for High-Throughput Sequencing (ChIP-seq, RNAseq etc.). These include MDS plots (analogues to PCA), detecting inefficient immuno-precipitation or over-amplification artifacts, tools to identify and test for genomic regions with large accumulation of reads, and visualization of coverage profiles. biocViews: Sequencing, QualityControl Author: Evarist Planet, Camille Stephan-Otto, Oscar Reina, Oscar Flores, David Rossell Maintainer: Oscar Reina source.ver: src/contrib/htSeqTools_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/htSeqTools_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/htSeqTools_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/htSeqTools_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/htSeqTools_1.10.0.tgz vignettes: vignettes/htSeqTools/inst/doc/htSeqTools.pdf vignetteTitles: Manual for the htSeqTools library hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/htSeqTools/inst/doc/htSeqTools.R Package: HTSFilter Version: 1.4.0 Depends: methods, Biobase (>= 2.16.0), R (>= 2.10.0) Imports: DESeq (>= 1.8.3), edgeR (>= 2.6.12), DESeq2 (>= 1.2.8), GenomicRanges, IRanges Suggests: EDASeq (>= 1.2.0) License: Artistic-2.0 MD5sum: 741d282dfada49f4b4299eef2476df83 NeedsCompilation: no Title: Filter replicated high-throughput transcriptome sequencing data Description: This package implements a filtering procedure for replicated transcriptome sequencing data based on a global Jaccard similarity index in order to identify genes with low, constant levels of expression across one or more experimental conditions. biocViews: Sequencing, RNASeq, Preprocessing, DifferentialExpression Author: Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic Maintainer: Andrea Rau source.ver: src/contrib/HTSFilter_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HTSFilter_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HTSFilter_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HTSFilter_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HTSFilter_1.4.0.tgz vignettes: vignettes/HTSFilter/inst/doc/HTSFilter.pdf vignetteTitles: HTSFilter Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HTSFilter/inst/doc/HTSFilter.R Package: HybridMTest Version: 1.8.0 Depends: R (>= 2.9.0), Biobase, fdrtool, MASS, survival Imports: stats License: GPL Version 2 or later MD5sum: d93e52720cecdca5faea59f0829dacf0 NeedsCompilation: no Title: Hybrid Multiple Testing Description: Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs. biocViews: GeneExpression, Genetics, Microarray Author: Stan Pounds , Demba Fofana Maintainer: Demba Fofana source.ver: src/contrib/HybridMTest_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/HybridMTest_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/HybridMTest_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/HybridMTest_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/HybridMTest_1.8.0.tgz vignettes: vignettes/HybridMTest/inst/doc/HybridMTest.pdf vignetteTitles: Hybrid Multiple Testing hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HybridMTest/inst/doc/HybridMTest.R Package: hyperdraw Version: 1.16.0 Depends: R (>= 2.9.0) Imports: methods, grid, graph, hypergraph, Rgraphviz, stats4 License: GPL (>= 2) MD5sum: f0d4c7965dcd550d3611b4cd1773426b NeedsCompilation: no Title: Visualizing Hypergaphs Description: Functions for visualizing hypergraphs. biocViews: Visualization, GraphAndNetwork Author: Paul Murrell Maintainer: Paul Murrell SystemRequirements: graphviz source.ver: src/contrib/hyperdraw_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/hyperdraw_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/hyperdraw_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/hyperdraw_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/hyperdraw_1.16.0.tgz vignettes: vignettes/hyperdraw/inst/doc/hyperdraw.pdf vignetteTitles: Hyperdraw hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hyperdraw/inst/doc/hyperdraw.R dependsOnMe: BiGGR Package: hypergraph Version: 1.36.0 Depends: R (>= 2.1.0), methods, graph License: Artistic-2.0 MD5sum: 3193faef5947d88e72e5b937115d7341 NeedsCompilation: no Title: A package providing hypergraph data structures Description: A package that implements some simple capabilities for representing and manipulating hypergraphs. biocViews: GraphAndNetwork Author: Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/hypergraph_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/hypergraph_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/hypergraph_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/hypergraph_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/hypergraph_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: altcdfenvs, RpsiXML importsMe: BiGGR, hyperdraw Package: iASeq Version: 1.8.0 Depends: R (>= 2.14.1) Imports: graphics, grDevices License: GPL-2 MD5sum: 2a483a2cc78e1381643dc9f9e6858313 NeedsCompilation: no Title: iASeq: integrating multiple sequencing datasets for detecting allele-specific events Description: It fits correlation motif model to multiple RNAseq or ChIPseq studies to improve detection of allele-specific events and describe correlation patterns across studies. biocViews: SNP, RNASeq, ChIPSeq Author: Yingying Wei, Hongkai Ji Maintainer: Yingying Wei source.ver: src/contrib/iASeq_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iASeq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iASeq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iASeq_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iASeq_1.8.0.tgz vignettes: vignettes/iASeq/inst/doc/iASeqVignette.pdf vignetteTitles: iASeq Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iASeq/inst/doc/iASeqVignette.R Package: iBBiG Version: 1.8.0 Depends: biclust Imports: stats4,xtable,ade4 Suggests: methods License: Artistic-2.0 Archs: i386, x64 MD5sum: 9ada8b655d1e3f6ef8b6c840daf6f769 NeedsCompilation: yes Title: Iterative Binary Biclustering of Genesets Description: iBBiG is a bi-clustering algorithm which is optimizes for binary data analysis. We apply it to meta-gene set analysis of large numbers of gene expression datasets. The iterative algorithm extracts groups of phenotypes from multiple studies that are associated with similar gene sets. iBBiG does not require prior knowledge of the number or scale of clusters and allows discovery of clusters with diverse sizes biocViews: Clustering, Annotation, GeneSetEnrichment Author: Daniel Gusenleitner, Aedin Culhane Maintainer: Aedin Culhane URL: http://bcb.dfci.harvard.edu/~aedin/publications/ source.ver: src/contrib/iBBiG_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iBBiG_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iBBiG_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iBBiG_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iBBiG_1.8.0.tgz vignettes: vignettes/iBBiG/inst/doc/tutorial.pdf vignetteTitles: iBBiG User Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iBBiG/inst/doc/tutorial.R Package: ibh Version: 1.12.0 Depends: simpIntLists Suggests: yeastCC, stats License: GPL (>= 2) MD5sum: a1fbf0c8e413a33f1457156d8583dcd6 NeedsCompilation: no Title: Interaction Based Homogeneity for Evaluating Gene Lists Description: This package contains methods for calculating Interaction Based Homogeneity to evaluate fitness of gene lists to an interaction network which is useful for evaluation of clustering results and gene list analysis. BioGRID interactions are used in the calculation. The user can also provide their own interactions. biocViews: QualityControl, DataImport, GraphAndNetwork, NetworkEnrichment Author: Kircicegi Korkmaz, Volkan Atalay, Rengul Cetin Atalay. Maintainer: Kircicegi Korkmaz source.ver: src/contrib/ibh_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ibh_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ibh_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ibh_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ibh_1.12.0.tgz vignettes: vignettes/ibh/inst/doc/ibh.pdf vignetteTitles: ibh hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ibh/inst/doc/ibh.R Package: iBMQ Version: 1.4.2 Depends: R(>= 2.15.0),Biobase (>= 2.16.0), ggplot2 (>= 0.9.2) License: Artistic-2.0 Archs: i386, x64 MD5sum: fe43a0d0ec3fbda25f95c8d1bad9f45e NeedsCompilation: yes Title: integrated Bayesian Modeling of eQTL data Description: integrated Bayesian Modeling of eQTL data biocViews: Microarray, Preprocessing, GeneExpression, SNP Author: Marie-Pier Scott-Boyer and Greg Imholte Maintainer: Greg Imholte URL: http://www.rglab.org SystemRequirements: GSL and OpenMP source.ver: src/contrib/iBMQ_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/iBMQ_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/iBMQ_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/iBMQ_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iBMQ_1.4.2.tgz vignettes: vignettes/iBMQ/inst/doc/iBMQ.pdf vignetteTitles: iBMQ: An Integrated Hierarchical Bayesian Model for Multivariate eQTL Mapping hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iBMQ/inst/doc/iBMQ.R Package: Icens Version: 1.36.0 Depends: survival Imports: graphics License: Artistic-2.0 MD5sum: b574dcc37720c95eb3f42828ac99341d NeedsCompilation: no Title: NPMLE for Censored and Truncated Data Description: Many functions for computing the NPMLE for censored and truncated data. biocViews: Infrastructure Author: R. Gentleman and Alain Vandal Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Icens_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Icens_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Icens_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Icens_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Icens_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: PROcess importsMe: PROcess Package: iChip Version: 1.18.0 Depends: R (>= 2.10.0) Imports: limma License: GPL (>= 2) Archs: i386, x64 MD5sum: 9477b318d280f38c06065fc3e5b28c2c NeedsCompilation: yes Title: Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models Description: This package uses hidden Ising models to identify enriched genomic regions in ChIP-chip data. It can be used to analyze the data from multiple platforms (e.g., Affymetrix, Agilent, and NimbleGen), and the data with single to multiple replicates. biocViews: ChIPchip, NimbleGen, OneChannel, Agilent, Microarray Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iChip_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iChip_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iChip_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iChip_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iChip_1.18.0.tgz vignettes: vignettes/iChip/inst/doc/iChip.pdf vignetteTitles: iChip hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iChip/inst/doc/iChip.R Package: iClusterPlus Version: 1.0.1 Depends: R (>= 2.15.0), parallel Suggests: RUnit, BiocGenerics License: GPL (>= 2) Archs: i386, x64 MD5sum: 713fd272db475fd1474c5fab8fd15d9e NeedsCompilation: yes Title: Integrative clustering of multi-type genomic data Description: Integrative clustering of multiple genomic data using a joint latent variable model biocViews: Genomic data, Microarray Author: Qianxing Mo, Ronglai Shen Maintainer: Qianxing Mo , Ronglai Shen source.ver: src/contrib/iClusterPlus_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/iClusterPlus_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/iClusterPlus_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/iClusterPlus_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iClusterPlus_1.0.1.tgz vignettes: vignettes/iClusterPlus/inst/doc/iClusterPlus.pdf, vignettes/iClusterPlus/inst/doc/iManual.pdf vignetteTitles: iClusterPlus, iManual.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iClusterPlus/inst/doc/iClusterPlus.R Package: idiogram Version: 1.40.0 Depends: R (>= 2.10), methods, Biobase, annotate, plotrix Suggests: hu6800.db, hgu95av2.db, golubEsets License: GPL-2 MD5sum: 458f84df5922239911972b30c1147e39 NeedsCompilation: no Title: idiogram Description: A package for plotting genomic data by chromosomal location biocViews: Visualization Author: Karl J. Dykema Maintainer: Karl J. Dykema source.ver: src/contrib/idiogram_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/idiogram_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/idiogram_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/idiogram_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/idiogram_1.40.0.tgz vignettes: vignettes/idiogram/inst/doc/idiogram.pdf vignetteTitles: HOWTO: idiogram hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/idiogram/inst/doc/idiogram.R dependsOnMe: reb Package: IdMappingAnalysis Version: 1.8.0 Depends: R (>= 2.14), R.oo (>= 1.13.0), rChoiceDialogs Imports: boot, mclust, RColorBrewer, Biobase License: GPL-2 MD5sum: c43fbb17173a1318b04c4a393e9a61a8 NeedsCompilation: no Title: ID Mapping Analysis Description: Identifier mapping performance analysis biocViews: Annotation, MultipleComparison Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingAnalysis_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/IdMappingAnalysis_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/IdMappingAnalysis_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/IdMappingAnalysis_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/IdMappingAnalysis_1.8.0.tgz vignettes: vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.pdf vignetteTitles: Critically comparing identifier maps retrieved from bioinformatics annotation resources. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IdMappingAnalysis/inst/doc/IdMappingAnalysis.R Package: IdMappingRetrieval Version: 1.10.0 Depends: R.oo, XML, RCurl, rChoiceDialogs, ENVISIONQuery Imports: biomaRt, ENVISIONQuery, DAVIDQuery, AffyCompatible, R.methodsS3, R.oo, utils License: GPL-2 MD5sum: 156601ae49ff2ed4cadae1186e487918 NeedsCompilation: no Title: ID Mapping Data Retrieval Description: Data retrieval for identifier mapping performance analysis biocViews: Annotation, MultipleComparison Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingRetrieval_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/IdMappingRetrieval_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/IdMappingRetrieval_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/IdMappingRetrieval_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/IdMappingRetrieval_1.10.0.tgz vignettes: vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.pdf vignetteTitles: Collection and subsequent fast retrieval of identifier mapping related information from various online sources. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IdMappingRetrieval/inst/doc/IdMappingRetrieval.R Package: illuminaio Version: 0.6.1 Imports: base64 Suggests: RUnit, BiocGenerics, IlluminaDataTestFiles (>= 1.0.2), BiocStyle License: GPL-2 Archs: i386, x64 MD5sum: 5437f862010d901741ba69a52223211e NeedsCompilation: yes Title: Parsing Illumina microarray output files Description: Tools for parsing Illuminas microarray output files, including IDAT. biocViews: Infrastructure, DataImport Author: Keith Baggerly [aut], Henrik Bengtsson [aut], Kasper Daniel Hansen [aut, cre], Matt Ritchie [aut], Mike L. Smith [aut], Tim Triche Jr. [ctb] Maintainer: Kasper Daniel Hansen source.ver: src/contrib/illuminaio_0.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/illuminaio_0.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/illuminaio_0.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/illuminaio_0.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/illuminaio_0.6.1.tgz vignettes: vignettes/illuminaio/inst/doc/EncryptedFormat.pdf, vignettes/illuminaio/inst/doc/illuminaio.pdf vignetteTitles: Description of Encrypted IDAT Format, Introduction to illuminaio hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/illuminaio/inst/doc/EncryptedFormat.R, vignettes/illuminaio/inst/doc/illuminaio.R importsMe: beadarray, crlmm, methylumi, minfi suggestsMe: limma Package: imageHTS Version: 1.14.1 Depends: R (>= 2.9.0), EBImage (>= 4.3.12), cellHTS2 (>= 2.10.0) Imports: tools, Biobase, hwriter, methods, vsn, stats, utils, e1071 Suggests: BiocStyle, MASS License: LGPL-2.1 MD5sum: fcff26218b67ba6c4bcff6fde2a353e7 NeedsCompilation: no Title: Analysis of high-throughput microscopy-based screens Description: imageHTS is an R package dedicated to the analysis of high-throughput microscopy-based screens. The package provides a modular and extensible framework to segment cells, extract quantitative cell features, predict cell types and browse screen data through web interfaces. Designed to operate in distributed environments, imageHTS provides a standardized access to remote data and facilitates the dissemination of high-throughput microscopy-based datasets. biocViews: Software, CellBasedAssays, Preprocessing, Visualization Author: Gregoire Pau, Xian Zhang, Michael Boutros, Wolfgang Huber Maintainer: Joseph Barry source.ver: src/contrib/imageHTS_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/imageHTS_1.14.1.zip win64.binary.ver: bin/windows64/contrib/3.1/imageHTS_1.14.1.zip mac.binary.ver: bin/macosx/contrib/3.1/imageHTS_1.14.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/imageHTS_1.14.1.tgz vignettes: vignettes/imageHTS/inst/doc/imageHTS-introduction.pdf vignetteTitles: Analysis of high-throughput microscopy-based screens with imageHTS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/imageHTS/inst/doc/imageHTS-introduction.R dependsOnMe: phenoDist Package: impute Version: 1.38.1 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: 5823554f46968e740beb24decb2e8587 NeedsCompilation: yes Title: impute: Imputation for microarray data Description: Imputation for microarray data (currently KNN only) biocViews: Microarray Author: Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu Maintainer: Balasubramanian Narasimhan source.ver: src/contrib/impute_1.38.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/impute_1.38.1.zip win64.binary.ver: bin/windows64/contrib/3.1/impute_1.38.1.zip mac.binary.ver: bin/macosx/contrib/3.1/impute_1.38.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/impute_1.38.1.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: CGHcall, HCsnip importsMe: ChAMP, MSnbase suggestsMe: BioNet Package: INPower Version: 1.0.0 Depends: R (>= 3.1.0), mvtnorm Suggests: RUnit, BiocGenerics License: GPL-2 + file LICENSE MD5sum: 4801468a894aebf30118287842f450f8 NeedsCompilation: no Title: An R package for computing the number of susceptibility SNPs Description: An R package for computing the number of susceptibility SNPs and power of future studies biocViews: SNP Author: Ju-Hyun Park Maintainer: Bill Wheeler source.ver: src/contrib/INPower_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/INPower_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/INPower_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/INPower_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/INPower_1.0.0.tgz vignettes: vignettes/INPower/inst/doc/vignette.pdf vignetteTitles: INPower Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/INPower/inst/doc/vignette.R Package: inSilicoDb Version: 2.0.1 Depends: R (>= 3.0.0), rjson, Biobase, RCurl Suggests: limma License: GPL-2 MD5sum: ddb9bbb963b91d0dd4e960664914cdc1 NeedsCompilation: no Title: Access to the InSilico Database Description: Access expert curated and normalized microarray eSet datasets from the InSilico Database. biocViews: Microarray, DataImport Author: Jonatan Taminau Maintainer: Quentin De Clerck , David Steenhoff URL: https://insilicodb.com source.ver: src/contrib/inSilicoDb_2.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/inSilicoDb_2.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/inSilicoDb_2.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/inSilicoDb_2.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/inSilicoDb_2.0.1.tgz vignettes: vignettes/inSilicoDb/inst/doc/inSilicoDb2.pdf, vignettes/inSilicoDb/inst/doc/inSilicoDb.pdf vignetteTitles: Using the inSilicoDb v2 package, Using the inSilicoDb package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoDb/inst/doc/inSilicoDb2.R, vignettes/inSilicoDb/inst/doc/inSilicoDb.R suggestsMe: inSilicoMerging Package: inSilicoMerging Version: 1.8.7 Depends: R (>= 2.11.1), Biobase, DWD Suggests: BiocGenerics, inSilicoDb License: GPL-2 MD5sum: 1cba2018f08810a7bbdc0ab4dbdb633f NeedsCompilation: no Title: Collection of Merging Techniques for Gene Expression Data Description: Collection of techniques to remove inter-study bias when combining gene expression data originating from different studies. biocViews: Microarray Author: Jonatan Taminau Maintainer: Quentin De Clerck , David Steenhoff URL: http://insilicodb.com/ source.ver: src/contrib/inSilicoMerging_1.8.7.tar.gz win.binary.ver: bin/windows/contrib/3.1/inSilicoMerging_1.8.7.zip win64.binary.ver: bin/windows64/contrib/3.1/inSilicoMerging_1.8.7.zip mac.binary.ver: bin/macosx/contrib/3.1/inSilicoMerging_1.8.7.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/inSilicoMerging_1.8.7.tgz vignettes: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.pdf vignetteTitles: Using the inSilicoMerging package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.R Package: intansv Version: 1.4.1 Depends: R (>= 2.14.0), plyr, ggbio, GenomicRanges Imports: BiocGenerics, IRanges License: Artistic-2.0 MD5sum: 81118315e3e4195992f0af746cf1820f NeedsCompilation: no Title: Integrative analysis of structural variations Description: This package provides efficient tools to read and integrate structural variations predicted by popular softwares. Annotation and visulation of structural variations are also implemented in the package. biocViews: Genetics, Annotation, Sequencing, Software Author: Wen Yao Maintainer: Wen Yao source.ver: src/contrib/intansv_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/intansv_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/intansv_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/intansv_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/intansv_1.4.1.tgz vignettes: vignettes/intansv/inst/doc/intansvOverview.pdf vignetteTitles: An Introduction to intansv hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/intansv/inst/doc/intansvOverview.R Package: interactiveDisplay Version: 1.2.0 Depends: R (>= 2.10), methods, BiocGenerics, grid Imports: shiny, RColorBrewer, ggplot2, reshape2, plyr, gridSVG, XML, Category, AnnotationDbi Suggests: RUnit, hgu95av2.db, knitr,GenomicRanges, GOstats, ggbio, GO.db, Gviz, rtracklayer License: Artistic-2.0 MD5sum: d453619c0e52637dbf7feee88bacf619 NeedsCompilation: no Title: Package for enabling powerful shiny web displays of Bioconductor objects Description: The interactiveDisplay package contains the methods needed to generate interactive Shiny based display methods for Bioconductor objects. biocViews: GO, GeneExpression, Microarray, Sequencing, Classification, Network, QualityControl, Visualization, Visualization, Genetics, DataRepresentation, GUI, AnnotationData Author: Shawn Balcome, Marc Carlson Maintainer: Shawn Balcome VignetteBuilder: knitr source.ver: src/contrib/interactiveDisplay_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/interactiveDisplay_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/interactiveDisplay_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/interactiveDisplay_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/interactiveDisplay_1.2.0.tgz vignettes: vignettes/interactiveDisplay/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/interactiveDisplay/inst/doc/interactiveDisplay.R htmlDocs: vignettes/interactiveDisplay/inst/doc/interactiveDisplay.html htmlTitles: "Using interactiveDisplay for Bioconductor object visualization and modification" importsMe: AnnotationHub Package: inveRsion Version: 1.12.1 Depends: methods, haplo.stats Imports: graphics, methods, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 7f0c130d4cce9226b47edc74fb77adb8 NeedsCompilation: yes Title: Inversions in genotype data Description: Package to find genetic inversions in genotype (SNP array) data. biocViews: Microarray, SNP Author: Alejandro Caceres Maintainer: Alejandro Caceres source.ver: src/contrib/inveRsion_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/inveRsion_1.12.1.zip win64.binary.ver: bin/windows64/contrib/3.1/inveRsion_1.12.1.zip mac.binary.ver: bin/macosx/contrib/3.1/inveRsion_1.12.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/inveRsion_1.12.1.tgz vignettes: vignettes/inveRsion/inst/doc/inveRsion.pdf vignetteTitles: Quick start guide for inveRsion package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inveRsion/inst/doc/inveRsion.R Package: iontree Version: 1.10.0 Depends: methods, rJava, RSQLite, XML Suggests: iontreeData License: GPL-2 MD5sum: 0278c1fe8ed5a975b404727fde28c896 NeedsCompilation: no Title: Data management and analysis of ion trees from ion-trap mass spectrometry Description: Ion fragmentation provides structural information for metabolite identification. This package provides utility functions to manage and analyse MS2/MS3 fragmentation data from ion trap mass spectrometry. It was designed for high throughput metabolomics data with many biological samples and a large numer of ion trees collected. Tests have been done with data from low-resolution mass spectrometry but could be readily extended to precursor ion based fragmentation data from high resoultion mass spectrometry. biocViews: Metabolomics, MassSpectrometry Author: Mingshu Cao Maintainer: Mingshu Cao source.ver: src/contrib/iontree_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iontree_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iontree_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iontree_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iontree_1.10.0.tgz vignettes: vignettes/iontree/inst/doc/iontree_doc.pdf vignetteTitles: MSn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/iontree/inst/doc/iontree_doc.R Package: iPAC Version: 1.8.0 Depends: R(>= 2.15),gdata, scatterplot3d, Biostrings, multtest License: GPL-2 MD5sum: 9bd24ebdc48f682d1e5694de5d5cf306 NeedsCompilation: no Title: Identification of Protein Amino acid Clustering Description: iPAC is a novel tool to identify somatic amino acid mutation clustering within proteins while taking into account protein structure. biocViews: Clustering, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/iPAC_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iPAC_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iPAC_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iPAC_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iPAC_1.8.0.tgz vignettes: vignettes/iPAC/inst/doc/iPAC.pdf vignetteTitles: iPAC: identification of Protein Amino acid Mutations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iPAC/inst/doc/iPAC.R Package: IPPD Version: 1.12.0 Depends: R (>= 2.12.0), MASS, Matrix, XML, digest, bitops Imports: methods, stats, graphics License: GPL (version 2 or later) Archs: i386, x64 MD5sum: 9356472c325191fa1fcc856ca15930dd NeedsCompilation: yes Title: Isotopic peak pattern deconvolution for Protein Mass Spectrometry by template matching Description: The package provides functionality to extract isotopic peak patterns from raw mass spectra. This is done by fitting a large set of template basis functions to the raw spectrum using either nonnegative least squares or least absolute deviation fittting. The package offers a flexible function which tries to estimate model parameters in a way tailored to the peak shapes in the data. The package also provides functionality to process LCMS runs. biocViews: Proteomics Author: Martin Slawski , Rene Hussong , Matthias Hein Maintainer: Martin Slawski source.ver: src/contrib/IPPD_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/IPPD_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/IPPD_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/IPPD_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/IPPD_1.12.0.tgz vignettes: vignettes/IPPD/inst/doc/IPPD.pdf vignetteTitles: IPPD Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IPPD/inst/doc/IPPD.R Package: IRanges Version: 1.22.10 Depends: R (>= 3.1.0), methods, utils, stats, BiocGenerics (>= 0.9.1) Imports: methods, utils, stats, BiocGenerics, stats4 Suggests: XVector, GenomicRanges, BSgenome.Celegans.UCSC.ce2, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: a59804d89234a109f4c33c08ffdc0acd NeedsCompilation: yes Title: Infrastructure for manipulating intervals on sequences Description: The package provides efficient low-level and highly reusable S4 classes for storing ranges of integers, RLE vectors (Run-Length Encoding), and, more generally, data that can be organized sequentially (formally defined as Vector objects), as well as views on these Vector objects. Efficient list-like classes are also provided for storing big collections of instances of the basic classes. All classes in the package use consistent naming and share the same rich and consistent "Vector API" as much as possible. biocViews: Infrastructure, DataRepresentation Author: H. Pages, P. Aboyoun and M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/IRanges_1.22.10.tar.gz win.binary.ver: bin/windows/contrib/3.1/IRanges_1.22.10.zip win64.binary.ver: bin/windows64/contrib/3.1/IRanges_1.22.10.zip mac.binary.ver: bin/macosx/contrib/3.1/IRanges_1.22.10.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/IRanges_1.22.10.tgz vignettes: vignettes/IRanges/inst/doc/IRangesOverview.pdf, vignettes/IRanges/inst/doc/RleTricks.pdf vignetteTitles: An Introduction to IRanges, Rle Tips and Tricks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IRanges/inst/doc/IRangesOverview.R, vignettes/IRanges/inst/doc/RleTricks.R dependsOnMe: AnnotationHub, BayesPeak, biomvRCNS, Biostrings, BiSeq, BSgenome, bsseq, bumphunter, CAFE, casper, CexoR, ChIPpeakAnno, chipseq, chroGPS, cn.mops, CSAR, customProDB, DASiR, deepSNV, DESeq2, DEXSeq, DirichletMultinomial, DNaseR, epigenomix, exomeCopy, genomes, GenomicAlignments, GenomicFeatures, GenomicRanges, Genominator, genoset, girafe, HiTC, HMMcopy, htSeqTools, methyAnalysis, MotifDb, motifRG, nucleR, oneChannelGUI, PING, PSICQUIC, RefNet, rfPred, rGADEM, RIPSeeker, rMAT, Rsamtools, rSFFreader, scsR, segmentSeq, SomatiCA, SplicingGraphs, TEQC, triform, triplex, VariantTools, XVector importsMe: AllelicImbalance, annmap, AnnotationDbi, ArrayExpressHTS, BayesPeak, beadarray, Biostrings, biovizBase, BiSeq, BitSeq, BSgenome, CAGEr, charm, chipenrich, ChIPQC, ChIPseeker, chipseq, ChIPseqR, ChIPsim, ChromHeatMap, cleaver, CNEr, cn.mops, CNVrd2, cobindR, copynumber, customProDB, DECIPHER, DiffBind, easyRNASeq, EDASeq, epivizr, fastseg, flipflop, flowQ, FunciSNP, gCMAPWeb, GenomicAlignments, GenomicRanges, ggbio, GGtools, girafe, gmapR, GOTHiC, Gviz, gwascat, h5vc, HTSeqGenie, HTSFilter, intansv, MEDIPS, MeSHDbi, methVisual, methyAnalysis, MethylSeekR, minfi, MinimumDistance, mosaics, MotIV, MSnbase, NarrowPeaks, nucleR, oligoClasses, OTUbase, pdInfoBuilder, PICS, plethy, prebs, QuasR, R453Plus1Toolbox, Rariant, Rcade, REDseq, Repitools, ReportingTools, rGADEM, rMAT, rnaSeqMap, roar, Rolexa, rSFFreader, RSVSim, RTN, rtracklayer, segmentSeq, SeqArray, SeqVarTools, ShortRead, SomatiCA, SomaticSignatures, spliceR, SplicingGraphs, TFBSTools, triform, TSSi, VanillaICE, VariantAnnotation, VariantFiltering, waveTiling, XVector suggestsMe: BaseSpaceR, BiocGenerics, GenomeInfoDb, GenomicFiles, HilbertVis, HilbertVisGUI, MiRaGE, SNPchip Package: iSeq Version: 1.16.0 Depends: R (>= 2.10.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: a240d86badeab21e2549b329944c1ce5 NeedsCompilation: yes Title: Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models Description: This package uses Bayesian hidden Ising models to identify IP-enriched genomic regions from ChIP-seq data. It can be used to analyze ChIP-seq data with and without controls and replicates. biocViews: ChIPSeq, Sequencing Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iSeq_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iSeq_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iSeq_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iSeq_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iSeq_1.16.0.tgz vignettes: vignettes/iSeq/inst/doc/iSeq.pdf vignetteTitles: iSeq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iSeq/inst/doc/iSeq.R Package: isobar Version: 1.10.0 Depends: R (>= 2.10.0), Biobase, stats, methods, plyr Imports: distr Suggests: MSnbase, OrgMassSpecR, XML, biomaRt, ggplot2, RJSONIO, Hmisc, gplots, RColorBrewer, gridExtra, limma, boot, distr, Rgbp, DBI, MASS License: LGPL-2 MD5sum: a6510ad27bef64100affc645c9d0211f NeedsCompilation: no Title: Analysis and quantitation of isobarically tagged MSMS proteomics data Description: isobar provides methods for preprocessing, normalization, and report generation for the analysis of quantitative mass spectrometry proteomics data labeled with isobaric tags, such as iTRAQ and TMT. Features modules for integrating and validating PTM-centric datasets (isobar-PTM). More information on http://www.ms-isobar.org. biocViews: Proteomics, MassSpectrometry, Bioinformatics, MultipleComparisons, QualityControl Author: Florian P Breitwieser and Jacques Colinge , with contributions from Xavier Robin and Florent Gluck Maintainer: Florian P Breitwieser URL: http://www.ms-isobar.org source.ver: src/contrib/isobar_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/isobar_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/isobar_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/isobar_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/isobar_1.10.0.tgz vignettes: vignettes/isobar/inst/doc/isobar-devel.pdf, vignettes/isobar/inst/doc/isobar.pdf, vignettes/isobar/inst/doc/isobar-ptm.pdf vignetteTitles: isobar for developers, isobar package for iTRAQ and TMT protein quantification, isobar for quantification of PTM datasets hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/isobar/inst/doc/isobar-devel.R, vignettes/isobar/inst/doc/isobar-ptm.R, vignettes/isobar/inst/doc/isobar.R Package: IsoGeneGUI Version: 1.20.0 Depends: tcltk, tkrplot, IsoGene Imports: multtest, relimp, WriteXLS,gdata, RColorBrewer, geneplotter Suggests: RUnit License: GPL-2 MD5sum: b8f2fc990a881b935ac862e7701ac6d2 NeedsCompilation: no Title: A graphical user interface to conduct a dose-response analysis of microarray data Description: The IsoGene Graphical User Interface (IsoGene-GUI) is a user friendly interface of the IsoGene package which is aimed to identify for genes with a monotonic trend in the expression levels with respect to the increasing doses using several test statistics: global likelihood ratio test (E2), Bartholomew 1961, Barlow et al. 1972 and Robertson et al. 1988), Williams (1971, 1972), Marcus (1976), the M (Hu et al. 2005) and the modified M (Lin et al. 2007). The p-values of the global likelihood ratio test (E2) are obtained using the excat distribution and permutation. The other four test statistics are obtained using permutation . Several p-values adjustment are provided: Bonferroni, Holm (1979), Hochberg (1988), and Sidak procedures for controlling the family-wise Type I error rate (FWER), and BH (Benjamini and Hochberg 1995) and BY (Benjamini and Yekutieli 2001) procedures are used for controlling the FDR. the inference is based on resampling methods, which control the False Discovery Rate (FDR) (both permutations (Ge et al., 2003) and the Significance Analysis of Microarrays (SAM), Tusher et al., 2001). biocViews: Microarray, DifferentialExpression, GUI Author: Setia Pramana, Dan Lin, Philippe Haldermans, Tobias Verbeke Maintainer: Setia Pramana URL: http://www.ibiostat.be/software/IsoGeneGUI/index.html source.ver: src/contrib/IsoGeneGUI_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/IsoGeneGUI_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/IsoGeneGUI_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/IsoGeneGUI_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/IsoGeneGUI_1.20.0.tgz vignettes: vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.pdf vignetteTitles: IsoGeneGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.R Package: ITALICS Version: 2.24.0 Depends: R (>= 2.0.0), GLAD, ITALICSData, oligo, affxparser, pd.mapping50k.xba240 Imports: affxparser, DBI, GLAD, oligo, oligoClasses, stats Suggests: pd.mapping50k.hind240, pd.mapping250k.sty, pd.mapping250k.nsp License: GPL-2 MD5sum: 805ad4f9e4e09b4cd753d54e9823c4da NeedsCompilation: no Title: ITALICS Description: A Method to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set biocViews: Microarray, CopyNumberVariation Author: Guillem Rigaill, Philippe Hupe Maintainer: Guillem Rigaill URL: http://bioinfo.curie.fr source.ver: src/contrib/ITALICS_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ITALICS_2.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ITALICS_2.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ITALICS_2.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ITALICS_2.24.0.tgz vignettes: vignettes/ITALICS/inst/doc/ITALICS.pdf vignetteTitles: ITALICS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ITALICS/inst/doc/ITALICS.R Package: iterativeBMA Version: 1.22.0 Depends: BMA, leaps, Biobase (>= 2.5.5) License: GPL (>= 2) MD5sum: 762d124af7f331de01b22d5ef35974d6 NeedsCompilation: no Title: The Iterative Bayesian Model Averaging (BMA) algorithm Description: The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402). biocViews: Microarray, Classification Author: Ka Yee Yeung, University of Washington, Seattle, WA, with contributions from Adrian Raftery and Ian Painter Maintainer: Ka Yee Yeung URL: http://faculty.washington.edu/kayee/research.html source.ver: src/contrib/iterativeBMA_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iterativeBMA_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iterativeBMA_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iterativeBMA_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iterativeBMA_1.22.0.tgz vignettes: vignettes/iterativeBMA/inst/doc/iterativeBMA.pdf vignetteTitles: The Iterative Bayesian Model Averaging Algorithm hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iterativeBMA/inst/doc/iterativeBMA.R Package: iterativeBMAsurv Version: 1.22.0 Depends: BMA, leaps, survival, splines Imports: graphics, grDevices, stats, survival, utils License: GPL (>= 2) MD5sum: 8a71df1a3daae7fbe5fbbf67b2132fe4 NeedsCompilation: no Title: The Iterative Bayesian Model Averaging (BMA) Algorithm For Survival Analysis Description: The iterative Bayesian Model Averaging (BMA) algorithm for survival analysis is a variable selection method for applying survival analysis to microarray data. biocViews: Microarray Author: Amalia Annest, University of Washington, Tacoma, WA Ka Yee Yeung, University of Washington, Seattle, WA Maintainer: Ka Yee Yeung URL: http://expression.washington.edu/ibmasurv/protected source.ver: src/contrib/iterativeBMAsurv_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/iterativeBMAsurv_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/iterativeBMAsurv_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/iterativeBMAsurv_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/iterativeBMAsurv_1.22.0.tgz vignettes: vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.pdf vignetteTitles: The Iterative Bayesian Model Averaging Algorithm For Survival Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/iterativeBMAsurv/inst/doc/iterativeBMAsurv.R Package: jmosaics Version: 1.4.0 Depends: R (>= 2.15.2), mosaics License: GPL (>= 2) MD5sum: 705fd59ddea55750045b9507fc6099dc NeedsCompilation: no Title: Joint analysis of multiple ChIP-Seq data sets Description: jmosaics detects enriched regions of ChIP-seq data sets jointly. biocViews: ChIPSeq, Sequencing, Transcription, Genetics Author: Xin Zeng Maintainer: Xin Zeng source.ver: src/contrib/jmosaics_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/jmosaics_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/jmosaics_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/jmosaics_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/jmosaics_1.4.0.tgz vignettes: vignettes/jmosaics/inst/doc/jmosaics.pdf vignetteTitles: jMOSAiCS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/jmosaics/inst/doc/jmosaics.R Package: joda Version: 1.12.0 Depends: R (>= 2.0), bgmm, RBGL License: GPL (>= 2) MD5sum: 96902c2de63a8067decb319f040286e8 NeedsCompilation: no Title: JODA algorithm for quantifying gene deregulation using knowledge Description: Package 'joda' implements three steps of an algorithm called JODA. The algorithm computes gene deregulation scores. For each gene, its deregulation score reflects how strongly an effect of a certain regulator's perturbation on this gene differs between two different cell populations. The algorithm utilizes regulator knockdown expression data as well as knowledge about signaling pathways in which the regulators are involved (formalized in a simple matrix model). biocViews: Microarray, Pathways, GraphAndNetwork, StatisticalMethod, NetworkInference Author: Ewa Szczurek Maintainer: Ewa Szczurek URL: http://www.bioconductor.org source.ver: src/contrib/joda_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/joda_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/joda_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/joda_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/joda_1.12.0.tgz vignettes: vignettes/joda/inst/doc/JodaVignette.pdf vignetteTitles: Introduction to joda hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/joda/inst/doc/JodaVignette.R Package: KCsmart Version: 2.22.0 Depends: siggenes, multtest, KernSmooth Imports: methods, BiocGenerics Enhances: Biobase, CGHbase License: GPL-3 MD5sum: e8bfaabb7e803aca4ed681d2cdd01e3e NeedsCompilation: no Title: Multi sample aCGH analysis package using kernel convolution Description: Multi sample aCGH analysis package using kernel convolution biocViews: CopyNumberVariation, Visualization, aCGH, Microarray Author: Jorma de Ronde, Christiaan Klijn, Arno Velds Maintainer: Jorma de Ronde source.ver: src/contrib/KCsmart_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/KCsmart_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/KCsmart_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/KCsmart_2.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/KCsmart_2.22.0.tgz vignettes: vignettes/KCsmart/inst/doc/KCS.pdf vignetteTitles: KCsmart example session hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KCsmart/inst/doc/KCS.R Package: KEGGgraph Version: 1.22.1 Depends: R (>= 2.10), methods, XML (>= 2.3-0), graph Imports: methods, XML, graph Suggests: Rgraphviz, RBGL, RUnit, RColorBrewer, KEGG.db, org.Hs.eg.db, hgu133plus2.db, SPIA License: GPL (>= 2) MD5sum: 3ae43174602b2c6ff53bad4c2ff8944e NeedsCompilation: no Title: KEGGgraph: A graph approach to KEGG PATHWAY in R and Bioconductor Description: KEGGGraph is an interface between KEGG pathway and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated KGML (KEGG XML) files into graph models maintaining all essential pathway attributes. The package offers functionalities including parsing, graph operation, visualization and etc. biocViews: Pathways, GraphAndNetwork, Visualization Author: Jitao David Zhang, with inputs from Paul Shannon Maintainer: Jitao David Zhang URL: http://www.nextbiomotif.com source.ver: src/contrib/KEGGgraph_1.22.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/KEGGgraph_1.22.1.zip win64.binary.ver: bin/windows64/contrib/3.1/KEGGgraph_1.22.1.zip mac.binary.ver: bin/macosx/contrib/3.1/KEGGgraph_1.22.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/KEGGgraph_1.22.1.tgz vignettes: vignettes/KEGGgraph/inst/doc/KEGGgraphApp.pdf, vignettes/KEGGgraph/inst/doc/KEGGgraph.pdf vignetteTitles: KEGGgraph: Application Examples, KEGGgraph: graph approach to KEGG PATHWAY hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGgraph/inst/doc/KEGGgraphApp.R, vignettes/KEGGgraph/inst/doc/KEGGgraph.R dependsOnMe: pathview, ROntoTools, SPIA importsMe: clipper, DEGraph, NCIgraph suggestsMe: DEGraph, GenomicRanges Package: keggorthology Version: 2.16.1 Depends: R (>= 2.5.0),stats,graph,hgu95av2.db Imports: AnnotationDbi,graph,DBI, graph, grDevices, methods, stats, tools, utils Suggests: RBGL,ALL License: Artistic-2.0 MD5sum: 5a4c7e263f69bb8b9d461212218c4120 NeedsCompilation: no Title: graph support for KO, KEGG Orthology Description: graphical representation of the Feb 2010 KEGG Orthology. The KEGG orthology is a set of pathway IDs that are not to be confused with the KEGG ortholog IDs. biocViews: Pathways, GraphAndNetwork, Visualization Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/keggorthology_2.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/keggorthology_2.16.1.zip win64.binary.ver: bin/windows64/contrib/3.1/keggorthology_2.16.1.zip mac.binary.ver: bin/macosx/contrib/3.1/keggorthology_2.16.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/keggorthology_2.16.1.tgz vignettes: vignettes/keggorthology/inst/doc/keggorth.pdf vignetteTitles: keggorthology overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/keggorthology/inst/doc/keggorth.R suggestsMe: MLInterfaces Package: KEGGprofile Version: 1.7.6 Imports: AnnotationDbi,png,TeachingDemos,XML,KEGG.db,KEGGREST,biomaRt License: GPL (>= 2) MD5sum: 5381c008f25b6e6f1c3e9d2aa5d49ab4 NeedsCompilation: no Title: An annotation and visualization package for multi-types and multi-groups expression data in KEGG pathway Description: KEGGprofile is an annotation and visualization tool which integrated the expression profiles and the function annotation in KEGG pathway maps. The multi-types and multi-groups expression data can be visualized in one pathway map. KEGGprofile facilitated more detailed analysis about the specific function changes inner pathway or temporal correlations in different genes and samples. biocViews: Pathways Author: Shilin Zhao, Yu Shyr Maintainer: Shilin Zhao source.ver: src/contrib/KEGGprofile_1.7.6.tar.gz win.binary.ver: bin/windows/contrib/3.1/KEGGprofile_1.7.6.zip win64.binary.ver: bin/windows64/contrib/3.1/KEGGprofile_1.7.6.zip mac.binary.ver: bin/macosx/contrib/3.1/KEGGprofile_1.7.6.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/KEGGprofile_1.7.6.tgz vignettes: vignettes/KEGGprofile/inst/doc/KEGGprofile.pdf vignetteTitles: KEGGprofile: Application Examples hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGprofile/inst/doc/KEGGprofile.R Package: KEGGREST Version: 1.4.1 Imports: methods, httr, png, Biostrings Suggests: RUnit, BiocGenerics, knitr License: Artistic-2.0 MD5sum: 86e45f7234415af3131128c9c7ea5582 NeedsCompilation: no Title: Client-side REST access to KEGG Description: A package that provides a client interface to the KEGG REST server. Based on KEGGSOAP by J. Zhang, R. Gentleman, and Marc Carlson, and KEGG (python package) by Aurelien Mazurie. biocViews: Annotation, Pathways, ThirdPartyClient Author: Dan Tenenbaum Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/KEGGREST_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/KEGGREST_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/KEGGREST_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/KEGGREST_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/KEGGREST_1.4.1.tgz vignettes: vignettes/KEGGREST/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGREST/inst/doc/KEGGREST-vignette.R htmlDocs: vignettes/KEGGREST/inst/doc/KEGGREST-vignette.html htmlTitles: "Accessing the KEGG REST API" dependsOnMe: PAPi, ROntoTools importsMe: gage, mmnet, pathview Package: lapmix Version: 1.30.0 Depends: R (>= 2.6.0),stats Imports: Biobase, graphics, grDevices, methods, stats, tools, utils License: GPL (>= 2) MD5sum: 21f0b14260af432eadc381fe4ee3e36c NeedsCompilation: no Title: Laplace Mixture Model in Microarray Experiments Description: Laplace mixture modelling of microarray experiments. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes. The main purpose is to identify differentially expressed genes. biocViews: Microarray, OneChannel, DifferentialExpression Author: Yann Ruffieux, contributions from Debjani Bhowmick, Anthony C. Davison, and Darlene R. Goldstein Maintainer: Yann Ruffieux URL: http://www.r-project.org, http://www.bioconductor.org, http://stat.epfl.ch source.ver: src/contrib/lapmix_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/lapmix_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/lapmix_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/lapmix_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/lapmix_1.30.0.tgz vignettes: vignettes/lapmix/inst/doc/lapmix-example.pdf vignetteTitles: lapmix example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lapmix/inst/doc/lapmix-example.R Package: LBE Version: 1.32.0 Depends: stats Imports: graphics, grDevices, methods, stats, utils Suggests: qvalue License: GPL-2 MD5sum: d2f392ba29b13368bbe108f998437690 NeedsCompilation: no Title: Estimation of the false discovery rate. Description: LBE is an efficient procedure for estimating the proportion of true null hypotheses, the false discovery rate (and so the q-values) in the framework of estimating procedures based on the marginal distribution of the p-values without assumption for the alternative hypothesis. biocViews: MultipleComparison Author: Cyril Dalmasso Maintainer: Cyril Dalmasso source.ver: src/contrib/LBE_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/LBE_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/LBE_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/LBE_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LBE_1.32.0.tgz vignettes: vignettes/LBE/inst/doc/LBE.pdf vignetteTitles: LBE Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LBE/inst/doc/LBE.R Package: les Version: 1.14.0 Depends: R (>= 2.13.2), methods, graphics, fdrtool Imports: boot, gplots, RColorBrewer Suggests: Biobase, limma Enhances: parallel License: GPL-3 MD5sum: d86978958ed5423699571031422257e7 NeedsCompilation: no Title: Identifying Differential Effects in Tiling Microarray Data Description: The 'les' package estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes. biocViews: Microarray, DifferentialExpression, ChIPchip, DNAMethylation, Transcription Author: Julian Gehring, Clemens Kreutz, Jens Timmer Maintainer: Julian Gehring URL: http://julian-gehring.github.com/les/ source.ver: src/contrib/les_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/les_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/les_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/les_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/les_1.14.0.tgz vignettes: vignettes/les/inst/doc/les.pdf vignetteTitles: Introduction to the les package: Identifying Differential Effects in Tiling Microarray Data with the Loci of Enhanced Significance Framework hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/les/inst/doc/les.R importsMe: GSRI Package: limma Version: 3.20.9 Depends: R (>= 2.3.0), methods Suggests: statmod (>= 1.2.2), splines, locfit, MASS, ellipse, affy, vsn, AnnotationDbi, org.Hs.eg.db, illuminaio License: GPL (>=2) Archs: i386, x64 MD5sum: 6b7f93883b539ee041188c817240263b NeedsCompilation: yes Title: Linear Models for Microarray Data Description: Data analysis, linear models and differential expression for microarray data. biocViews: ExonArray, GeneExpression, Transcription, AlternativeSplicing, DifferentialExpression, DifferentialSplicing, GeneSetEnrichment, DataImport, Genetics, Bayesian, Clustering, Regression, TimeCourse, Microarray, microRNAArray, mRNAMicroarray, OneChannel, ProprietaryPlatforms, TwoChannel, RNASeq, BatchEffect, MultipleComparison, Normalization, Preprocessing, QualityControl Author: Gordon Smyth [cre,aut], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Natalie Thorne [ctb], Davis McCarthy [ctb], Di Wu [ctb], Yifang Hu [ctb], Wei Shi [ctb], Belinda Phipson [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb] Maintainer: Gordon Smyth URL: http://bioinf.wehi.edu.au/limma source.ver: src/contrib/limma_3.20.9.tar.gz win.binary.ver: bin/windows/contrib/3.1/limma_3.20.9.zip win64.binary.ver: bin/windows64/contrib/3.1/limma_3.20.9.zip mac.binary.ver: bin/macosx/contrib/3.1/limma_3.20.9.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/limma_3.20.9.tgz vignettes: vignettes/limma/inst/doc/intro.pdf, vignettes/limma/inst/doc/usersguide.pdf vignetteTitles: Limma One Page Introduction, usersguide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/limma/inst/doc/intro.R, vignettes/limma/inst/doc/limma.R dependsOnMe: a4Base, AffyExpress, affylmGUI, attract, birta, CALIB, cghMCR, codelink, convert, COPDSexualDimorphism, Cormotif, coRNAi, DiffBind, DMRcate, DrugVsDisease, edgeR, ExiMiR, gCMAP, HTqPCR, limmaGUI, maigesPack, marray, metagenomeSeq, metaseqR, MLSeq, MmPalateMiRNA, nem, PADOG, qpcrNorm, qusage, Ringo, snapCGH, SSPA, tRanslatome, TurboNorm, wateRmelon importsMe: affycoretools, ArrayExpress, arrayQuality, arrayQualityMetrics, ArrayTools, attract, beadarray, betr, bumphunter, CALIB, CancerMutationAnalysis, ChAMP, charm, ChIPpeakAnno, compcodeR, explorase, flowBin, GeneSelectMMD, GeneSelector, GGBase, HTqPCR, iChip, lmdme, LVSmiRNA, maSigPro, minfi, MmPalateMiRNA, OLIN, PADOG, PECA, phenoTest, PhenStat, Ringo, RNAinteract, RNAither, RTN, RTopper, SimBindProfiles, snapCGH, timecourse, tweeDEseq, vsn suggestsMe: ABarray, ADaCGH2, beadarraySNP, BiocCaseStudies, BioNet, Category, categoryCompare, CMA, coGPS, dyebias, ELBOW, gage, GeneSelector, GEOquery, GSRI, GSVA, Heatplus, inSilicoDb, isobar, les, lumi, methylumi, MLP, npGSEA, oligo, oneChannelGUI, PGSEA, piano, plw, PREDA, puma, Rcade, RTopper, rtracklayer, virtualArray Package: limmaGUI Version: 1.40.0 Depends: limma, tcltk Suggests: statmod, R2HTML, xtable, tkrplot License: LGPL MD5sum: c988af0820a62c28135ab052051c9ce9 NeedsCompilation: no Title: GUI for limma package Description: A Graphical User Interface for the limma Microarray package biocViews: Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, DifferentialExpression, MultipleComparison, GUI Author: James Wettenhall Division of Genetics and Bioinformatics, WEHI Maintainer: Keith Satterley URL: http://bioinf.wehi.edu.au/limmaGUI/ source.ver: src/contrib/limmaGUI_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/limmaGUI_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/limmaGUI_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/limmaGUI_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/limmaGUI_1.40.0.tgz vignettes: vignettes/limmaGUI/inst/doc/extract.pdf, vignettes/limmaGUI/inst/doc/limmaGUI.pdf vignetteTitles: Extracting limma objects from limmaGUI files, limmaGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/limmaGUI/inst/doc/extract.R, vignettes/limmaGUI/inst/doc/limmaGUI.R htmlDocs: vignettes/limmaGUI/inst/doc/about.html, vignettes/limmaGUI/inst/doc/CustMenu.html, vignettes/limmaGUI/inst/doc/import.html, vignettes/limmaGUI/inst/doc/index.html, vignettes/limmaGUI/inst/doc/InputFiles.html, vignettes/limmaGUI/inst/doc/lgDevel.html, vignettes/limmaGUI/inst/doc/windowsFocus.html htmlTitles: "About limmaGUI", "Customizing the menus in limmaGUI (for Advanced users)", "Importing MA Data into LimmaGUI", "limmaGUI Documentation", "InputFiles.html", "LimmaGUI Developers' Guide", "Troubleshooting Window Focus Problems" Package: LiquidAssociation Version: 1.18.0 Depends: geepack, methods, yeastCC, org.Sc.sgd.db Imports: Biobase, graphics, grDevices, methods, stats License: GPL (>=3) MD5sum: 6deba0c66419cb071134ef9a3e0fc364 NeedsCompilation: no Title: LiquidAssociation Description: The package contains functions for calculate direct and model-based estimators for liquid association. It also provides functions for testing the existence of liquid association given a gene triplet data. biocViews: Pathways, GeneExpression, CellBiology, Genetics, Network, TimeCourse Author: Yen-Yi Ho Maintainer: Yen-Yi Ho source.ver: src/contrib/LiquidAssociation_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/LiquidAssociation_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/LiquidAssociation_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/LiquidAssociation_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LiquidAssociation_1.18.0.tgz vignettes: vignettes/LiquidAssociation/inst/doc/LiquidAssociation.pdf vignetteTitles: LiquidAssociation Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LiquidAssociation/inst/doc/LiquidAssociation.R dependsOnMe: fastLiquidAssociation Package: lmdme Version: 1.6.0 Depends: R (>= 2.14.1), pls, stemHypoxia Imports: stats, methods, limma Enhances: parallel License: GPL (>=2) MD5sum: 11bbbcd2dfc119cffb007ff16b6fafc5 NeedsCompilation: no Title: Linear Model decomposition for Designed Multivariate Experiments Description: linear ANOVA decomposition of Multivariate Designed Experiments implementation based on limma lmFit. Features: i)Flexible formula type interface, ii) Fast limma based implementation, iii) p-values for each estimated coefficient levels in each factor, iv) F values for factor effects and v) plotting functions for PCA and PLS. biocViews: Microarray, OneChannel, TwoChannel, Visualization, DifferentialExpression, ExperimentData, Cancer Author: Cristobal Fresno and Elmer A. Fernandez Maintainer: Cristobal Fresno URL: http://www.bdmg.com.ar/?page_id=38 source.ver: src/contrib/lmdme_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/lmdme_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/lmdme_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/lmdme_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/lmdme_1.6.0.tgz vignettes: vignettes/lmdme/inst/doc/lmdme-vignette.pdf vignetteTitles: lmdme: linear model framework for PCA/PLS analysis of ANOVA decomposition on Designed Multivariate Experiments in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lmdme/inst/doc/lmdme-vignette.R Package: LMGene Version: 2.20.0 Depends: R (>= 2.10.0), Biobase (>= 2.5.5), multtest, survival, affy Suggests: affydata License: LGPL MD5sum: 9bc838b16a81397220117e9bd030d5a3 NeedsCompilation: no Title: LMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays Description: LMGene package for analysis of microarray data using a linear model and glog data transformation biocViews: Microarray, DifferentialExpression, Preprocessing Author: David Rocke, Geun Cheol Lee, John Tillinghast, Blythe Durbin-Johnson, and Shiquan Wu Maintainer: Blythe Durbin-Johnson URL: http://dmrocke.ucdavis.edu/software.html source.ver: src/contrib/LMGene_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/LMGene_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/LMGene_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/LMGene_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LMGene_2.20.0.tgz vignettes: vignettes/LMGene/inst/doc/LMGene.pdf vignetteTitles: LMGene User's Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LMGene/inst/doc/LMGene.R Package: logicFS Version: 1.34.0 Depends: LogicReg, mcbiopi Suggests: genefilter, siggenes License: LGPL (>= 2) MD5sum: d9062dd896a1a464bbf24fd82b59b6ed NeedsCompilation: no Title: Identification of SNP Interactions Description: Identification of interactions between binary variables using Logic Regression. Can, e.g., be used to find interesting SNP interactions. Contains also a bagging version of logic regression for classification. biocViews: SNP, Classification, Genetics Author: Holger Schwender Maintainer: Holger Schwender source.ver: src/contrib/logicFS_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/logicFS_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/logicFS_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/logicFS_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/logicFS_1.34.0.tgz vignettes: vignettes/logicFS/inst/doc/logicFS.pdf vignetteTitles: logicFS Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/logicFS/inst/doc/logicFS.R suggestsMe: trio Package: logitT Version: 1.22.0 Depends: affy Suggests: SpikeInSubset License: GPL (>= 2) Archs: i386, x64 MD5sum: 78440a8e4b608e6c96f0acf18e59d1a1 NeedsCompilation: yes Title: logit-t Package Description: The logitT library implements the Logit-t algorithm introduced in --A high performance test of differential gene expression for oligonucleotide arrays-- by William J Lemon, Sandya Liyanarachchi and Ming You for use with Affymetrix data stored in an AffyBatch object in R. biocViews: Microarray, DifferentialExpression Author: Tobias Guennel Maintainer: Tobias Guennel URL: http://www.bioconductor.org source.ver: src/contrib/logitT_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/logitT_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/logitT_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/logitT_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/logitT_1.22.0.tgz vignettes: vignettes/logitT/inst/doc/logitT.pdf vignetteTitles: logitT primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/logitT/inst/doc/logitT.R Package: lol Version: 1.12.0 Depends: penalized, Matrix Imports: Matrix, penalized, graphics, grDevices, stats License: GPL-2 MD5sum: d2a173d3061d3f230b944f3a5e286b42 NeedsCompilation: no Title: Lots Of Lasso Description: Various optimization methods for Lasso inference with matrix warpper biocViews: StatisticalMethod Author: Yinyin Yuan Maintainer: Yinyin Yuan source.ver: src/contrib/lol_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/lol_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/lol_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/lol_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/lol_1.12.0.tgz vignettes: vignettes/lol/inst/doc/lol.pdf vignetteTitles: An introduction to the lol package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lol/inst/doc/lol.R Package: LPE Version: 1.38.0 Depends: R (>= 2.10) Imports: stats License: LGPL MD5sum: 0fb8d874cce73d50bda12ad282314795 NeedsCompilation: no Title: Methods for analyzing microarray data using Local Pooled Error (LPE) method Description: This LPE library is used to do significance analysis of microarray data with small number of replicates. It uses resampling based FDR adjustment, and gives less conservative results than traditional 'BH' or 'BY' procedures. Data accepted is raw data in txt format from MAS4, MAS5 or dChip. Data can also be supplied after normalization. LPE library is primarily used for analyzing data between two conditions. To use it for paired data, see LPEP library. For using LPE in multiple conditions, use HEM library. biocViews: Microarray, DifferentialExpression Author: Nitin Jain , Michael O'Connell , Jae K. Lee . Includes R source code contributed by HyungJun Cho Maintainer: Nitin Jain URL: http://www.r-project.org, http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/, http://sourceforge.net/projects/r-lpe/ source.ver: src/contrib/LPE_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/LPE_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/LPE_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/LPE_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LPE_1.38.0.tgz vignettes: vignettes/LPE/inst/doc/LPE.pdf vignetteTitles: LPE test for microarray data with small number of replicates hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LPE/inst/doc/LPE.R dependsOnMe: LPEadj, PLPE importsMe: LPEadj suggestsMe: ABarray Package: LPEadj Version: 1.24.0 Depends: LPE Imports: LPE, stats License: LGPL MD5sum: f5a95f72e36f9cf58332fa1efd5c53c5 NeedsCompilation: no Title: A correction of the local pooled error (LPE) method to replace the asymptotic variance adjustment with an unbiased adjustment based on sample size. Description: Two options are added to the LPE algorithm. The original LPE method sets all variances below the max variance in the ordered distribution of variances to the maximum variance. in LPEadj this option is turned off by default. The second option is to use a variance adjustment based on sample size rather than pi/2. By default the LPEadj uses the sample size based variance adjustment. biocViews: Microarray, Proteomics Author: Carl Murie , Robert Nadon Maintainer: Carl Murie source.ver: src/contrib/LPEadj_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/LPEadj_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/LPEadj_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/LPEadj_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LPEadj_1.24.0.tgz vignettes: vignettes/LPEadj/inst/doc/LPEadj.pdf vignetteTitles: LPEadj test for microarray data with small number of replicates hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LPEadj/inst/doc/LPEadj.R Package: lpNet Version: 1.4.0 Depends: lpSolve, nem License: Artistic License 2.0 MD5sum: d56d42d1269a4b555209601be6021a89 NeedsCompilation: no Title: Linear Programming Model for Network Inference Description: lpNet takes perturbation data as input and generates an LP model which allows the inference of signaling networks. For parameter identification either leave-one-out cross-validation or stratified n-fold cross-validation can be used. biocViews: Network Author: Bettina Knapp, Johanna Mazur, Lars Kaderali Maintainer: Bettina Knapp source.ver: src/contrib/lpNet_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/lpNet_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/lpNet_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/lpNet_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/lpNet_1.4.0.tgz vignettes: vignettes/lpNet/inst/doc/vignette_lpNet.pdf vignetteTitles: lpNet,, network inference with a linear optimization program. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lpNet/inst/doc/vignette_lpNet.R Package: lumi Version: 2.16.0 Depends: R (>= 2.10), Biobase (>= 2.5.5) Imports: affy (>= 1.23.4), methylumi (>= 2.3.2), GenomicFeatures, GenomicRanges, annotate, Biobase (>= 2.5.5), lattice, mgcv (>= 1.4-0), nleqslv, KernSmooth, preprocessCore, RSQLite, DBI, AnnotationDbi, MASS, graphics, stats, stats4, methods Suggests: beadarray, limma, vsn, lumiBarnes, lumiHumanAll.db, lumiHumanIDMapping, genefilter, RColorBrewer License: LGPL (>= 2) MD5sum: 2fb8f9f3e57fc7f6fdb2c0cc4c83ac27 NeedsCompilation: no Title: BeadArray Specific Methods for Illumina Methylation and Expression Microarrays Description: The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays. biocViews: Microarray, OneChannel, Preprocessing, DNAMethylation, QualityControl, TwoChannel Author: Pan Du, Richard Bourgon, Gang Feng, Simon Lin Maintainer: Pan Du source.ver: src/contrib/lumi_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/lumi_2.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/lumi_2.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/lumi_2.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/lumi_2.16.0.tgz vignettes: vignettes/lumi/inst/doc/IlluminaAnnotation.pdf, vignettes/lumi/inst/doc/lumi.pdf, vignettes/lumi/inst/doc/lumi_VST_evaluation.pdf, vignettes/lumi/inst/doc/methylationAnalysis.pdf vignetteTitles: Resolve the inconsistency of Illumina identifiers through nuID, Using lumi A package processing Illumina Microarray, Evaluation of VST algorithm in lumi package, Analyze Illumina Infinium methylation microarray data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/lumi/inst/doc/IlluminaAnnotation.R, vignettes/lumi/inst/doc/lumi.R, vignettes/lumi/inst/doc/lumi_VST_evaluation.R, vignettes/lumi/inst/doc/methylationAnalysis.R dependsOnMe: arrayMvout, wateRmelon importsMe: ffpe, methyAnalysis, MineICA suggestsMe: beadarray, methylumi, tigre, virtualArray Package: LVSmiRNA Version: 1.14.3 Depends: R (>= 3.1.0), methods, splines Imports: BiocGenerics, stats4, graphics, stats, utils, MASS, Biobase, quantreg, limma, affy, SparseM, vsn Enhances: parallel,snow, Rmpi License: GPL-2 Archs: i386, x64 MD5sum: f999ca6912a066445e32ea99b8378b72 NeedsCompilation: yes Title: LVS normalization for Agilent miRNA data Description: Normalization of Agilent miRNA arrays. biocViews: Microarray,AgilentChip,OneChannel,Preprocessing Author: Stefano Calza, Suo Chen, Yudi Pawitan Maintainer: Stefano Calza source.ver: src/contrib/LVSmiRNA_1.14.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/LVSmiRNA_1.14.3.zip win64.binary.ver: bin/windows64/contrib/3.1/LVSmiRNA_1.14.3.zip mac.binary.ver: bin/macosx/contrib/3.1/LVSmiRNA_1.14.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/LVSmiRNA_1.14.3.tgz vignettes: vignettes/LVSmiRNA/inst/doc/LVSmiRNA.pdf vignetteTitles: LVSmiRNA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/LVSmiRNA/inst/doc/LVSmiRNA.R Package: maanova Version: 1.34.1 Depends: R (>= 2.10) Imports: Biobase, graphics, grDevices, methods, stats, utils Suggests: qvalue, snow Enhances: Rmpi License: GPL (>= 2) Archs: i386, x64 MD5sum: e0b3df8908f9b1f5e8888d5a3be5b7db NeedsCompilation: yes Title: Tools for analyzing Micro Array experiments Description: Analysis of N-dye Micro Array experiment using mixed model effect. Containing analysis of variance, permutation and bootstrap, cluster and consensus tree. biocViews: Microarray, DifferentialExpression, Clustering Author: Hao Wu, modified by Hyuna Yang and Keith Sheppard with ideas from Gary Churchill, Katie Kerr and Xiangqin Cui. Maintainer: Keith Sheppard URL: http://research.jax.org/faculty/churchill source.ver: src/contrib/maanova_1.34.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/maanova_1.34.1.zip win64.binary.ver: bin/windows64/contrib/3.1/maanova_1.34.1.zip mac.binary.ver: bin/macosx/contrib/3.1/maanova_1.34.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maanova_1.34.1.tgz vignettes: vignettes/maanova/inst/doc/maanova.pdf vignetteTitles: R/maanova HowTo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maanova/inst/doc/maanova.R Package: macat Version: 1.38.0 Depends: Biobase, annotate Suggests: hgu95av2.db, stjudem License: Artistic-2.0 MD5sum: 20f845aa5e245b8ae4eb417da5b5820d NeedsCompilation: no Title: MicroArray Chromosome Analysis Tool Description: This library contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. MACAT is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions. The functions have been tested on a publicly available data set about acute lymphoblastic leukemia (Yeoh et al.Cancer Cell 2002), which is provided in the library 'stjudem'. biocViews: Microarray, DifferentialExpression, Visualization Author: Benjamin Georgi, Matthias Heinig, Stefan Roepcke, Sebastian Schmeier, Joern Toedling Maintainer: Joern Toedling source.ver: src/contrib/macat_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/macat_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/macat_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/macat_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/macat_1.38.0.tgz vignettes: vignettes/macat/inst/doc/macat.pdf vignetteTitles: MicroArray Chromosome Analysis Tool hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/macat/inst/doc/macat.R Package: maCorrPlot Version: 1.34.0 Depends: lattice Imports: graphics, grDevices, lattice, stats License: GPL (>= 2) MD5sum: 9a91023e4f094d55ebe0ec0da9c25725 NeedsCompilation: no Title: Visualize artificial correlation in microarray data Description: Graphically displays correlation in microarray data that is due to insufficient normalization biocViews: Microarray, Preprocessing, Visualization Author: Alexander Ploner Maintainer: Alexander Ploner URL: http://www.pubmedcentral.gov/articlerender.fcgi?tool=pubmed&pubmedid=15799785 source.ver: src/contrib/maCorrPlot_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/maCorrPlot_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/maCorrPlot_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/maCorrPlot_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maCorrPlot_1.34.0.tgz vignettes: vignettes/maCorrPlot/inst/doc/maCorrPlot.pdf vignetteTitles: maCorrPlot Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maCorrPlot/inst/doc/maCorrPlot.R Package: made4 Version: 1.38.0 Depends: ade4, RColorBrewer,gplots,scatterplot3d Suggests: affy License: Artistic-2.0 MD5sum: 9cf02854697053ea74d3c84f57837915 NeedsCompilation: no Title: Multivariate analysis of microarray data using ADE4 Description: Multivariate data analysis and graphical display of microarray data. Functions include between group analysis and coinertia analysis. It contains functions that require ADE4. biocViews: Clustering, Classification, MultipleComparison Author: Aedin Culhane Maintainer: Aedin Culhane URL: http://www.hsph.harvard.edu/aedin-culhane/ source.ver: src/contrib/made4_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/made4_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/made4_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/made4_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/made4_1.38.0.tgz vignettes: vignettes/made4/inst/doc/introduction.pdf vignetteTitles: introduction.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/made4/inst/doc/introduction.R dependsOnMe: bgafun importsMe: omicade4 Package: maigesPack Version: 1.28.1 Depends: R (>= 2.10), convert, graph, limma, marray, methods Suggests: amap, annotate, class, e1071, MASS, multtest, OLIN, R2HTML, rgl, som License: GPL (>= 2) Archs: i386, x64 MD5sum: 1ccce21dd467645f2baa53cffcf2c2be NeedsCompilation: yes Title: Functions to handle cDNA microarray data, including several methods of data analysis Description: This package uses functions of various other packages together with other functions in a coordinated way to handle and analyse cDNA microarray data biocViews: Microarray, TwoChannel, Preprocessing, ThirdPartyClient, DifferentialExpression, Clustering, Classification, GraphAndNetwork Author: Gustavo H. Esteves , with contributions from Roberto Hirata Jr , E. Jordao Neves , Elier B. Cristo , Ana C. Simoes and Lucas Fahham Maintainer: Gustavo H. Esteves URL: http://www.maiges.org/en/software/ source.ver: src/contrib/maigesPack_1.28.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/maigesPack_1.28.1.zip win64.binary.ver: bin/windows64/contrib/3.1/maigesPack_1.28.1.zip mac.binary.ver: bin/macosx/contrib/3.1/maigesPack_1.28.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maigesPack_1.28.1.tgz vignettes: vignettes/maigesPack/inst/doc/maigesPack_tutorial.pdf vignetteTitles: maigesPack Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maigesPack/inst/doc/maigesPack_tutorial.R Package: makecdfenv Version: 1.40.0 Depends: R (>= 2.6.0), affyio Imports: Biobase, affy, methods, stats, utils, zlibbioc License: GPL (>= 2) Archs: i386, x64 MD5sum: efdbbe43a0e1b08509d5a2fdd5635995 NeedsCompilation: yes Title: CDF Environment Maker Description: This package has two functions. One reads a Affymetrix chip description file (CDF) and creates a hash table environment containing the location/probe set membership mapping. The other creates a package that automatically loads that environment. biocViews: OneChannel, DataImport, Preprocessing Author: Rafael A. Irizarry , Laurent Gautier , Wolfgang Huber , Ben Bolstad Maintainer: James W. MacDonald source.ver: src/contrib/makecdfenv_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/makecdfenv_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/makecdfenv_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/makecdfenv_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/makecdfenv_1.40.0.tgz vignettes: vignettes/makecdfenv/inst/doc/makecdfenv.pdf vignetteTitles: makecdfenv primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/makecdfenv/inst/doc/makecdfenv.R dependsOnMe: altcdfenvs Package: MANOR Version: 1.36.0 Depends: R (>= 2.10), GLAD Imports: GLAD, graphics, grDevices, stats, utils License: GPL-2 Archs: i386, x64 MD5sum: 4d9b26684ca1ea261ee39b3aa7947490 NeedsCompilation: yes Title: CGH Micro-Array NORmalization Description: Importation, normalization, visualization, and quality control functions to correct identified sources of variability in array-CGH experiments. biocViews: Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, CopyNumberVariation Author: Pierre Neuvial , Philippe Hupe Maintainer: Pierre Neuvial URL: http://bioinfo.curie.fr/projects/manor/index.html source.ver: src/contrib/MANOR_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MANOR_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MANOR_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MANOR_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MANOR_1.36.0.tgz vignettes: vignettes/MANOR/inst/doc/MANOR.pdf vignetteTitles: MANOR overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MANOR/inst/doc/MANOR.R Package: manta Version: 1.10.0 Depends: R (>= 1.8.0), methods, edgeR (>= 2.5.13) Imports: Hmisc, caroline(>= 0.6.6) Suggests: RSQLite, plotrix License: Artistic-2.0 MD5sum: f67a2cac277c414d0ab939bdde989e69 NeedsCompilation: no Title: Microbial Assemblage Normalized Transcript Analysis Description: Tools for robust comparative metatranscriptomics. biocViews: DifferentialExpression, RNASeq, Genetics, GeneExpression, Sequencing, QualityControl, DataImport, Visualization Author: Ginger Armbrust, Adrian Marchetti Maintainer: Chris Berthiaume , Adrian Marchetti URL: http://manta.ocean.washington.edu/ source.ver: src/contrib/manta_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/manta_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/manta_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/manta_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/manta_1.10.0.tgz vignettes: vignettes/manta/inst/doc/manta.pdf vignetteTitles: manta hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/manta/inst/doc/manta.R Package: MantelCorr Version: 1.34.0 Depends: R (>= 2.10) Imports: stats License: GPL (>= 2) MD5sum: 58bc162dfa7e52f09b2022c6507b461e NeedsCompilation: no Title: Compute Mantel Cluster Correlations Description: Computes Mantel cluster correlations from a (p x n) numeric data matrix (e.g. microarray gene-expression data). biocViews: Clustering Author: Brian Steinmeyer and William Shannon Maintainer: Brian Steinmeyer source.ver: src/contrib/MantelCorr_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MantelCorr_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MantelCorr_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MantelCorr_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MantelCorr_1.34.0.tgz vignettes: vignettes/MantelCorr/inst/doc/MantelCorrVignette.pdf vignetteTitles: MantelCorrVignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MantelCorr/inst/doc/MantelCorrVignette.R Package: maPredictDSC Version: 1.2.0 Depends: R (>= 2.15.0), MASS,affy,limma,gcrma,ROC,class,e1071,caret,hgu133plus2.db,ROCR,AnnotationDbi,LungCancerACvsSCCGEO Suggests: parallel License: GPL-2 MD5sum: 0b1cf1fcbad9efc927a3fabef0113cd9 NeedsCompilation: no Title: Phenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge Description: This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types. biocViews: Microarray, Classification Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca URL: http://bioinformaticsprb.med.wayne.edu/maPredictDSC source.ver: src/contrib/maPredictDSC_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/maPredictDSC_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/maPredictDSC_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/maPredictDSC_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maPredictDSC_1.2.0.tgz vignettes: vignettes/maPredictDSC/inst/doc/maPredictDSC.pdf vignetteTitles: maPredictDSC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maPredictDSC/inst/doc/maPredictDSC.R Package: marray Version: 1.42.0 Depends: R (>= 2.10.0), limma, methods Suggests: tkWidgets License: LGPL MD5sum: e46e9892bf435f9a6ec69386b35488ce NeedsCompilation: no Title: Exploratory analysis for two-color spotted microarray data Description: Class definitions for two-color spotted microarray data. Fuctions for data input, diagnostic plots, normalization and quality checking. biocViews: Microarray, TwoChannel, Preprocessing Author: Yee Hwa (Jean) Yang with contributions from Agnes Paquet and Sandrine Dudoit. Maintainer: Yee Hwa (Jean) Yang URL: http://www.maths.usyd.edu.au/u/jeany/ source.ver: src/contrib/marray_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/marray_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/marray_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/marray_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/marray_1.42.0.tgz vignettes: vignettes/marray/inst/doc/marrayClasses.pdf, vignettes/marray/inst/doc/marrayClassesShort.pdf, vignettes/marray/inst/doc/marrayInput.pdf, vignettes/marray/inst/doc/marrayNorm.pdf, vignettes/marray/inst/doc/marray.pdf, vignettes/marray/inst/doc/marrayPlots.pdf vignetteTitles: marrayClasses Overview, marrayClasses Tutorial (short), marrayInput Introduction, marray Normalization, marray Overview, marrayPlots Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/marray/inst/doc/marrayClasses.R, vignettes/marray/inst/doc/marrayClassesShort.R, vignettes/marray/inst/doc/marrayInput.R, vignettes/marray/inst/doc/marrayNorm.R, vignettes/marray/inst/doc/marrayPlots.R, vignettes/marray/inst/doc/marray.R dependsOnMe: CGHbase, convert, dyebias, maigesPack, MineICA, nnNorm, OLIN, stepNorm, TurboNorm importsMe: arrayQuality, ChAMP, nnNorm, OLIN, OLINgui, piano, plrs, sigaR, stepNorm, timecourse suggestsMe: DEGraph, Mfuzz Package: maSigPro Version: 1.36.0 Depends: R (>= 2.3.1), stats, Biobase, MASS Imports: Biobase, graphics, grDevices, limma, Mfuzz, stats, utils, MASS License: GPL (>= 2) MD5sum: 009fb7f19886ead93d8c9c7174c74c50 NeedsCompilation: no Title: Significant Gene Expression Profile Differences in Time Course Microarray Data Description: maSigPro is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray experiments. biocViews: Microarray, DifferentialExpression, TimeCourse Author: Ana Conesa , Maria Jose Nueda Maintainer: Maria Jose Nueda URL: http://bioinfo.cipf.es/ source.ver: src/contrib/maSigPro_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/maSigPro_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/maSigPro_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/maSigPro_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maSigPro_1.36.0.tgz vignettes: vignettes/maSigPro/inst/doc/maSigPro.pdf, vignettes/maSigPro/inst/doc/maSigProUsersGuide.pdf vignetteTitles: maSigPro Vignette, maSigProUsersGuide.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maSigPro/inst/doc/maSigPro.R suggestsMe: oneChannelGUI Package: maskBAD Version: 1.8.0 Depends: R (>= 2.10), gcrma (>= 2.27.1), affy Suggests: hgu95av2probe License: GPL version 2 or newer MD5sum: ccc0fd73530ea4b8413cc57128792287 NeedsCompilation: no Title: Masking probes with binding affinity differences Description: Package includes functions to analyze and mask microarray expression data. biocViews: Microarray Author: Michael Dannemann Maintainer: Michael Dannemann source.ver: src/contrib/maskBAD_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/maskBAD_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/maskBAD_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/maskBAD_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/maskBAD_1.8.0.tgz vignettes: vignettes/maskBAD/inst/doc/maskBAD.pdf vignetteTitles: Package maskBAD hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maskBAD/inst/doc/maskBAD.R Package: MassArray Version: 1.16.0 Depends: R (>= 2.10.0), methods Imports: graphics, grDevices, methods, stats, utils License: GPL (>=2) MD5sum: bfce9fc5ec879d4f1d0976e27c675c2d NeedsCompilation: no Title: Analytical Tools for MassArray Data Description: This package is designed for the import, quality control, analysis, and visualization of methylation data generated using Sequenom's MassArray platform. The tools herein contain a highly detailed amplicon prediction for optimal assay design. Also included are quality control measures of data, such as primer dimer and bisulfite conversion efficiency estimation. Methylation data are calculated using the same algorithms contained in the EpiTyper software package. Additionally, automatic SNP-detection can be used to flag potentially confounded data from specific CG sites. Visualization includes barplots of methylation data as well as UCSC Genome Browser-compatible BED tracks. Multiple assays can be positionally combined for integrated analysis. biocViews: DNAMethylation, SNP, MassSpectrometry, Genetics, DataImport, Visualization Author: Reid F. Thompson , John M. Greally Maintainer: Reid F. Thompson source.ver: src/contrib/MassArray_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MassArray_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MassArray_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MassArray_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MassArray_1.16.0.tgz vignettes: vignettes/MassArray/inst/doc/MassArray.pdf vignetteTitles: 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MassArray/inst/doc/MassArray.R Package: massiR Version: 1.0.1 Depends: cluster, gplots, diptest, Biobase, R (>= 3.0.2), Suggests: biomaRt, RUnit, BiocGenerics License: GPL-3 MD5sum: f179488138a1d84f7b7abc762de066f7 NeedsCompilation: no Title: massiR: MicroArray Sample Sex Identifier Description: Predicts the sex of samples in gene expression microarray datasets biocViews: Software, Microarray, GeneExpression, Clustering, Classification, QualityControl Author: Sam Buckberry Maintainer: Sam Buckberry source.ver: src/contrib/massiR_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/massiR_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/massiR_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/massiR_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/massiR_1.0.1.tgz vignettes: vignettes/massiR/inst/doc/massiR_Vignette.pdf vignetteTitles: massiR_Example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/massiR/inst/doc/massiR_Vignette.R Package: MassSpecWavelet Version: 1.30.0 Depends: waveslim Suggests: xcms, caTools License: LGPL (>= 2) Archs: i386, x64 MD5sum: 314fab3a7206dfa4bad7b9f6fd66c3ee NeedsCompilation: yes Title: Mass spectrum processing by wavelet-based algorithms Description: Processing Mass Spectrometry spectrum by using wavelet based algorithm biocViews: MassSpectrometry, Proteomics Author: Pan Du, Warren Kibbe, Simon Lin Maintainer: Pan Du source.ver: src/contrib/MassSpecWavelet_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MassSpecWavelet_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MassSpecWavelet_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MassSpecWavelet_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MassSpecWavelet_1.30.0.tgz vignettes: vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.pdf vignetteTitles: MassSpecWavelet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MassSpecWavelet/inst/doc/MassSpecWavelet.R suggestsMe: xcms Package: matchBox Version: 1.6.0 Depends: R (>= 2.8.0) License: Artistic-2.0 MD5sum: 00d5dee27e9bd52d28418ad24c0c378d NeedsCompilation: no Title: Utilities to compute, compare, and plot the agreement between ordered vectors of features (ie. distinct genomic experiments). The package includes Correspondence-At-the-TOP (CAT) analysis. Description: The matchBox package enables comparing ranked vectors of features, merging multiple datasets, removing redundant features, using CAT-plots and Venn diagrams, and computing statistical significance. biocViews: Software, Annotation, Microarray, MultipleComparison, Visualization Author: Luigi Marchionni , Anuj Gupta Maintainer: Luigi Marchionni , Anuj Gupta source.ver: src/contrib/matchBox_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/matchBox_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/matchBox_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/matchBox_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/matchBox_1.6.0.tgz vignettes: vignettes/matchBox/inst/doc/matchBox.pdf vignetteTitles: Working with the matchBox package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/matchBox/inst/doc/matchBox.R Package: MBCB Version: 1.18.0 Depends: R (>= 2.9.0), tcltk, tcltk2 Imports: preprocessCore, stats, utils License: GPL (>= 2) MD5sum: f8729f97f98a66a458a5c873c4e502ec NeedsCompilation: no Title: MBCB (Model-based Background Correction for Beadarray) Description: This package provides a model-based background correction method, which incorporates the negative control beads to pre-process Illumina BeadArray data. biocViews: Microarray, Preprocessing Author: Yang Xie Maintainer: Jeff Allen URL: http://www.utsouthwestern.edu source.ver: src/contrib/MBCB_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MBCB_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MBCB_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MBCB_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MBCB_1.18.0.tgz vignettes: vignettes/MBCB/inst/doc/MBCB.pdf vignetteTitles: MBCB hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MBCB/inst/doc/MBCB.R Package: mBPCR Version: 1.18.0 Depends: oligoClasses, SNPchip Imports: Biobase Suggests: xtable License: GPL (>= 2) MD5sum: 8a7aad38f79834a3a116646e648c7fc5 NeedsCompilation: no Title: Bayesian Piecewise Constant Regression for DNA copy number estimation Description: Estimates the DNA copy number profile using mBPCR to detect regions with copy number changes biocViews: aCGH, SNP, Microarray, CopyNumberVariation Author: P.M.V. Rancoita , with contributions from M. Hutter Maintainer: P.M.V. Rancoita URL: http://www.idsia.ch/~paola/mBPCR source.ver: src/contrib/mBPCR_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/mBPCR_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/mBPCR_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/mBPCR_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mBPCR_1.18.0.tgz vignettes: vignettes/mBPCR/inst/doc/mBPCR.pdf vignetteTitles: mBPCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mBPCR/inst/doc/mBPCR.R Package: mcaGUI Version: 1.12.0 Depends: lattice, MASS, proto, foreign, gWidgets(>= 0.0-36), gWidgetsRGtk2(>= 0.0-53), OTUbase, vegan, bpca Enhances: iplots, reshape, ggplot2, cairoDevice, OTUbase License: GPL (>= 2) MD5sum: d831b0494086404d5bb9d539141a58a1 NeedsCompilation: no Title: Microbial Community Analysis GUI Description: Microbial community analysis GUI for R using gWidgets. biocViews: GUI, Visualization, Clustering, Sequencing Author: Wade K. Copeland, Vandhana Krishnan, Daniel Beck, Matt Settles, James Foster, Kyu-Chul Cho, Mitch Day, Roxana Hickey, Ursel M.E. Schutte, Xia Zhou, Chris Williams, Larry J. Forney, Zaid Abdo, Poor Man's GUI (PMG) base code by John Verzani with contributions by Yvonnick Noel Maintainer: Wade K. Copeland URL: http://www.ibest.uidaho.edu/ibest/index.php source.ver: src/contrib/mcaGUI_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/mcaGUI_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/mcaGUI_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/mcaGUI_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mcaGUI_1.12.0.tgz vignettes: vignettes/mcaGUI/inst/doc/ hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: MCRestimate Version: 2.20.0 Depends: R (>= 2.7.2), golubEsets (>= 1.4.6) Imports: e1071 (>= 1.5-12), pamr (>= 1.22), randomForest (>= 3.9-6), RColorBrewer (>= 0.1-3), Biobase (>= 2.5.5), graphics, grDevices, stats, utils Suggests: xtable (>= 1.2-1), ROC (>= 1.8.0), genefilter (>= 1.12.0), gpls (>= 1.6.0) License: GPL (>= 2) MD5sum: 16d5289bb08d8e4e90cc1e7a5b3c2b48 NeedsCompilation: no Title: Misclassification error estimation with cross-validation Description: This package includes a function for combining preprocessing and classification methods to calculate misclassification errors biocViews: Classification Author: Marc Johannes, Markus Ruschhaupt, Holger Froehlich, Ulrich Mansmann, Andreas Buness, Patrick Warnat, Wolfgang Huber, Axel Benner, Tim Beissbarth Maintainer: Marc Johannes source.ver: src/contrib/MCRestimate_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MCRestimate_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MCRestimate_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MCRestimate_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MCRestimate_2.20.0.tgz vignettes: vignettes/MCRestimate/inst/doc/UsingMCRestimate.pdf vignetteTitles: HOW TO use MCRestimate hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MCRestimate/inst/doc/UsingMCRestimate.R Package: mdqc Version: 1.26.0 Depends: R (>= 2.2.1), cluster, MASS License: LGPL (>= 2) MD5sum: 719b496c9f4e5d3620fe4efa4f806be4 NeedsCompilation: no Title: Mahalanobis Distance Quality Control for microarrays Description: MDQC is a multivariate quality assessment method for microarrays based on quality control (QC) reports. The Mahalanobis distance of an array's quality attributes is used to measure the similarity of the quality of that array against the quality of the other arrays. Then, arrays with unusually high distances can be flagged as potentially low-quality. biocViews: Microarray, QualityControl Author: Justin Harrington Maintainer: Gabriela Cohen-Freue source.ver: src/contrib/mdqc_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/mdqc_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/mdqc_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/mdqc_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mdqc_1.26.0.tgz vignettes: vignettes/mdqc/inst/doc/mdqcvignette.pdf vignetteTitles: Introduction to MDQC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mdqc/inst/doc/mdqcvignette.R importsMe: arrayMvout Package: MeasurementError.cor Version: 1.36.0 License: LGPL MD5sum: 99163185e87e12bdecd3e044dc4ff6be NeedsCompilation: no Title: Measurement Error model estimate for correlation coefficient Description: Two-stage measurement error model for correlation estimation with smaller bias than the usual sample correlation biocViews: StatisticalMethod Author: Beiying Ding Maintainer: Beiying Ding source.ver: src/contrib/MeasurementError.cor_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MeasurementError.cor_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MeasurementError.cor_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MeasurementError.cor_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MeasurementError.cor_1.36.0.tgz vignettes: vignettes/MeasurementError.cor/inst/doc/MeasurementError.cor.pdf vignetteTitles: MeasurementError.cor Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: MEDIPS Version: 1.14.0 Depends: R (>= 3.0), BSgenome, DNAcopy Imports: Biostrings, BSgenome, Rsamtools, graphics, gtools, IRanges, methods, stats, utils, GenomicRanges, edgeR, GenomicFeatures, DNAcopy, biomaRt, rtracklayer Suggests: BSgenome, BSgenome.Hsapiens.UCSC.hg19, MEDIPSData License: GPL (>=2) MD5sum: d56ee712237548dd6c5afd9a86b1a809 NeedsCompilation: no Title: (MeD)IP-seq data analysis Description: MEDIPS was developed for analyzing data derived from methylated DNA immunoprecipitation (MeDIP) experiments followed by sequencing (MeDIP-seq). However, MEDIPS provides several functionalities for the analysis of other kinds of quantitative sequencing data (e.g. ChIP-seq, MBD-seq, CMS-seq and others) including calculation of differential coverage between groups of samples as well as saturation and correlation analyses. biocViews: DNAMethylation, CpGIsland, DifferentialExpression, Sequencing, ChIPSeq, Preprocessing, QualityControl, Visualization Author: Lukas Chavez, Matthias Lienhard, Joern Dietrich Maintainer: Lukas Chavez source.ver: src/contrib/MEDIPS_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MEDIPS_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MEDIPS_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MEDIPS_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MEDIPS_1.14.0.tgz vignettes: vignettes/MEDIPS/inst/doc/MEDIPS.pdf vignetteTitles: MEDIPS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MEDIPS/inst/doc/MEDIPS.R Package: MEDME Version: 1.24.0 Depends: R (>= 2.15), grDevices, graphics, methods, stats, utils Imports: Biostrings, MASS, drc Suggests: BSgenome.Hsapiens.UCSC.hg18, BSgenome.Mmusculus.UCSC.mm9 License: GPL (>= 2) Archs: i386, x64 MD5sum: be9b14dbb954db167686d5c219e3738b NeedsCompilation: yes Title: Modelling Experimental Data from MeDIP Enrichment Description: Description: MEDME allows the prediction of absolute and relative methylation levels based on measures obtained by MeDIP-microarray experiments biocViews: Microarray, CpGIsland, DNAMethylation Author: Mattia Pelizzola and Annette Molinaro Maintainer: Mattia Pelizzola source.ver: src/contrib/MEDME_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MEDME_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MEDME_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MEDME_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MEDME_1.24.0.tgz vignettes: vignettes/MEDME/inst/doc/MEDME.pdf vignetteTitles: MEDME.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MEDME/inst/doc/MEDME.R Package: MergeMaid Version: 2.36.0 Depends: R (>= 2.10.0), survival, Biobase, MASS, methods License: GPL (>= 2) MD5sum: 2e3b53141b3b32c8b1066d447da39300 NeedsCompilation: no Title: Merge Maid Description: The functions in this R extension are intended for cross-study comparison of gene expression array data. Required from the user is gene expression matrices, their corresponding gene-id vectors and other useful information, and they could be 'list','matrix', or 'ExpressionSet'. The main function is 'mergeExprs' which transforms the input objects into data in the merged format, such that common genes in different datasets can be easily found. And the function 'intcor' calculate the correlation coefficients. Other functions use the output from 'modelOutcome' to graphically display the results and cross-validate associations of gene expression data with survival. biocViews: Microarray, DifferentialExpression, Visualization Author: Xiaogang Zhong Leslie Cope Elizabeth Garrett Giovanni Parmigiani Maintainer: Xiaogang Zhong URL: http://astor.som.jhmi.edu/MergeMaid source.ver: src/contrib/MergeMaid_2.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MergeMaid_2.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MergeMaid_2.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MergeMaid_2.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MergeMaid_2.36.0.tgz vignettes: vignettes/MergeMaid/inst/doc/MergeMaid.pdf vignetteTitles: MergeMaid primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MergeMaid/inst/doc/MergeMaid.R importsMe: metaArray, XDE suggestsMe: oneChannelGUI Package: MeSHDbi Version: 1.0.2 Depends: R (>= 3.0.1) Imports: methods, AnnotationDbi (>= 1.16.10), DBI, RSQLite, IRanges, Biobase Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 15a3571f662126d25465ea7166f640ec NeedsCompilation: no Title: DBI to construct MeSH-related package from sqlite file. Description: The package is unified implementation of MeSH.db, MeSH.AOR.db, and MeSH.PCR.db and also is interface to construct Gene-MeSH package (org.MeSH.XXX.db). loadMeSHDbiPkg import sqlite file and generate org.MeSH.XXX.db. biocViews: Annotation, AnnotationData, Infrastructure Author: Koki Tsuyuzaki Maintainer: Koki Tsuyuzaki source.ver: src/contrib/MeSHDbi_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/MeSHDbi_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/MeSHDbi_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/MeSHDbi_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MeSHDbi_1.0.2.tgz vignettes: vignettes/MeSHDbi/inst/doc/MeSHDbi.pdf vignetteTitles: MeSH.db hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MeSHDbi/inst/doc/MeSHDbi.R dependsOnMe: meshr Package: meshr Version: 1.0.4 Depends: R (>= 3.0.1), fdrtool, Category, BiocGenerics, methods, cummeRbund, org.Hs.eg.db, MeSH.db, MeSH.AOR.db, MeSH.PCR.db, MeSHDbi, org.MeSH.Hsa.db, org.MeSH.Aca.db, org.MeSH.Atu.K84.db, org.MeSH.Bsu.168.db, org.MeSH.Syn.db License: Artistic-2.0 MD5sum: 8bb3b43a030ac8d5ada57bf799bb8d11 NeedsCompilation: no Title: Tools for conducting enrichment analysis of MeSH Description: A set of annotation maps describing the entire MeSH assembled using data from MeSH biocViews: AnnotationData, FunctionalAnnotation, Bioinformatics, Statistics, Annotation, MultipleComparisons Author: Itoshi Nikaido, Koki Tsuyuzaki, Gota Morota Maintainer: Koki Tsuyuzaki source.ver: src/contrib/meshr_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/meshr_1.0.4.zip win64.binary.ver: bin/windows64/contrib/3.1/meshr_1.0.4.zip mac.binary.ver: bin/macosx/contrib/3.1/meshr_1.0.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/meshr_1.0.4.tgz vignettes: vignettes/meshr/inst/doc/MeSH.pdf vignetteTitles: MeSH.db hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/meshr/inst/doc/MeSH.R Package: messina Version: 1.0.0 Depends: R (>= 3.1.0), survival (>= 2.37-4), methods Imports: Rcpp (>= 0.11.1), plyr (>= 1.8), ggplot2 (>= 0.9.3.1), grid (>= 3.1.0), foreach (>= 1.4.1), graphics LinkingTo: Rcpp Suggests: knitr (>= 1.5), antiProfilesData (>= 0.99.2), Biobase (>= 2.22.0), BiocStyle Enhances: doMC (>= 1.3.3) License: EPL (>= 1.0) Archs: i386, x64 MD5sum: d174f8ec26599c6f307a911c1469d7d1 NeedsCompilation: yes Title: Single-gene classifiers and outlier-resistant detection of differential expression for two-group and survival problems. Description: Messina is a collection of algorithms for constructing optimally robust single-gene classifiers, and for identifying differential expression in the presence of outliers or unknown sample subgroups. The methods have application in identifying lead features to develop into clinical tests (both diagnostic and prognostic), and in identifying differential expression when a fraction of samples show unusual patterns of expression. biocViews: GeneExpression, DifferentialExpression, BiomedicalInformatics, Classification, Survival Author: Mark Pinese [aut], Mark Pinese [cre], Mark Pinese [cph] Maintainer: Mark Pinese VignetteBuilder: knitr source.ver: src/contrib/messina_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/messina_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/messina_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/messina_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/messina_1.0.0.tgz vignettes: vignettes/messina/inst/doc/messina.pdf vignetteTitles: Using Messina hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/messina/inst/doc/messina.R Package: metaArray Version: 1.42.0 Imports: Biobase, MergeMaid, graphics, stats License: LGPL-2 Archs: i386, x64 MD5sum: fa4b1cbfd82c8193accd927ed4f8474f NeedsCompilation: yes Title: Integration of Microarray Data for Meta-analysis Description: 1) Data transformation for meta-analysis of microarray Data: Transformation of gene expression data to signed probability scale (MCMC/EM methods) 2) Combined differential expression on raw scale: Weighted Z-score after stabilizing mean-variance relation within platform biocViews: Microarray, DifferentialExpression Author: Debashis Ghosh Hyungwon Choi Maintainer: Hyungwon Choi source.ver: src/contrib/metaArray_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/metaArray_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/metaArray_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/metaArray_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metaArray_1.42.0.tgz vignettes: vignettes/metaArray/inst/doc/metaArray.pdf vignetteTitles: metaArray Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metaArray/inst/doc/metaArray.R suggestsMe: oneChannelGUI Package: metagenomeSeq Version: 1.6.0 Depends: R(>= 3.0), Biobase, limma, matrixStats, methods, RColorBrewer, gplots Suggests: annotate, biom, parallel, vegan, knitr License: Artistic-2.0 MD5sum: 97d1238aff2f91fc9e626d8d84318d1c NeedsCompilation: no Title: Statistical analysis for sparse high-throughput sequencing Description: metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations. biocViews: DifferentialExpression, Metagenomics, Visualization Author: Joseph Nathaniel Paulson, Mihai Pop, Hector Corrada Bravo Maintainer: Joseph N. Paulson URL: http://cbcb.umd.edu/software/metagenomeSeq VignetteBuilder: knitr source.ver: src/contrib/metagenomeSeq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/metagenomeSeq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/metagenomeSeq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/metagenomeSeq_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metagenomeSeq_1.6.0.tgz vignettes: vignettes/metagenomeSeq/inst/doc/metagenomeSeq.pdf vignetteTitles: metagenomeSeq: statistical analysis for sparse high-throughput sequencing hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metagenomeSeq/inst/doc/metagenomeSeq.R Package: metahdep Version: 1.22.0 Depends: R (>= 2.10), methods Suggests: affyPLM License: GPL-3 Archs: i386, x64 MD5sum: bcc7b0e624c1ab42af949aeb8d2fd1e5 NeedsCompilation: yes Title: Hierarchical Dependence in Meta-Analysis Description: Tools for meta-analysis in the presence of hierarchical (and/or sampling) dependence, including with gene expression studies biocViews: Microarray, DifferentialExpression Author: John R. Stevens, Gabriel Nicholas Maintainer: John R. Stevens source.ver: src/contrib/metahdep_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/metahdep_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/metahdep_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/metahdep_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metahdep_1.22.0.tgz vignettes: vignettes/metahdep/inst/doc/metahdep.pdf vignetteTitles: metahdep Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metahdep/inst/doc/metahdep.R Package: metaMS Version: 1.0.0 Depends: R (>= 2.10), methods, CAMERA, xcms (>= 1.35) Imports: Matrix, tools, robustbase, BiocGenerics Suggests: metaMSdata, RUnit License: GPL (>= 2) MD5sum: 4a44d10f494ef4da468c180a7c02b77a NeedsCompilation: no Title: MS-based metabolomics annotation pipeline Description: MS-based metabolomics data processing and compound annotation pipeline. biocViews: MassSpectrometry, Metabolomics Author: Ron Wehrens [aut, cre] (author of GC-MS part), Pietro Franceschi [aut] (author of LC-MS part), Nir Shahaf [ctb], Matthias Scholz [ctb], Georg Weingart [ctb] (development of GC-MS approach), Elisabete Carvalho [ctb] (testing and feedback of GC-MS pipeline) Maintainer: Ron Wehrens source.ver: src/contrib/metaMS_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/metaMS_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/metaMS_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/metaMS_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metaMS_1.0.0.tgz vignettes: vignettes/metaMS/inst/doc/runGC.pdf, vignettes/metaMS/inst/doc/runLC.pdf vignetteTitles: runGC, alsace hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metaMS/inst/doc/runGC.R, vignettes/metaMS/inst/doc/runLC.R Package: metaSeq Version: 1.4.0 Depends: R (>= 2.13.0), NOISeq, snow, Rcpp License: Artistic-2.0 MD5sum: e5641c438048503486ca7e499ae50a0c NeedsCompilation: no Title: Meta-analysis of RNA-Seq count data in multiple studies Description: The probabilities by one-sided NOISeq are combined by Fisher's method or Stouffer's method biocViews: RNASeq, DifferentialExpression, Sequencing Author: Koki Tsuyuzaki, Itoshi Nikaido Maintainer: Koki Tsuyuzaki source.ver: src/contrib/metaSeq_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/metaSeq_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/metaSeq_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/metaSeq_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metaSeq_1.4.0.tgz vignettes: vignettes/metaSeq/inst/doc/metaSeq.pdf vignetteTitles: metaSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metaSeq/inst/doc/metaSeq.R Package: metaseqR Version: 1.2.3 Depends: R (>= 2.13.0), EDASeq, DESeq, limma, qvalue Imports: edgeR, NOISeq, baySeq, NBPSeq, biomaRt, utils, gplots, corrplot, vsn, brew, rjson, log4r Suggests: BiocGenerics, GenomicRanges, rtracklayer, Rsamtools, MADAM, survcomp, VennDiagram, knitr, zoo, RUnit Enhances: parallel, TCC License: GPL (>= 3) MD5sum: 0f84693b38eb618481198040bbd1d5b8 NeedsCompilation: no Title: metaseqR: an R package for the analysis and result reporting of RNA-Seq gene expression data using multiple statistical algorithms. Description: Provides an interface to several normalization and statistical testing packages for RNA-Seq gene expression data. Additionally, it creates several diagnostic plots, performs meta-analysis by combinining the results of several statistical tests and reports the results in an interactive way. biocViews: Software, GeneExpression, DifferentialExpression, WorkflowStep, Preprocessing, QualityControl, Normalization, ReportWriting, RNASeq Author: Panagiotis Moulos Maintainer: Panagiotis Moulos URL: http://www.fleming.gr VignetteBuilder: knitr source.ver: src/contrib/metaseqR_1.2.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/metaseqR_1.2.3.zip win64.binary.ver: bin/windows64/contrib/3.1/metaseqR_1.2.3.zip mac.binary.ver: bin/macosx/contrib/3.1/metaseqR_1.2.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/metaseqR_1.2.3.tgz vignettes: vignettes/metaseqR/inst/doc/metaseqr-pdf.pdf vignetteTitles: RNA-Seq data analysis using mulitple statistical algorithms with metaseqR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/metaseqR/inst/doc/metaseqr-pdf.R Package: methVisual Version: 1.16.0 Depends: R (>= 2.11.0), Biostrings(>= 2.4.8), plotrix,gsubfn, grid,sqldf Imports: Biostrings, ca, graphics, grDevices, grid, gridBase, IRanges, stats, utils License: GPL (>= 2) MD5sum: 2386c88681d96a4d05827057111760fe NeedsCompilation: no Title: Methods for visualization and statistics on DNA methylation data Description: The package 'methVisual' allows the visualization of DNA methylation data after bisulfite sequencing. biocViews: DNAMethylation, Clustering, Classification Author: A. Zackay, C. Steinhoff Maintainer: Arie Zackay source.ver: src/contrib/methVisual_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/methVisual_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/methVisual_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/methVisual_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/methVisual_1.16.0.tgz vignettes: vignettes/methVisual/inst/doc/methVisual.pdf vignetteTitles: Introduction to methVisual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methVisual/inst/doc/methVisual.R Package: methyAnalysis Version: 1.6.0 Depends: R (>= 2.10), grid, IRanges, GenomicRanges, Biobase (>= 2.5.5), org.Hs.eg.db Imports: lumi, methylumi, Gviz, genoset, GenomicRanges, IRanges, rtracklayer, GenomicFeatures, annotate, Biobase (>= 2.5.5), AnnotationDbi, genefilter, biomaRt, methods Suggests: FDb.InfiniumMethylation.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: 3cb1d1cda65451b259b95d1fb52e42b3 NeedsCompilation: no Title: DNA methylation data analysis and visualization Description: The methyAnalysis package aims for the DNA methylation data analysis and visualization. A new class is defined to keep the chromosome location information together with the data. The current version of the package mainly focus on analyzing the Illumina Infinium methylation array data, but most methods can be generalized to other methylation array or sequencing data. biocViews: Microarray, DNAMethylation, Visualization Author: Pan Du, Richard Bourgon Maintainer: Pan Du source.ver: src/contrib/methyAnalysis_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/methyAnalysis_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/methyAnalysis_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/methyAnalysis_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/methyAnalysis_1.6.0.tgz vignettes: vignettes/methyAnalysis/inst/doc/methyAnalysis.pdf vignetteTitles: An Introduction to the methyAnalysis package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methyAnalysis/inst/doc/methyAnalysis.R suggestsMe: methylumi Package: methylMnM Version: 1.2.0 Depends: R (>= 2.12.1), edgeR, statmod License: GPL-3 Archs: i386, x64 MD5sum: 75115b462e7c000a14681c9a7681bc43 NeedsCompilation: yes Title: detect different methylation level (DMR) Description: To give the exactly p-value and q-value of MeDIP-seq and MRE-seq data for different samples comparation. biocViews: Software, DNAMethylation, Sequencing Author: Yan Zhou, Bo Zhang, Nan Lin, BaoXue Zhang and Ting Wang Maintainer: Yan Zhou source.ver: src/contrib/methylMnM_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/methylMnM_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/methylMnM_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/methylMnM_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/methylMnM_1.2.0.tgz vignettes: vignettes/methylMnM/inst/doc/methylMnM.pdf vignetteTitles: methylMnM hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methylMnM/inst/doc/methylMnM.R Package: MethylSeekR Version: 1.4.0 Depends: rtracklayer (>= 1.16.3), parallel (>= 2.15.1), mhsmm (>= 0.4.4) Imports: IRanges (>= 1.16.3), BSgenome (>= 1.26.1), GenomicRanges (>= 1.10.5), geneplotter (>= 1.34.0), graphics (>= 2.15.2), grDevices (>= 2.15.2), parallel (>= 2.15.2), stats (>= 2.15.2), utils (>= 2.15.2) Suggests: BSgenome.Hsapiens.UCSC.hg18 License: GPL (>=2) MD5sum: f510f93a38c723eff3e886411ce8a2c3 NeedsCompilation: no Title: Segmentation of Bis-seq data Description: This is a package for the discovery of regulatory regions from Bis-seq data biocViews: Sequencing, MethylSeq, DNAMethylation Author: Lukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael Stadler Maintainer: Lukas Burger source.ver: src/contrib/MethylSeekR_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MethylSeekR_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MethylSeekR_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MethylSeekR_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MethylSeekR_1.4.0.tgz vignettes: vignettes/MethylSeekR/inst/doc/MethylSeekR.pdf vignetteTitles: MethylSeekR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MethylSeekR/inst/doc/MethylSeekR.R Package: methylumi Version: 2.10.0 Depends: Biobase, methods, R (>= 2.13), scales, reshape2, ggplot2, matrixStats, minfi Imports: Biobase, graphics, lattice, annotate, genefilter, AnnotationDbi, minfi, stats4, BiocGenerics, illuminaio Suggests: lumi, lattice, limma, xtable, IlluminaHumanMethylation27k.db (>= 1.4.4), IlluminaHumanMethylation450k.db, SQN, GenomicRanges, MASS, matrixStats, parallel, rtracklayer, Biostrings, methyAnalysis, FDb.InfiniumMethylation.hg19, TCGAMethylation450k, TxDb.Hsapiens.UCSC.hg19.knownGene, IlluminaHumanMethylation450kanno.ilmn12.hg19, Homo.sapiens, knitr License: GPL-2 MD5sum: 1f7ed387a48450a9af495e7f86e67f91 NeedsCompilation: no Title: Handle Illumina methylation data Description: This package provides classes for holding and manipulating Illumina methylation data. Based on eSet, it can contain MIAME information, sample information, feature information, and multiple matrices of data. An "intelligent" import function, methylumiR can read the Illumina text files and create a MethyLumiSet. methylumIDAT can directly read raw IDAT files from HumanMethylation27 and HumanMethylation450 microarrays. Normalization, background correction, and quality control features for GoldenGate, Infinium, and Infinium HD arrays are also included. biocViews: DNAMethylation, TwoChannel, Preprocessing, QualityControl, CpGIsland Author: Sean Davis, Pan Du, Sven Bilke, Tim Triche, Jr., Moiz Bootwalla Maintainer: Sean Davis VignetteBuilder: knitr source.ver: src/contrib/methylumi_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/methylumi_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/methylumi_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/methylumi_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/methylumi_2.10.0.tgz vignettes: vignettes/methylumi/inst/doc/methylumi450k.pdf, vignettes/methylumi/inst/doc/methylumi.pdf vignetteTitles: Working with Illumina 450k Arrays using methylumi, An Introduction to the methylumi package hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methylumi/inst/doc/methylumi450k.R, vignettes/methylumi/inst/doc/methylumi.R dependsOnMe: wateRmelon importsMe: asmn, ffpe, lumi, methyAnalysis Package: Mfuzz Version: 2.22.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), e1071 Imports: tcltk, tkWidgets Suggests: marray License: GPL-2 MD5sum: 27136672cce9305d804af6e31ffea8a5 NeedsCompilation: no Title: Soft clustering of time series gene expression data Description: Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface) biocViews: Microarray, Clustering, TimeCourse, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/Mfuzz/ source.ver: src/contrib/Mfuzz_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Mfuzz_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Mfuzz_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Mfuzz_2.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Mfuzz_2.22.0.tgz vignettes: vignettes/Mfuzz/inst/doc/Mfuzz.pdf vignetteTitles: Introduction to Mfuzz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mfuzz/inst/doc/Mfuzz.R dependsOnMe: cycle importsMe: maSigPro Package: mgsa Version: 1.12.0 Depends: R (>= 2.14.0), methods, gplots Imports: graphics, stats, utils Suggests: DBI, RSQLite, GO.db License: Artistic-2.0 Archs: i386, x64 MD5sum: 9e405d0e391840227fcdec7aa69a7b7b NeedsCompilation: yes Title: Model-based gene set analysis Description: Model-based Gene Set Analysis (MGSA) is a Bayesian modeling approach for gene set enrichment. The package mgsa implements MGSA and tools to use MGSA together with the Gene Ontology. biocViews: Pathways, GO, GeneSetEnrichment Author: Sebastian Bauer , Julien Gagneur Maintainer: Sebastian Bauer source.ver: src/contrib/mgsa_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/mgsa_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/mgsa_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/mgsa_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mgsa_1.12.0.tgz vignettes: vignettes/mgsa/inst/doc/mgsa.pdf vignetteTitles: Overview of the mgsa package. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mgsa/inst/doc/mgsa.R suggestsMe: gCMAP Package: MiChip Version: 1.18.0 Depends: R (>= 2.3.0), Biobase Imports: Biobase License: GPL (>= 2) MD5sum: cb308f5fbc8c360180adf140caae017a NeedsCompilation: no Title: MiChip Parsing and Summarizing Functions Description: This package takes the MiChip miRNA microarray .grp scanner output files and parses these out, providing summary and plotting functions to analyse MiChip hybridizations. A set of hybridizations is packaged into an ExpressionSet allowing it to be used by other BioConductor packages. biocViews: Microarray, Preprocessing Author: Jonathon Blake Maintainer: Jonathon Blake source.ver: src/contrib/MiChip_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MiChip_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MiChip_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MiChip_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MiChip_1.18.0.tgz vignettes: vignettes/MiChip/inst/doc/MiChip.pdf vignetteTitles: MiChip miRNA Microarray Processing hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiChip/inst/doc/MiChip.R Package: microRNA Version: 1.22.0 Depends: R (>= 2.10) Imports: Biostrings (>= 2.11.32) Suggests: Biostrings (>= 2.11.32) Enhances: Rlibstree License: Artistic-2.0 MD5sum: 69b29179235b0bc39f09ecf5fcfd0efb NeedsCompilation: no Title: Data and functions for dealing with microRNAs Description: Different data resources for microRNAs and some functions for manipulating them. biocViews: Infrastructure, GenomeAnnotation, SequenceMatching Author: R. Gentleman, S. Falcon Maintainer: "James F. Reid" source.ver: src/contrib/microRNA_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/microRNA_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/microRNA_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/microRNA_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/microRNA_1.22.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: Roleswitch suggestsMe: MmPalateMiRNA, rtracklayer Package: MIMOSA Version: 1.0.0 Depends: R (>= 3.0.2), MASS, plyr, reshape, Biobase, ggplot2 Imports: methods, Formula, data.table, pracma, MCMCpack, coda, modeest, ggplot2, reshape, plyr, Biobase, MASS, testthat, Rcpp LinkingTo: Rcpp, RcppArmadillo Suggests: parallel, knitr License: Artistic-2.0 Archs: i386, x64 MD5sum: c4c9da317d0c3f2fd6525eaa4c7a707f NeedsCompilation: yes Title: Mixture Models for Single-Cell Assays Description: Modeling count data using Dirichlet-multinomial and beta-binomial mixtures with applications to single-cell assays. biocViews: FlowCytometry, CellBasedAssays Author: Greg Finak Maintainer: Greg Finak VignetteBuilder: knitr source.ver: src/contrib/MIMOSA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MIMOSA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MIMOSA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MIMOSA_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MIMOSA_1.0.0.tgz vignettes: vignettes/MIMOSA/inst/doc/MIMOSA.pdf vignetteTitles: MIMOSA: Mixture Models For Single Cell Assays hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MIMOSA/inst/doc/MIMOSA.R Package: MineICA Version: 1.4.0 Depends: R (>= 2.10), Biobase, plyr, ggplot2, scales, foreach, xtable, biomaRt, gtools, GOstats, cluster, marray, mclust, RColorBrewer, colorspace, igraph, Rgraphviz, graph, annotate, Hmisc, fastICA, JADE, methods Imports: AnnotationDbi, lumi, fpc, lumiHumanAll.db Suggests: biomaRt, GOstats, cluster, hgu133a.db, mclust, igraph, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerVDX Enhances: doMC License: GPL-2 MD5sum: c5e38e9c8c5d1151008f7225a852f244 NeedsCompilation: no Title: Analysis of an ICA decomposition obtained on genomics data Description: The goal of MineICA is to perform Independent Component Analysis (ICA) on multiple transcriptome datasets, integrating additional data (e.g molecular, clinical and pathological). This Integrative ICA helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph. biocViews: Visualizations, MultipleComparison Author: Anne Biton Maintainer: Anne Biton source.ver: src/contrib/MineICA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MineICA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MineICA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MineICA_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MineICA_1.4.0.tgz vignettes: vignettes/MineICA/inst/doc/MineICA.pdf vignetteTitles: MineICA: Independent component analysis of genomic data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MineICA/inst/doc/MineICA.R Package: minet Version: 3.20.2 Depends: infotheo License: CC BY-NC-SA 3.0 Archs: i386, x64 MD5sum: 98eab6caec45c4613e0bb44118eebfde NeedsCompilation: yes Title: Mutual Information NETworks Description: This package implements various algorithms for inferring mutual information networks from data. biocViews: Microarray, GraphAndNetwork, Network, NetworkInference Author: Patrick E. Meyer, Frederic Lafitte, Gianluca Bontempi Maintainer: Patrick E. Meyer URL: http://minet.meyerp.com source.ver: src/contrib/minet_3.20.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/minet_3.20.2.zip win64.binary.ver: bin/windows64/contrib/3.1/minet_3.20.2.zip mac.binary.ver: bin/macosx/contrib/3.1/minet_3.20.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/minet_3.20.2.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: BUS, geNetClassifier, netresponse importsMe: RTN suggestsMe: CNORfeeder, predictionet Package: minfi Version: 1.10.2 Depends: methods, BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), lattice, GenomicRanges, Biostrings, utils, bumphunter (>= 1.1.9) Imports: IRanges, beanplot, RColorBrewer, nor1mix, siggenes, limma, preprocessCore, illuminaio, matrixStats, mclust, genefilter, nlme, reshape Suggests: IlluminaHumanMethylation450kmanifest (>= 0.2.0), IlluminaHumanMethylation450kanno.ilmn12.hg19, minfiData (>= 0.4.1), quadprog, FlowSorted.Blood.450k (>= 1.0.1), RUnit, digest License: Artistic-2.0 MD5sum: 39a1bef35b9a61b975f917aadbc788ac NeedsCompilation: no Title: Analyze Illumina's 450k methylation arrays Description: Tools for analyzing and visualizing Illumina's 450k array data biocViews: DNAMethylation, Microarray, TwoChannel, DataImport, Preprocessing, QualityControl Author: Kasper Daniel Hansen [cre, aut], Martin Ayree [aut], Rafael A. Irizarry [aut], Andrew E. Jaffe [ctb], Jovana Maksimovic [ctb], E. Andres Houseman [ctb], Jean-Phillipe Fortin [ctb] Maintainer: Kasper Daniel Hansen source.ver: src/contrib/minfi_1.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/minfi_1.10.2.zip win64.binary.ver: bin/windows64/contrib/3.1/minfi_1.10.2.zip mac.binary.ver: bin/macosx/contrib/3.1/minfi_1.10.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/minfi_1.10.2.tgz vignettes: vignettes/minfi/inst/doc/minfi.pdf vignetteTitles: Minfi Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/minfi/inst/doc/minfi.R dependsOnMe: ChAMP, CopyNumber450k, DMRcate, methylumi importsMe: methylumi Package: MinimumDistance Version: 1.8.1 Depends: R (>= 3.01) Imports: methods, DNAcopy, utils, msm, lattice, BiocGenerics, VanillaICE (>= 1.26.1), ff, Biobase (>= 2.23.6), foreach, oligoClasses (>= 1.24.0), IRanges, GenomicRanges, matrixStats Suggests: human610quadv1bCrlmm (>= 1.0.3), SNPchip, RUnit Enhances: snow, doSNOW License: Artistic-2.0 MD5sum: 162db1bd851ada3b00bbe8d3222116f7 NeedsCompilation: no Title: A package for de novo CNV detection in case-parent trios Description: Analysis of de novo copy number variants in trios from high-dimensional genotyping platforms biocViews: Microarray, SNP, CopyNumberVariation Author: Robert B Scharpf and Ingo Ruczinski Maintainer: Robert B Scharpf source.ver: src/contrib/MinimumDistance_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/MinimumDistance_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/MinimumDistance_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/MinimumDistance_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MinimumDistance_1.8.1.tgz vignettes: vignettes/MinimumDistance/inst/doc/MinimumDistance.pdf vignetteTitles: Detection of de novo copy number alterations in case-parent trios hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MinimumDistance/inst/doc/MinimumDistance.R Package: MiPP Version: 1.36.0 Depends: R (>= 2.4) Imports: Biobase, e1071, MASS, stats License: GPL (>= 2) MD5sum: c6adfca178c3c2d4793095cf9685e20c NeedsCompilation: no Title: Misclassification Penalized Posterior Classification Description: This package finds optimal sets of genes that seperate samples into two or more classes. biocViews: Microarray, Classification Author: HyungJun Cho , Sukwoo Kim , Mat Soukup , and Jae K. Lee Maintainer: Sukwoo Kim URL: http://www.healthsystem.virginia.edu/internet/hes/biostat/bioinformatics/ source.ver: src/contrib/MiPP_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MiPP_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MiPP_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MiPP_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MiPP_1.36.0.tgz vignettes: vignettes/MiPP/inst/doc/MiPP.pdf vignetteTitles: MiPP Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiPP/inst/doc/MiPP.R Package: MiRaGE Version: 1.6.0 Depends: R (>= 3.1.0), Biobase(>= 2.23.3) Imports: AnnotationDbi, BiocGenerics Suggests: seqinr (>= 3.0.7), biomaRt (>= 2.19.1), GenomicFeatures (>= 1.15.4), Biostrings (>= 2.31.3), BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm10, miRNATarget, humanStemCell, IRanges, GenomicRanges (>= 1.8.3), BSgenome, beadarrayExampleData License: GPL MD5sum: 5162bd925fc487028e120e34567f5486 NeedsCompilation: no Title: MiRNA Ranking by Gene Expression Description: The package contains functions for inferece of target gene regulation by miRNA, based on only target gene expression profile. biocViews: Microarray, GeneExpression, RNASeq, RNAseqData, Sequencing, Sequencing, SAGE Author: Y-h. Taguchi Maintainer: Y-h. Taguchi source.ver: src/contrib/MiRaGE_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MiRaGE_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MiRaGE_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MiRaGE_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MiRaGE_1.6.0.tgz vignettes: vignettes/MiRaGE/inst/doc/MiRaGE.pdf vignetteTitles: How to use MiRaGE Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MiRaGE/inst/doc/MiRaGE.R Package: miRNApath Version: 1.24.0 Depends: methods, R(>= 2.7.0) License: LGPL-2.1 MD5sum: 5f3371c65d6555f512e52aae1a18bdfa NeedsCompilation: no Title: miRNApath: Pathway Enrichment for miRNA Expression Data Description: This package provides pathway enrichment techniques for miRNA expression data. Specifically, the set of methods handles the many-to-many relationship between miRNAs and the multiple genes they are predicted to target (and thus affect.) It also handles the gene-to-pathway relationships separately. Both steps are designed to preserve the additive effects of miRNAs on genes, many miRNAs affecting one gene, one miRNA affecting multiple genes, or many miRNAs affecting many genes. biocViews: Annotation, Pathways, DifferentialExpression, NetworkEnrichment, miRNA Author: James M. Ward with contributions from Yunling Shi, Cindy Richards, John P. Cogswell Maintainer: James M. Ward source.ver: src/contrib/miRNApath_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/miRNApath_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/miRNApath_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/miRNApath_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/miRNApath_1.24.0.tgz vignettes: vignettes/miRNApath/inst/doc/miRNApath.pdf vignetteTitles: miRNApath: Pathway Enrichment for miRNA Expression Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/miRNApath/inst/doc/miRNApath.R Package: Mirsynergy Version: 1.0.1 Depends: R (>= 3.0.2), igraph, ggplot2 Imports: graphics, grDevices, gridExtra, Matrix, parallel, RColorBrewer, reshape, scales, utils Suggests: glmnet, RUnit, BiocGenerics, knitr License: GPL-2 MD5sum: 09642ed746eee1e730d0b68419b63fd5 NeedsCompilation: no Title: Mirsynergy Description: Detect synergistic miRNA regulatory modules by overlapping neighbourhood expansion. biocViews: Clustering Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/Mirsynergy.html VignetteBuilder: knitr source.ver: src/contrib/Mirsynergy_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Mirsynergy_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Mirsynergy_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Mirsynergy_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Mirsynergy_1.0.1.tgz vignettes: vignettes/Mirsynergy/inst/doc/Mirsynergy.pdf vignetteTitles: Mirsynergy hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mirsynergy/inst/doc/Mirsynergy.R Package: mitoODE Version: 1.2.0 Depends: R (>= 2.14.0), minpack.lm, MASS, parallel, mitoODEdata, KernSmooth License: LGPL Archs: i386, x64 MD5sum: 9d07cffe8fffff70efc1c7be778fb1bf NeedsCompilation: yes Title: Implementation of the differential equation model described in "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" Description: The package contains the methods to fit a cell-cycle model on cell count data and the code to reproduce the results shown in our paper "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" by Pau, G., Walter, T., Neumann, B., Heriche, J.-K., Ellenberg, J., & Huber, W., BMC Bioinformatics (2013), 14(1), 308. doi:10.1186/1471-2105-14-308 biocViews: ExperimentData, TimeCourse, CellBasedAssays, Preprocessing Author: Gregoire Pau Maintainer: Gregoire Pau SystemRequirements: source.ver: src/contrib/mitoODE_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/mitoODE_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/mitoODE_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/mitoODE_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mitoODE_1.2.0.tgz vignettes: vignettes/mitoODE/inst/doc/mitoODE-introduction.pdf vignetteTitles: mitoODE hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mitoODE/inst/doc/mitoODE-introduction.R Package: MLInterfaces Version: 1.44.1 Depends: R (>= 2.9), Biobase, MASS, methods, genefilter, rpart, rda, annotate, cluster, sfsmisc Imports: mboost, gdata, pls Suggests: class, e1071, ipred, randomForest, gpls, pamr, rpart, MASS, nnet, ALL, gbm, mlbench, hgu95av2.db, som, RColorBrewer, hu6800.db, lattice, caret (>= 5.07), golubEsets, ada, keggorthology, kernlab, gbm, mboost, sfsmisc, party Enhances: parallel License: LGPL MD5sum: e322578f8bf8d1caf569db9f010c9ca6 NeedsCompilation: no Title: Uniform interfaces to R machine learning procedures for data in Bioconductor containers Description: Uniform interfaces to machine learning code for data in Bioconductor containers biocViews: Classification, Clustering Author: Vince Carey , Robert Gentleman, Jess Mar, and contributions from Jason Vertrees and Laurent Gatto Maintainer: V. Carey source.ver: src/contrib/MLInterfaces_1.44.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/MLInterfaces_1.44.1.zip win64.binary.ver: bin/windows64/contrib/3.1/MLInterfaces_1.44.1.zip mac.binary.ver: bin/macosx/contrib/3.1/MLInterfaces_1.44.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MLInterfaces_1.44.1.tgz vignettes: vignettes/MLInterfaces/inst/doc/MLint_devel.pdf, vignettes/MLInterfaces/inst/doc/MLInterfaces.pdf, vignettes/MLInterfaces/inst/doc/MLprac2_2.pdf, vignettes/MLInterfaces/inst/doc/xvalComputerClusters.pdf vignetteTitles: MLInterfaces devel for schema-based MLearn, MLInterfaces Primer, A machine learning tutorial: applications of the Bioconductor MLInterfaces package to expression and ChIP-Seq data, MLInterfaces Computer Cluster hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MLInterfaces/inst/doc/MLint_devel.R, vignettes/MLInterfaces/inst/doc/MLInterfaces.R, vignettes/MLInterfaces/inst/doc/MLprac2_2.R, vignettes/MLInterfaces/inst/doc/xvalComputerClusters.R dependsOnMe: a4Classif, pRoloc suggestsMe: BiocCaseStudies Package: MLP Version: 1.12.0 Depends: AnnotationDbi, affy, plotrix, gplots, gmodels, gdata, gtools Suggests: GO.db, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Cf.eg.db, KEGG.db, annotate, Rgraphviz, GOstats, limma, mouse4302.db, reactome.db License: GPL-3 MD5sum: 3b1d0ecf675857bc2abacf81a48a6c99 NeedsCompilation: no Title: MLP Description: Mean Log P Analysis biocViews: Genetics Author: Nandini Raghavan, Tobias Verbeke, An De Bondt with contributions by Javier Cabrera, Dhammika Amaratunga, Tine Casneuf and Willem Ligtenberg Maintainer: Tobias Verbeke source.ver: src/contrib/MLP_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MLP_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MLP_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MLP_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MLP_1.12.0.tgz vignettes: vignettes/MLP/inst/doc/UsingMLP.pdf vignetteTitles: UsingMLP hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MLP/inst/doc/UsingMLP.R suggestsMe: a4 Package: MLSeq Version: 1.0.0 Depends: R (>= 3.0.0), caret, DESeq2, Biobase, limma, randomForest, edgeR Imports: methods Suggests: knitr, e1071, kernlab, earth, ellipse, fastICA, gam, ipred, klaR, MASS, mda, mgcv, mlbench, nnet, party, pls, pROC, proxy, RANN, spls, affy License: GPL(>=2) MD5sum: 97295040cf3408bdbd10b00c788eacb9 NeedsCompilation: no Title: Machine learning interface for RNA-Seq data Description: This package applies several machine learning methods, including SVM, bagSVM, Random Forest and CART, to RNA-Seq data. biocViews: Bioinformatics, Classification, Clustering Author: Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Izzet Parug Duru, Turgay Unver, Ahmet Ozturk Maintainer: Gokmen Zararsiz VignetteBuilder: knitr source.ver: src/contrib/MLSeq_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MLSeq_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MLSeq_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MLSeq_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MLSeq_1.0.0.tgz vignettes: vignettes/MLSeq/inst/doc/MLSeq.pdf vignetteTitles: MLSeq hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MLSeq/inst/doc/MLSeq.R Package: MMDiff Version: 1.4.1 Depends: R (>= 2.14.0),GenomicRanges,parallel,DiffBind,GMD,Rsamtools Imports: GenomicRanges,IRanges,Biobase Suggests: MMDiffBamSubset License: Artistic-2.0 MD5sum: 717f5e98ec12d22a48b272114eb6c645 NeedsCompilation: no Title: Statistical Testing for ChIP-Seq data sets Description: This package detects statistically significant difference between read enrichment profiles in different ChIP-Seq samples. To take advantage of shape differences it uses Kernel methods (Maximum Mean Discrepancy, MMD). biocViews: ChIPSeq, MultipleComparison Author: Gabriele Schweikert Maintainer: Gabriele Schweikert source.ver: src/contrib/MMDiff_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/MMDiff_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/MMDiff_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/MMDiff_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MMDiff_1.4.1.tgz vignettes: vignettes/MMDiff/inst/doc/MMDiff.pdf vignetteTitles: Analysing ChIP-Seq data with the "MMDiff" package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MMDiff/inst/doc/MMDiff.R Package: mmnet Version: 1.2.2 Depends: R (>= 2.14), igraph, biom Imports: Biobase, RJSONIO, stringr, reshape2, ggplot2, KEGGREST, plyr, XML, RCurl, flexmix, Matrix, methods, tools Suggests: RCytoscape, graph, knitr License: GPL (>= 2) MD5sum: 97646ebce8c97a638d4b8333fee352d3 NeedsCompilation: no Title: A metagenomic pipeline for systems biology Description: This package gives the implementations microbiome metabolic network constructing and analyzing. It introduces a unique metagenomic systems biology approach, mapping metagenomic data to the KEGG global metabolic pathway and constructing a systems-level network. The system-level network and the next topological analysis will be of great help to analysis the various functional properties, including regulation and metabolic functionality of the metagenome. biocViews: GraphsAndNetwork, Sequencing, Pathways, Microbiome, SystemsBiology Author: Yang Cao, Fei Li Maintainer: Yang Cao , Fei Li VignetteBuilder: knitr source.ver: src/contrib/mmnet_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/mmnet_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.1/mmnet_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.1/mmnet_1.2.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mmnet_1.2.2.tgz vignettes: vignettes/mmnet/inst/doc/mmnet.pdf vignetteTitles: mmnet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mmnet/inst/doc/mmnet.R Package: MmPalateMiRNA Version: 1.14.0 Depends: R (>= 2.13.0), methods, Biobase, xtable, limma, statmod, lattice, vsn Imports: limma, lattice, Biobase Suggests: GOstats, graph, Category, org.Mm.eg.db, microRNA, targetscan.Mm.eg.db, RSQLite, DBI, AnnotationDbi, clValid, class, cluster, multtest, RColorBrewer, latticeExtra License: GPL-3 MD5sum: 63f3690037e37209dddc21055f4ca128 NeedsCompilation: no Title: Murine Palate miRNA Expression Analysis Description: R package compendium for the analysis of murine palate miRNA two-color expression data. biocViews: Microarray, TwoChannel, QualityControl, Preprocessing, DifferentialExpression, MultipleComparison, Clustering, GO, Pathways, ReportWriting, SequenceMatching Author: Guy Brock , Partha Mukhopadhyay , Vasyl Pihur , Robert M. Greene , and M. Michele Pisano Maintainer: Guy Brock source.ver: src/contrib/MmPalateMiRNA_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MmPalateMiRNA_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MmPalateMiRNA_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MmPalateMiRNA_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MmPalateMiRNA_1.14.0.tgz vignettes: vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.pdf vignetteTitles: Palate miRNA Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MmPalateMiRNA/inst/doc/MmPalateMiRNA.R Package: mosaics Version: 1.12.2 Depends: R (>= 2.11.1), methods, graphics, Rcpp Imports: MASS, splines, lattice, IRanges LinkingTo: Rcpp Suggests: mosaicsExample Enhances: parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: 0b3ad58ae78599cf22de92289952ced4 NeedsCompilation: yes Title: MOSAiCS (MOdel-based one and two Sample Analysis and Inference for ChIP-Seq) Description: This package provides functions for fitting MOSAiCS, a statistical framework to analyze one-sample or two-sample ChIP-seq data. biocViews: ChIPseq, Sequencing, Transcription, Genetics, Bioinformatics Author: Dongjun Chung, Pei Fen Kuan, Sunduz Keles Maintainer: Dongjun Chung URL: http://groups.google.com/group/mosaics_user_group SystemRequirements: Perl source.ver: src/contrib/mosaics_1.12.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/mosaics_1.12.2.zip win64.binary.ver: bin/windows64/contrib/3.1/mosaics_1.12.2.zip mac.binary.ver: bin/macosx/contrib/3.1/mosaics_1.12.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mosaics_1.12.2.tgz vignettes: vignettes/mosaics/inst/doc/mosaics-example.pdf vignetteTitles: MOSAiCS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mosaics/inst/doc/mosaics-example.R dependsOnMe: jmosaics Package: MotifDb Version: 1.6.0 Depends: R (>= 2.15.0), methods, IRanges, Biostrings Imports: BiocGenerics, rtracklayer Suggests: RUnit, MotIV, seqLogo License: Artistic-2.0 | file LICENSE License_is_FOSS: no License_restricts_use: yes MD5sum: 1a39c1a781ff345802603d94e8f4a0e3 NeedsCompilation: no Title: An Annotated Collection of Protein-DNA Binding Sequence Motifs Description: More than 2000 annotated position frequency matrices from five public source, for multiple organisms biocViews: GenomicSequence, MotifAnnotation Author: Paul Shannon Maintainer: Paul Shannon source.ver: src/contrib/MotifDb_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MotifDb_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MotifDb_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MotifDb_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MotifDb_1.6.0.tgz vignettes: vignettes/MotifDb/inst/doc/MotifDb.pdf vignetteTitles: MotifDb Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/MotifDb/inst/doc/MotifDb.R importsMe: rTRMui suggestsMe: motifStack, PWMEnrich, rTRM, vtpnet Package: motifRG Version: 1.8.0 Depends: R (>= 2.15), Biostrings (>= 2.26), IRanges, seqLogo, parallel, methods, grid, graphics, BSgenome, XVector, BSgenome.Hsapiens.UCSC.hg19 Imports: Biostrings,IRanges,seqLogo,parallel,methods,grid,graphics,XVector License: Artistic-2.0 MD5sum: 74a1930f289429c14bfc7d05fb0d235f NeedsCompilation: no Title: A package for discriminative motif discovery, designed for high throughput sequencing dataset Description: Tools for discriminative motif discovery using regression methods biocViews: Transcription,MotifDiscovery Author: Zizhen Yao Maintainer: Zizhen Yao source.ver: src/contrib/motifRG_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/motifRG_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/motifRG_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/motifRG_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/motifRG_1.8.0.tgz vignettes: vignettes/motifRG/inst/doc/motifRG.pdf vignetteTitles: motifRG: regression-based discriminative motif discovery hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/motifRG/inst/doc/motifRG.R Package: motifStack Version: 1.8.1 Depends: R (>= 2.15.1), methods, grImport, grid, MotIV, ade4 Imports: XML Suggests: RUnit, BiocGenerics, MotifDb, RColorBrewer, BiocStyle License: GPL (>= 2) MD5sum: 6e320167b1c573ef3012c0b2076a8e46 NeedsCompilation: no Title: Plot stacked logos for single or multiple DNA, RNA and amino acid sequence Description: The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motif and amino acid sequence motif. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors. biocViews: SequenceMatching, GenomicsSequence, Visualization Author: Jianhong Ou, Michael Brodsky, Scot Wolfe and Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/motifStack_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/motifStack_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/motifStack_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/motifStack_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/motifStack_1.8.1.tgz vignettes: vignettes/motifStack/inst/doc/motifStack.pdf vignetteTitles: motifStack Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/motifStack/inst/doc/motifStack.R dependsOnMe: dagLogo Package: MotIV Version: 1.20.0 Depends: R (>= 2.10), BiocGenerics (>= 0.1.0) Imports: graphics, grid, methods, IRanges (>= 1.13.5), Biostrings (>= 1.24.0), lattice, rGADEM, stats, utils Suggests: rtracklayer License: GPL-2 Archs: i386, x64 MD5sum: 82c2c6e1fa6b0d89e7e97cbac1ff7f85 NeedsCompilation: yes Title: Motif Identification and Validation Description: This package makes use of STAMP for comparing a set of motifs to a given database (e.g. JASPAR). It can also be used to visualize motifs, motif distributions, modules and filter motifs. biocViews: Microarray, ChIPchip, ChIPSeq, GenomicSequence, MotifAnnotation Author: Eloi Mercier, Raphael Gottardo Maintainer: Eloi Mercier , Raphael Gottardo source.ver: src/contrib/MotIV_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MotIV_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MotIV_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MotIV_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MotIV_1.20.0.tgz vignettes: vignettes/MotIV/inst/doc/MotIV.pdf vignetteTitles: The MotIV users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MotIV/inst/doc/MotIV.R dependsOnMe: motifStack suggestsMe: MotifDb Package: msmsEDA Version: 1.2.0 Depends: R (>= 3.0.1), MSnbase Imports: MASS, gplots, RColorBrewer License: GPL-2 MD5sum: 951dfdaefe80f475952b4d96650f11a9 NeedsCompilation: no Title: Exploratory Data Analysis of LC-MS/MS data by spectral counts Description: Exploratory data analysis to assess the quality of a set of LC-MS/MS experiments, and visualize de influence of the involved factors. biocViews: Software, MassSpectrometry, Proteomics Author: Josep Gregori, Alex Sanchez, and Josep Villanueva Maintainer: Josep Gregori source.ver: src/contrib/msmsEDA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/msmsEDA_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/msmsEDA_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/msmsEDA_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/msmsEDA_1.2.0.tgz vignettes: vignettes/msmsEDA/inst/doc/msmsData-Vignette.pdf vignetteTitles: msmsEDA: Batch effects detection in LC-MSMS experiments hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/msmsEDA/inst/doc/msmsData-Vignette.R dependsOnMe: msmsTests Package: msmsTests Version: 1.2.0 Depends: R (>= 3.0.1), MSnbase, msmsEDA Imports: edgeR, qvalue License: GPL-2 MD5sum: f2c674f8429b710d61c6174960a7dcf8 NeedsCompilation: no Title: LC-MS/MS Differential Expression Tests Description: Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance variables.To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition. biocViews: Software, MassSpectrometry, Proteomics Author: Josep Gregori, Alex Sanchez, and Josep Villanueva Maintainer: Josep Gregori i Font source.ver: src/contrib/msmsTests_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/msmsTests_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/msmsTests_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/msmsTests_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/msmsTests_1.2.0.tgz vignettes: vignettes/msmsTests/inst/doc/msmsTests-Vignette2.pdf, vignettes/msmsTests/inst/doc/msmsTests-Vignette.pdf vignetteTitles: msmsTests: controlling batch effects by blocking, msmsTests: post test filters to improve reproducibility hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/msmsTests/inst/doc/msmsTests-Vignette2.R, vignettes/msmsTests/inst/doc/msmsTests-Vignette.R Package: MSnbase Version: 1.12.1 Depends: R (>= 3.1), methods, BiocGenerics (>= 0.7.1), Biobase (>= 2.15.2), ggplot2, mzR Imports: plyr, IRanges, preprocessCore, vsn, grid, reshape2, stats4, affy, impute, pcaMethods, mzID (>= 1.1.5) Suggests: testthat, zoo, knitr (>= 1.1.0), rols, Rdisop, pRolocdata (>= 1.0.7), msdata Enhances: foreach, doMC, parallel License: Artistic-2.0 MD5sum: 4069b237bed56e828b61ceb4c4afdebb NeedsCompilation: no Title: MSnbase: Base Functions and Classes for MS-based Proteomics Description: Basic plotting, data manipulation and processing of MS-based Proteomics data biocViews: Infrastructure, Proteomics, MassSpectrometry, QualityControl Author: Laurent Gatto with contributions from Guangchuang Yu, Samuel Wieczorek, Vasile-Cosmin Lazar, Vladislav Petyuk and Sebastian Gibb. Maintainer: Laurent Gatto VignetteBuilder: knitr source.ver: src/contrib/MSnbase_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/MSnbase_1.12.1.zip win64.binary.ver: bin/windows64/contrib/3.1/MSnbase_1.12.1.zip mac.binary.ver: bin/macosx/contrib/3.1/MSnbase_1.12.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MSnbase_1.12.1.tgz vignettes: vignettes/MSnbase/inst/doc/MSnbase-demo.pdf, vignettes/MSnbase/inst/doc/MSnbase-development.pdf, vignettes/MSnbase/inst/doc/MSnbase-io.pdf vignetteTitles: Base Functions and Classes for MS-based Proteomics, MSnbase development, MSnbase IO capabilities hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MSnbase/inst/doc/MSnbase-demo.R, vignettes/MSnbase/inst/doc/MSnbase-development.R, vignettes/MSnbase/inst/doc/MSnbase-io.R dependsOnMe: msmsEDA, msmsTests, MSstats, ProCoNA, pRoloc, synapter suggestsMe: isobar, qcmetrics, rpx Package: MSstats Version: 2.2.0 Depends: R (>= 3.0), Rcpp, MSnbase, reshape Imports: lme4,marray,limma,gplots,ggplot2, preprocessCore License: Artistic-2.0 MD5sum: 542fd8ddb2a38d272c795096101f2664 NeedsCompilation: no Title: Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments Description: A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA experiments. biocViews: MassSpectrometry, Proteomics, Software Author: Meena Choi , Ching-Yun Chang , Olga Vitek Maintainer: Meena Choi source.ver: src/contrib/MSstats_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MSstats_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MSstats_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MSstats_2.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MSstats_2.2.0.tgz vignettes: vignettes/MSstats/inst/doc/MSstats.pdf vignetteTitles: Protein quantification in LC-MS,, SRM,, DIA experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MSstats/inst/doc/MSstats.R Package: Mulcom Version: 1.14.1 Depends: R (>= 2.10), fields, Biobase Imports: graphics, grDevices, stats, methods License: GPL-2 Archs: i386, x64 MD5sum: 7225a4ee43de2d072ef7e0565afc58b8 NeedsCompilation: yes Title: Calculates Mulcom test Description: Identification of differentially expressed genes and false discovery rate (FDR) calculation by Multiple Comparison test biocViews: StatisticalMethod, MultipleComparison, Microarray, DifferentialExpression, GeneExpression Author: Claudio Isella Maintainer: Claudio Isella source.ver: src/contrib/Mulcom_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Mulcom_1.14.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Mulcom_1.14.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Mulcom_1.14.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Mulcom_1.14.1.tgz vignettes: vignettes/Mulcom/inst/doc/MulcomVignette.pdf vignetteTitles: Mulcom Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mulcom/inst/doc/MulcomVignette.R Package: multiscan Version: 1.24.0 Depends: R (>= 2.3.0) Imports: Biobase, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 548b3d34c8d057670e6bd069c8882851 NeedsCompilation: yes Title: R package for combining multiple scans Description: Estimates gene expressions from several laser scans of the same microarray biocViews: Microarray, Preprocessing Author: Mizanur Khondoker , Chris Glasbey, Bruce Worton. Maintainer: Mizanur Khondoker source.ver: src/contrib/multiscan_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/multiscan_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/multiscan_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/multiscan_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/multiscan_1.24.0.tgz vignettes: vignettes/multiscan/inst/doc/multiscan.pdf vignetteTitles: An R Package for Estimating Gene Expressions using Multiple Scans hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/multiscan/inst/doc/multiscan.R Package: multtest Version: 2.20.0 Depends: R (>= 2.10), methods, Biobase Imports: survival, MASS, stats4 Suggests: snow License: LGPL Archs: i386, x64 MD5sum: ae02ec8b6692f360018bca4fe9dc3550 NeedsCompilation: yes Title: Resampling-based multiple hypothesis testing Description: Non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments. biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit Maintainer: Katherine S. Pollard source.ver: src/contrib/multtest_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/multtest_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/multtest_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/multtest_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/multtest_2.20.0.tgz vignettes: vignettes/multtest/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4Base, aCGH, BicARE, iPAC, KCsmart, LMGene, PREDA, REDseq, SAGx, siggenes, webbioc importsMe: ABarray, aCGH, adSplit, anota, ChIPpeakAnno, GeneSelector, globaltest, IsoGeneGUI, OCplus, phyloseq, REDseq, RTopper, synapter, webbioc suggestsMe: annaffy, BiocCaseStudies, ecolitk, factDesign, GeneSelector, GGtools, GOstats, GSEAlm, maigesPack, MmPalateMiRNA, oneChannelGUI, pcot2, PECA, topGO, xcms Package: MVCClass Version: 1.38.0 Depends: R (>= 2.1.0), methods License: LGPL MD5sum: 476d1d9b58a2f4f4fc8d24dadc1b5193 NeedsCompilation: no Title: Model-View-Controller (MVC) Classes Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphAndNetwork Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/MVCClass_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/MVCClass_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/MVCClass_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/MVCClass_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/MVCClass_1.38.0.tgz vignettes: vignettes/MVCClass/inst/doc/MVCClass.pdf vignetteTitles: MVCClass hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MVCClass/inst/doc/MVCClass.R dependsOnMe: BioMVCClass Package: mzID Version: 1.2.1 Depends: methods Imports: XML, plyr, parallel, doParallel, foreach, iterators Suggests: knitr License: GPL (>= 2) MD5sum: b52d9e67b16a55ee42d4473ea223a124 NeedsCompilation: no Title: An mzIdentML parser for R Description: A parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less 'pretty' output than a vendor specific parser. Please contact the maintainer with any problems and supply an mzIdentML file so the problems can be fixed quick. biocViews: DataImport, MassSpectrometry, Proteomics Author: Thomas Lin Pedersen, Vladislav A Petyuk with contributions from Laurent Gatto and Sebastian Gibb. Maintainer: Thomas Lin Pedersen VignetteBuilder: knitr source.ver: src/contrib/mzID_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/mzID_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/mzID_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/mzID_1.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mzID_1.2.1.tgz vignettes: vignettes/mzID/inst/doc/HOWTO_mzID.pdf vignetteTitles: Using mzID hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mzID/inst/doc/HOWTO_mzID.R importsMe: MSnbase Package: mzR Version: 1.10.8 Depends: Rcpp (>= 0.10.1), methods, utils Imports: Biobase LinkingTo: Rcpp Suggests: msdata (>= 0.1.9), RUnit, faahKO License: Artistic-2.0 Archs: i386, x64 MD5sum: 1a367557305080fb59fb328ad3c9727e NeedsCompilation: yes Title: parser for netCDF, mzXML, mzData and mzML files (mass spectrometry data) Description: mzR provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML. The netCDF reading code has previously been used in XCMS. biocViews: Infrastructure, DataImport, Proteomics, Metabolomics, MassSpectrometry Author: Bernd Fischer, Steffen Neumann, Laurent Gatto, Qiang Kou Maintainer: Bernd Fischer , Steffen Neumann , Laurent Gatto , Qiang Kou SystemRequirements: GNU make, NetCDF, zlib source.ver: src/contrib/mzR_1.10.8.tar.gz win.binary.ver: bin/windows/contrib/3.1/mzR_1.10.7.zip win64.binary.ver: bin/windows64/contrib/3.1/mzR_1.10.7.zip mac.binary.ver: bin/macosx/contrib/3.1/mzR_1.10.8.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/mzR_1.10.8.tgz vignettes: vignettes/mzR/inst/doc/mzR.pdf vignetteTitles: mzR,, Ramp,, mzXML,, mzData,, mzML hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mzR/inst/doc/mzR.R dependsOnMe: MSnbase, TargetSearch, xcms suggestsMe: qcmetrics Package: NarrowPeaks Version: 1.8.0 Depends: R (>= 2.10.0), splines Imports: GenomicRanges, IRanges, fda, CSAR Suggests: rtracklayer, GenomicRanges, CSAR, BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: f0e7ed15fdedf299d51f170983dea563 NeedsCompilation: yes Title: Analysis of Variation in ChIP-seq using Functional PCA Description: The package applies a functional version of principal component analysis (FPCA) to: (1) Process data in wiggle track format (WIG) commonly produced by ChIP-seq peak callers by applying FPCA over a set of read-enriched regions (ChIP-seq peaks). This is done in order to shorten the genomic locations accounting for a given proportion of variation among the enrichment-score profiles. The function 'narrowpeaks' allows splitting and trimming binding sites in close proximity to each other, narrowing down the length of the putative transcription factor binding sites while preserving the information present in the variability of the dataset and capturing major sources of variation. (2) Analyse differential variation between multiple ChIP-seq samples with replicates. The function 'bigwigdiff' quantifies differences between the shapes, and uses Hotelling's T2 tests on the functional principal component scores to identify significant differences between conditions. biocViews: Visualization, ChIPSeq, Transcription, Genetics, Sequencing, Sequencing Author: Pedro Madrigal , with contributions from Pawel Krajewski Maintainer: Pedro Madrigal source.ver: src/contrib/NarrowPeaks_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/NarrowPeaks_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/NarrowPeaks_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/NarrowPeaks_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NarrowPeaks_1.8.0.tgz vignettes: vignettes/NarrowPeaks/inst/doc/NarrowPeaks.pdf vignetteTitles: NarrowPeaks Vignette. Splitting,, trimming and differential analysis of ChIP-seq peaks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NarrowPeaks/inst/doc/NarrowPeaksDiff.R, vignettes/NarrowPeaks/inst/doc/NarrowPeaks.R Package: ncdfFlow Version: 2.10.30 Depends: R (>= 2.14.0), flowCore, flowViz Imports: Biobase,flowCore,flowViz,methods,zlibbioc Suggests: testthat License: Artistic-2.0 Archs: i386, x64 MD5sum: f5f3055111c904bcea7a76be35493ebb NeedsCompilation: yes Title: ncdfFlow: A package that provides ncdf based storage for flow cytometry data. Description: Provides netCDF storage based methods and functions for manipulation of flow cytometry data. biocViews: FlowCytometry Author: Mike Jiang,Greg Finak,N. Gopalakrishnan Maintainer: Mike Jiang SystemRequirements: hdf5 (>= 1.8.0) source.ver: src/contrib/ncdfFlow_2.10.30.tar.gz win.binary.ver: bin/windows/contrib/3.1/ncdfFlow_2.10.30.zip win64.binary.ver: bin/windows64/contrib/3.1/ncdfFlow_2.10.30.zip mac.binary.ver: bin/macosx/contrib/3.1/ncdfFlow_2.10.30.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ncdfFlow_2.10.30.tgz vignettes: vignettes/ncdfFlow/inst/doc/ncdfFlow.pdf vignetteTitles: Basic Functions for Flow Cytometry Data hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ncdfFlow/inst/doc/ncdfFlow.R Package: NCIgraph Version: 1.12.0 Depends: graph, R (>= 2.10.0) Imports: graph, KEGGgraph, methods, RBGL, RCytoscape, R.methodsS3 Suggests: Rgraphviz Enhances: DEGraph License: GPL-3 MD5sum: 25bb25f6cc57566e34aaac4a4d74768a NeedsCompilation: no Title: Pathways from the NCI Pathways Database Description: Provides various methods to load the pathways from the NCI Pathways Database in R graph objects and to re-format them. biocViews: Pathways, GraphAndNetwork Author: Laurent Jacob Maintainer: Laurent Jacob source.ver: src/contrib/NCIgraph_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/NCIgraph_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/NCIgraph_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/NCIgraph_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NCIgraph_1.12.0.tgz vignettes: vignettes/NCIgraph/inst/doc/NCIgraph.pdf vignetteTitles: NCIgraph: networks from the NCI pathway integrated database as graphNEL objects. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NCIgraph/inst/doc/NCIgraph.R importsMe: DEGraph suggestsMe: DEGraph Package: neaGUI Version: 1.2.0 Depends: tcltk Imports: hwriter Suggests: AnnotationDbi, org.Hs.eg.db, KEGG.db, GO.db, reactome.db, RUnit, GOstats,hwriter License: GPL-2 MD5sum: dca2a7fecf364a173a714454c1cd9c3b NeedsCompilation: no Title: An R package to perform the network enrichment analysis (NEA). Description: neaGUI is an easy to use R package developed to perform the network enrichment analysis (NEA) proposed by Alexeyenko et al. (2012). The NEA method extends the overlap statistics in GSEA to network links between genes in the experimental set and those in the functional categories by exploiting biological information in terms of gene interaction network. The neaGUI requires the following R packages: tcltk, KEGG.db, GO.db, reactome.db, org.Hs.eg.db, AnnotationDbi, and hwriter. biocViews: Microarray, DifferentialExpression, GUI Author: Setia Pramana, Woojoo Lee, Yudi Pawitan Maintainer: Setia Pramana source.ver: src/contrib/neaGUI_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/neaGUI_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/neaGUI_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/neaGUI_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/neaGUI_1.2.0.tgz vignettes: vignettes/neaGUI/inst/doc/neaGUI_vignette.pdf vignetteTitles: neaGUI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/neaGUI/inst/doc/neaGUI_vignette.R Package: nem Version: 2.38.0 Depends: R (>= 2.0), e1071 (>= 1.5), graph (>= 1.24), plotrix, limma, cluster (>= 1.11), statmod, Hmisc, Rgraphviz Imports: boot, e1071, graph, graphics, grDevices, methods, RBGL (>= 1.8.1), RColorBrewer, stats, utils, Rgraphviz Suggests: Biobase (>= 1.10) Enhances: doMC, Rglpk License: GPL (>= 2) Archs: i386, x64 MD5sum: 316a9773958ed128eebdb81e2724a571 NeedsCompilation: yes Title: (Dynamic) Nested Effects Models and Deterministic Effects Propagation Networks to reconstruct phenotypic hierarchies Description: The package 'nem' allows to reconstruct features of pathways from the nested structure of perturbation effects. It takes as input (1.) a set of pathway components, which were perturbed, and (2.) phenotypic readout of these perturbations (e.g. gene expression, protein expression). The output is a directed graph representing the phenotypic hierarchy. biocViews: Microarray, GraphAndNetwork, Pathways Author: Holger Froehlich, Florian Markowetz, Achim Tresch, Theresa Niederberger, Christian Bender, Matthias Maneck, Claudio Lottaz, Tim Beissbarth Maintainer: Holger Froehlich URL: http://www.bioconductor.org source.ver: src/contrib/nem_2.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/nem_2.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/nem_2.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/nem_2.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/nem_2.38.0.tgz vignettes: vignettes/nem/inst/doc/nem.pdf vignetteTitles: Nested Effects Models - An example in Drosophila immune response hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nem/inst/doc/nem.R dependsOnMe: lpNet suggestsMe: rBiopaxParser Package: NetPathMiner Version: 1.0.4 Depends: R (>= 3.0.2), igraph (>= 0.6) Suggests: rBiopaxParser (>= 2.1), RCurl, RCytoscape License: GPL (>= 2) Archs: i386, x64 MD5sum: 18f473abdb8a3fa73980df872db54fbe NeedsCompilation: yes Title: NetPathMiner for Biological Network Construction, Path Mining and Visualization Description: NetPathMiner is a general framework for network path mining using genome-scale networks. It constructs networks from KGML, SBML and BioPAX files, providing three network representations, metabolic, reaction and gene representations. NetPathMiner finds active paths and applies machine learning methods to summarize found paths for easy interpretation. It also provides static and interactive visualizations of networks and paths to aid manual investigation. biocViews: GraphAndNetwork, Pathways, Network, Clustering, Classification Author: Ahmed Mohamed , Tim Hancock , Ichigaku Takigawa , Nicolas Wicker Maintainer: Ahmed Mohamed URL: https://github.com/ahmohamed/NetPathMiner SystemRequirements: libxml2, libSBML (>= 5.5) source.ver: src/contrib/NetPathMiner_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/NetPathMiner_1.0.4.zip win64.binary.ver: bin/windows64/contrib/3.1/NetPathMiner_1.0.4.zip mac.binary.ver: bin/macosx/contrib/3.1/NetPathMiner_1.0.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NetPathMiner_1.0.4.tgz vignettes: vignettes/NetPathMiner/inst/doc/NPMVignette.pdf vignetteTitles: NetPathMiner Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NetPathMiner/inst/doc/NPMVignette.R Package: netresponse Version: 1.16.0 Depends: R (>= 2.15.1), dmt, igraph, infotheo, ggplot2, graph, mclust, methods, minet, parallel, qvalue, RColorBrewer, reshape, Rgraphviz License: GPL (>=2) Archs: i386, x64 MD5sum: f789559fb3f3abb8808ab5f9d7000d93 NeedsCompilation: yes Title: netresponse: functional network analysis Description: Algorithms for functional network analysis. Includes an implementation of a variational Dirichlet process Gaussian mixture model for nonparametric mixture modeling. biocViews: CellBiology, Clustering, GeneExpression, Genetics, Network, GraphAndNetwork, DifferentialExpression, Microarray, Transcription Author: Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen Maintainer: Leo Lahti URL: https://github.com/antagomir/netresponse source.ver: src/contrib/netresponse_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/netresponse_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/netresponse_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/netresponse_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/netresponse_1.16.0.tgz vignettes: vignettes/netresponse/inst/doc/netresponse.pdf vignetteTitles: netresponse hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/netresponse/inst/doc/netresponse.R Package: NetSAM Version: 1.4.0 Depends: R (>= 2.15.1), methods, igraph (>= 0.6-1), seriation (>= 1.0-6), graph (>= 1.34.0) Imports: methods Suggests: RUnit, BiocGenerics License: LGPL MD5sum: 7fcbc0c3a987cea9dcd47eb13e555beb NeedsCompilation: no Title: Network Seriation And Modularization Description: The NetSAM (Network Seriation and Modularization) package takes an edge-list representation of a network as an input, performs network seriation and modularization analysis, and generates as files that can be used as an input for the one-dimensional network visualization tool NetGestalt (http://www.netgestalt.org) or other network analysis. biocViews: Visualization, Network Author: Jing Wang Maintainer: Bing Zhang source.ver: src/contrib/NetSAM_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/NetSAM_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/NetSAM_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/NetSAM_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NetSAM_1.4.0.tgz vignettes: vignettes/NetSAM/inst/doc/NetSAM.pdf vignetteTitles: NetSAM hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NetSAM/inst/doc/NetSAM.R Package: networkBMA Version: 1.6.0 Depends: R (>= 2.15.0), stats, utils, BMA, Rcpp (>= 0.10.3), RcppArmadillo (>= 0.3.810.2), RcppEigen (>= 0.3.1.2.1) LinkingTo: Rcpp, RcppArmadillo, RcppEigen License: GPL (>= 2) Archs: i386, x64 MD5sum: 30c61a09ff8913a1b5f7ffb69a901f60 NeedsCompilation: yes Title: Regression-based network inference using Bayesian Model Averaging Description: An extension of Bayesian Model Averaging (BMA) for network construction using time series gene expression data. Includes assessment functions and sample test data. biocViews: GraphsAndNetworks, NetworkInference Author: Chris Fraley, Wm. Chad Young, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo) Maintainer: Ka Yee Yeung source.ver: src/contrib/networkBMA_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/networkBMA_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/networkBMA_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/networkBMA_1.6.0.tgz vignettes: vignettes/networkBMA/inst/doc/networkBMA.pdf vignetteTitles: networkBMA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/networkBMA/inst/doc/networkBMA.R Package: nnNorm Version: 2.28.0 Depends: R(>= 2.2.0), marray Imports: graphics, grDevices, marray, methods, nnet, stats License: LGPL MD5sum: 9bb405ecd5d96c47e14836272a00a578 NeedsCompilation: no Title: Spatial and intensity based normalization of cDNA microarray data based on robust neural nets Description: This package allows to detect and correct for spatial and intensity biases with two-channel microarray data. The normalization method implemented in this package is based on robust neural networks fitting. biocViews: Microarray, TwoChannel, Preprocessing Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca URL: http://bioinformaticsprb.med.wayne.edu/tarca/ source.ver: src/contrib/nnNorm_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/nnNorm_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/nnNorm_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/nnNorm_2.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/nnNorm_2.28.0.tgz vignettes: vignettes/nnNorm/inst/doc/nnNorm.pdf vignetteTitles: nnNorm Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nnNorm/inst/doc/nnNorm.R Package: NOISeq Version: 2.6.0 Depends: R (>= 2.13.0), methods, Biobase (>= 2.13.11), splines (>= 3.0.1) License: Artistic-2.0 MD5sum: ef00323ece7de61a420fd2cb221fe03f NeedsCompilation: no Title: Exploratory analysis and differential expression for RNA-seq data Description: Analysis of RNA-seq expression data or other similar kind of data. Exploratory plots to evualuate saturation, count distribution, expression per chromosome, type of detected features, features length, etc. Differential expression between two experimental conditions with no parametric assumptions. biocViews: RNASeq, DifferentialExpression, Visualization, Sequencing Author: Sonia Tarazona, Pedro Furio-Tari, Alberto Ferrer and Ana Conesa Maintainer: Sonia Tarazona source.ver: src/contrib/NOISeq_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/NOISeq_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/NOISeq_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/NOISeq_2.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NOISeq_2.6.0.tgz vignettes: vignettes/NOISeq/inst/doc/NOISeq.pdf, vignettes/NOISeq/inst/doc/QCreport.pdf vignetteTitles: NOISeq User's Guide, QCreport.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NOISeq/inst/doc/NOISeq.R dependsOnMe: metaSeq importsMe: metaseqR suggestsMe: compcodeR Package: nondetects Version: 1.0.0 Depends: R (>= 3.0.2), Biobase (>= 2.22.0) Imports: utils, methods, HTqPCR (>= 1.16.0) Suggests: BiocStyle (>= 1.0.0), RUnit, BiocGenerics (>= 0.8.0) License: GPL (>= 2) MD5sum: 0fcb467c97b167f15b9184ac77ef4431 NeedsCompilation: no Title: Non-detects in qPCR data Description: Methods to model and impute non-detects in the results of qPCR experiments. biocViews: Software, AssayDomain, GeneExpression, Technology, qPCR, WorkflowStep, Preprocessing Author: Matthew N. McCall Maintainer: Matthew N. McCall source.ver: src/contrib/nondetects_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/nondetects_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/nondetects_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/nondetects_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/nondetects_1.0.0.tgz vignettes: vignettes/nondetects/inst/doc/nondetects.pdf vignetteTitles: nondetects - vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nondetects/inst/doc/nondetects.R Package: NormqPCR Version: 1.10.2 Depends: R(>= 2.14.0), stats, RColorBrewer, Biobase, methods, ReadqPCR, qpcR License: LGPL-3 MD5sum: dbd3cf88cf3f18afd91b2558db429a23 NeedsCompilation: no Title: Functions for normalisation of RT-qPCR data Description: Functions for the selection of optimal reference genes and the normalisation of real-time quantitative PCR data. biocViews: MicrotitrePlateAssay, GeneExpression, qPCR Author: Matthias Kohl, James Perkins, Nor Izayu Abdul Rahman Maintainer: James Perkins URL: www.bioconductor.org/packages/release/bioc/html/NormqPCR.html source.ver: src/contrib/NormqPCR_1.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/NormqPCR_1.10.2.zip win64.binary.ver: bin/windows64/contrib/3.1/NormqPCR_1.10.2.zip mac.binary.ver: bin/macosx/contrib/3.1/NormqPCR_1.10.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NormqPCR_1.10.2.tgz vignettes: vignettes/NormqPCR/inst/doc/NormqPCR.pdf vignetteTitles: NormqPCR: Functions for normalisation of RT-qPCR data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NormqPCR/inst/doc/NormqPCR.R Package: npGSEA Version: 1.0.0 Depends: GSEABase (>= 1.24.0) Imports: Biobase, methods, BiocGenerics, graphics, stats Suggests: ALL, genefilter, limma, hgu95av2.db, ReportingTools, BiocStyle License: Artistic-2.0 MD5sum: 6284687ede7a2c47421823e5cbcc2142 NeedsCompilation: no Title: Permutation approximation methods for gene set enrichment analysis (non-permutation GSEA) Description: Current gene set enrichment methods rely upon permutations for inference. These approaches are computationally expensive and have minimum achievable p-values based on the number of permutations, not on the actual observed statistics. We have derived three parametric approximations to the permutation distributions of two gene set enrichment test statistics. We are able to reduce the computational burden and granularity issues of permutation testing with our method, which is implemented in this package. npGSEA calculates gene set enrichment statistics and p-values without the computational cost of permutations. It is applicable in settings where one or many gene sets are of interest. There are also built-in plotting functions to help users visualize results. biocViews: GeneSetEnrichment, Microarray, StatisticalMethod, Pathways Author: Jessica Larson and Art Owen Maintainer: Jessica Larson source.ver: src/contrib/npGSEA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/npGSEA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/npGSEA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/npGSEA_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/npGSEA_1.0.0.tgz vignettes: vignettes/npGSEA/inst/doc/npGSEA.pdf vignetteTitles: Running gene set enrichment analysis with the "npGSEA" package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/npGSEA/inst/doc/npGSEA.R Package: NTW Version: 1.14.0 Depends: R (>= 2.3.0) Imports: mvtnorm, stats, utils License: GPL-2 MD5sum: 08ea38c2466ded6c25ad50b513d54bd7 NeedsCompilation: no Title: Predict gene network using an Ordinary Differential Equation (ODE) based method Description: This package predicts the gene-gene interaction network and identifies the direct transcriptional targets of the perturbation using an ODE (Ordinary Differential Equation) based method. biocViews: Preprocessing Author: Wei Xiao, Yin Jin, Darong Lai, Xinyi Yang, Yuanhua Liu, Christine Nardini Maintainer: Yuanhua Liu source.ver: src/contrib/NTW_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/NTW_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/NTW_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/NTW_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NTW_1.14.0.tgz vignettes: vignettes/NTW/inst/doc/NTW.pdf vignetteTitles: NTW vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NTW/inst/doc/NTW.R Package: nucleR Version: 1.12.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.5), Biobase (>= 2.15.1), ShortRead, parallel Imports: methods, BiocGenerics, IRanges, Biobase, ShortRead, GenomicRanges, stats Enhances: htSeqTools License: LGPL (>= 3) MD5sum: 067dda11615822783cfa34cba5f605d5 NeedsCompilation: no Title: Nucleosome positioning package for R Description: Nucleosome positioning for Tiling Arrays and Next Generation Sequencing Experiments biocViews: ChIPSeq, Microarray, Sequencing, Genetics Author: Oscar Flores, David Rossell Maintainer: Oscar Flores source.ver: src/contrib/nucleR_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/nucleR_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/nucleR_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/nucleR_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/nucleR_1.12.0.tgz vignettes: vignettes/nucleR/inst/doc/nucleR.pdf vignetteTitles: Quick analysis of nucleosome positioning experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nucleR/inst/doc/nucleR.R Package: nudge Version: 1.30.0 Imports: stats License: GPL-2 MD5sum: fb12d11c3677ed7610062d1a04d7f9a1 NeedsCompilation: no Title: Normal Uniform Differential Gene Expression detection Description: Package for normalizing microarray data in single and multiple replicate experiments and fitting a normal-uniform mixture to detect differentially expressed genes in the cases where the two samples are being compared directly or indirectly (via a common reference sample) biocViews: Microarray, TwoChannel, DifferentialExpression Author: N. Dean and A. E. Raftery Maintainer: N. Dean source.ver: src/contrib/nudge_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/nudge_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/nudge_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/nudge_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/nudge_1.30.0.tgz vignettes: vignettes/nudge/inst/doc/nudge.vignette.pdf vignetteTitles: nudge Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nudge/inst/doc/nudge.vignette.R Package: NuPoP Version: 1.14.1 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: b6568a8fe3be5202df2993f1257f9b87 NeedsCompilation: yes Title: An R package for nucleosome positioning prediction Description: NuPoP is an R package for Nucleosome Positioning Prediction.This package is built upon a duration hidden Markov model proposed in Xi et al, 2010; Wang et al, 2008. The core of the package was written in Fotran. In addition to the R package, a stand-alone Fortran software tool is also available at http://nucleosome.stats.northwestern.edu. biocViews: Genetics,Visualization,Classification Author: Ji-Ping Wang ; Liqun Xi Maintainer: Ji-Ping Wang source.ver: src/contrib/NuPoP_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/NuPoP_1.14.1.zip win64.binary.ver: bin/windows64/contrib/3.1/NuPoP_1.14.1.zip mac.binary.ver: bin/macosx/contrib/3.1/NuPoP_1.14.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/NuPoP_1.14.1.tgz vignettes: vignettes/NuPoP/inst/doc/NuPoP-intro.pdf vignetteTitles: An R package for Nucleosome positioning prediction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NuPoP/inst/doc/NuPoP-intro.R Package: occugene Version: 1.24.0 Depends: R (>= 2.0.0) License: GPL (>= 2) MD5sum: c4a26d080d6975b7e95bc16003a2b07f NeedsCompilation: no Title: Functions for Multinomial Occupancy Distribution Description: Statistical tools for building random mutagenesis libraries for prokaryotes. The package has functions for handling the occupancy distribution for a multinomial and for estimating the number of essential genes in random transposon mutagenesis libraries. biocViews: Annotation, Pathways Author: Oliver Will Maintainer: Oliver Will source.ver: src/contrib/occugene_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/occugene_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/occugene_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/occugene_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/occugene_1.24.0.tgz vignettes: vignettes/occugene/inst/doc/occugene.pdf vignetteTitles: occugene hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/occugene/inst/doc/occugene.R Package: OCplus Version: 1.38.0 Depends: R (>= 2.1.0), akima Imports: multtest (>= 1.7.3), graphics, grDevices, stats License: LGPL MD5sum: 880bfae9a50208b62caa5e6d0e5f4fc9 NeedsCompilation: no Title: Operating characteristics plus sample size and local fdr for microarray experiments Description: This package allows to characterize the operating characteristics of a microarray experiment, i.e. the trade-off between false discovery rate and the power to detect truly regulated genes. The package includes tools both for planned experiments (for sample size assessment) and for already collected data (identification of differentially expressed genes). biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Yudi Pawitan and Alexander Ploner Maintainer: Alexander Ploner source.ver: src/contrib/OCplus_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OCplus_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OCplus_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OCplus_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OCplus_1.38.0.tgz vignettes: vignettes/OCplus/inst/doc/OCplus.pdf vignetteTitles: OCplus Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OCplus/inst/doc/OCplus.R Package: oligo Version: 1.28.3 Depends: R (>= 2.15.0), BiocGenerics (>= 0.3.2), oligoClasses (>= 1.24.0), Biobase (>= 2.17.8), Biostrings (>= 2.25.12) Imports: affyio (>= 1.25.0), affxparser (>= 1.29.11), BiocGenerics (>= 0.3.2), DBI (>= 0.2-5), ff, graphics, methods, preprocessCore (>= 1.19.0), splines, stats, stats4, utils, zlibbioc LinkingTo: preprocessCore Suggests: hapmap100kxba, pd.mapping50k.xba240, pd.huex.1.0.st.v2, pd.hg18.60mer.expr, pd.hugene.1.0.st.v1, maqcExpression4plex, genefilter, limma, RColorBrewer, oligoData, RUnit Enhances: ff, doMC, doMPI License: LGPL (>= 2) Archs: i386, x64 MD5sum: 97e95000d334f276faff240274d05733 NeedsCompilation: yes Title: Preprocessing tools for oligonucleotide arrays. Description: A package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files). biocViews: Microarray, OneChannel, TwoChannel, Preprocessing, SNP, DifferentialExpression, ExonArray, GeneExpression, DataImport Author: Benilton Carvalho and Rafael Irizarry. Contributors: Ben Bolstad, Vincent Carey, Wolfgang Huber, Harris Jaffee, Jim MacDonald, Matt Settles Maintainer: Benilton Carvalho source.ver: src/contrib/oligo_1.28.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/oligo_1.28.3.zip win64.binary.ver: bin/windows64/contrib/3.1/oligo_1.28.3.zip mac.binary.ver: bin/macosx/contrib/3.1/oligo_1.28.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/oligo_1.28.3.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: ITALICS, pdInfoBuilder, SCAN.UPC, waveTiling importsMe: charm, cn.farms, frma, ITALICS suggestsMe: BiocGenerics, fastseg, frmaTools Package: oligoClasses Version: 1.26.0 Depends: R (>= 2.14) Imports: BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), methods, graphics, IRanges (>= 1.13.30), GenomicRanges, Biostrings (>= 2.23.6), affyio (>= 1.23.2), ff, foreach, BiocInstaller, utils Suggests: RSQLite, hapmapsnp5, hapmapsnp6, pd.genomewidesnp.6, pd.genomewidesnp.5, pd.mapping50k.hind240, pd.mapping50k.xba240, pd.mapping250k.sty, pd.mapping250k.nsp, genomewidesnp6Crlmm (>= 1.0.7), genomewidesnp5Crlmm (>= 1.0.6), crlmm, SNPchip, VanillaICE, RUnit, human370v1cCrlmm Enhances: doMC, doMPI, doSNOW, doParallel, doRedis License: GPL (>= 2) MD5sum: 648ce3fe7d6af5ccdb31507beb3d5234 NeedsCompilation: no Title: Classes for high-throughput arrays supported by oligo and crlmm Description: This package contains class definitions, validity checks, and initialization methods for classes used by the oligo and crlmm packages. biocViews: Infrastructure Author: Benilton Carvalho and Robert Scharpf Maintainer: Benilton Carvalho and Robert Scharpf source.ver: src/contrib/oligoClasses_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/oligoClasses_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/oligoClasses_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/oligoClasses_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/oligoClasses_1.26.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: cn.farms, crlmm, mBPCR, oligo, waveTiling importsMe: affycoretools, ArrayTV, charm, frma, ITALICS, MinimumDistance, SNPchip, VanillaICE suggestsMe: BiocGenerics Package: OLIN Version: 1.42.0 Depends: R (>= 2.10), methods, locfit, marray Imports: graphics, grDevices, limma, marray, methods, stats Suggests: convert License: GPL-2 MD5sum: 62248b41a62daa8717fae0df3ca167ec NeedsCompilation: no Title: Optimized local intensity-dependent normalisation of two-color microarrays Description: Functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data biocViews: Microarray, TwoChannel, QualityControl, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/OLIN/index.html source.ver: src/contrib/OLIN_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OLIN_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OLIN_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OLIN_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OLIN_1.42.0.tgz vignettes: vignettes/OLIN/inst/doc/OLIN.pdf vignetteTitles: Introduction to OLIN hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OLIN/inst/doc/OLIN.R dependsOnMe: OLINgui importsMe: OLINgui suggestsMe: maigesPack Package: OLINgui Version: 1.38.0 Depends: R (>= 2.0.0), OLIN (>= 1.4.0) Imports: graphics, marray, OLIN, tcltk, tkWidgets, widgetTools License: GPL-2 MD5sum: 522ff8ba913bda0cd796105185410944 NeedsCompilation: no Title: Graphical user interface for OLIN Description: Graphical user interface for the OLIN package biocViews: Microarray, TwoChannel, QualityControl, Preprocessing, Visualization Author: Matthias Futschik Maintainer: Matthias Futschik URL: http://itb.biologie.hu-berlin.de/~futschik/software/R/OLIN/index.html source.ver: src/contrib/OLINgui_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OLINgui_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OLINgui_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OLINgui_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OLINgui_1.38.0.tgz vignettes: vignettes/OLINgui/inst/doc/OLINgui.pdf vignetteTitles: Introduction to OLINgui hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OLINgui/inst/doc/OLINgui.R Package: omicade4 Version: 1.4.4 Depends: R (>= 3.0.0), ade4 Imports: made4 Suggests: BiocStyle License: GPL-2 MD5sum: 00616599a08c012f58dcf87fd3c62d77 NeedsCompilation: no Title: Multiple co-inertia analysis of omics datasets Description: Multiple co-inertia analysis of omics datasets biocViews: Software, Clustering, Classification, MultipleComparison Author: Chen Meng, Aedin Culhane, Amin M. Gholami. Maintainer: Chen Meng source.ver: src/contrib/omicade4_1.4.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/omicade4_1.4.4.zip win64.binary.ver: bin/windows64/contrib/3.1/omicade4_1.4.4.zip mac.binary.ver: bin/macosx/contrib/3.1/omicade4_1.4.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/omicade4_1.4.4.tgz vignettes: vignettes/omicade4/inst/doc/omicade4.pdf vignetteTitles: Using omicade4 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/omicade4/inst/doc/omicade4.R Package: OmicCircos Version: 1.2.0 Depends: R (>= 2.14.0),methods,GenomicRanges Suggests: knitr License: GPL-2 MD5sum: ba5505b5a55b46dd2d38f3f997678d50 NeedsCompilation: no Title: High-quality circular visualization of omic data Description: OmicCircos is an R application and package for generating high-quality circular maps for omic data biocViews: Visualization, StatisticalMethod, Annotation Author: Ying Hu Chunhua Yan Maintainer: Ying Hu VignetteBuilder: knitr source.ver: src/contrib/OmicCircos_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OmicCircos_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OmicCircos_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OmicCircos_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OmicCircos_1.2.0.tgz vignettes: vignettes/OmicCircos/inst/doc/OmicCircos_vignette.pdf vignetteTitles: OmicCircos vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OmicCircos/inst/doc/OmicCircos_vignette.R Package: oneChannelGUI Version: 1.30.6 Depends: Biobase, affylmGUI, tkrplot, tkWidgets, IRanges, Rsamtools (>= 1.13.1), Biostrings, siggenes, chimera Suggests: annotate, genefilter, maSigPro, pamr, pdmclass, ChIPpeakAnno, chipseq, BSgenome, Rgraphviz, affy ,annaffy, affyPLM, multtest, ssize, sizepower, RankProd, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, edgeR, metaArray, MergeMaid, biomaRt, GenomeGraphs,AffyCompatible, rtracklayer, Genominator, EDASeq, limma, DESeq, DEXSeq, goseq, hugene10sttranscriptcluster.db, mogene10sttranscriptcluster.db, ragene10sttranscriptcluster.db, GOstats, AnnotationDbi, preprocessCore, baySeq, HuExExonProbesetLocation, MoExExonProbesetLocation, RaExExonProbesetLocation, snow, RmiR, RmiR.Hs.miRNA, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm9, BSgenome.Rnorvegicus.UCSC.rn4, R.utils, cummeRbund License: Artistic-2.0 MD5sum: 4890ff4c88aafb986420a5799f03c8bb NeedsCompilation: no Title: A graphical interface designed to facilitate analysis of microarrays and miRNA/RNA-seq data on laptops. Description: This package was developed to simplify the use of Bioconductor tools for beginners having limited or no experience in writing R code. This library provides a graphical interface for microarray gene and exon level analysis as well as miRNA/mRNA-seq data analysis. biocViews: Sequencing, RNASeq, Microarray, OneChannel, DataImport, QualityControl, Preprocessing, StatisticalMethod, DifferentialExpression, GUI, MultipleComparison Author: Raffale A Calogero, Bioinformatics and Genomics Unit, Molecular Biotechnology Center, Torino (Italy) Maintainer: Raffaele A Calogero URL: http://www.bioinformatica.unito.it/oneChannelGUI/ source.ver: src/contrib/oneChannelGUI_1.30.6.tar.gz win.binary.ver: bin/windows/contrib/3.1/oneChannelGUI_1.30.6.zip win64.binary.ver: bin/windows64/contrib/3.1/oneChannelGUI_1.30.6.zip mac.binary.ver: bin/macosx/contrib/3.1/oneChannelGUI_1.30.6.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/oneChannelGUI_1.30.6.tgz vignettes: vignettes/oneChannelGUI/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/oneChannelGUI/inst/doc/Exon-level.analysis.R, vignettes/oneChannelGUI/inst/doc/gene-level.analysis.R, vignettes/oneChannelGUI/inst/doc/install.R, vignettes/oneChannelGUI/inst/doc/RNAseq.R, vignettes/oneChannelGUI/inst/doc/standAloneFunctions.R Package: ontoCAT Version: 1.16.0 Depends: rJava, methods License: Apache License 2.0 MD5sum: 47ad7fa0c1bf2863a3fe186cd0f39e92 NeedsCompilation: no Title: Ontology traversal and search Description: The ontoCAT R package provides a simple interface to ontologies described in widely used standard formats, stored locally in the filesystem or accessible online. The full version of ontoCAT R package also supports searching for ontology terms across multiple ontologies and in major ontology repositories, as well as a number of advanced ontology navigation functions: www.ontocat.org/wiki/r biocViews: Classification, DataRepresentation Author: Natalja Kurbatova, Tomasz Adamusiak, Pavel Kurnosov, Morris Swertz, Misha Kapushevsky Maintainer: Natalja Kurbatova source.ver: src/contrib/ontoCAT_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ontoCAT_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ontoCAT_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ontoCAT_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ontoCAT_1.16.0.tgz vignettes: vignettes/ontoCAT/inst/doc/ontoCAT.pdf vignetteTitles: ontoCAT package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ontoCAT/inst/doc/ontoCAT.R suggestsMe: RMassBank Package: openCyto Version: 1.2.11 Depends: methods,flowWorkspace Imports: Biobase,gtools,flowCore,flowViz,flowStats,flowClust,MASS,clue,plyr,RBGL,Rgraphviz,graph,data.table,ks,RColorBrewer,lattice,rrcov,R.utils Suggests: flowWorkspaceData, knitr, testthat, utils, tools License: Artistic-2.0 Archs: i386, x64 MD5sum: 9d3cf2d35b07606326c7fc61d3db463c NeedsCompilation: yes Title: Hierarchical Gating Pipeline for flow cytometry data Description: This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy. biocViews: FlowCytometry, DataImport, Preprocessing, DataRepresentation Author: Mike Jiang, John Ramey, Greg Finak, Raphael Gottardo Maintainer: Mike Jiang VignetteBuilder: knitr source.ver: src/contrib/openCyto_1.2.11.tar.gz win.binary.ver: bin/windows/contrib/3.1/openCyto_1.2.11.zip win64.binary.ver: bin/windows64/contrib/3.1/openCyto_1.2.11.zip mac.binary.ver: bin/macosx/contrib/3.1/openCyto_1.2.11.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/openCyto_1.2.11.tgz vignettes: vignettes/openCyto/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/openCyto/inst/doc/HowToWriteCSVTemplate.R, vignettes/openCyto/inst/doc/openCytoVignette.R htmlDocs: vignettes/openCyto/inst/doc/HowToWriteCSVTemplate.html, vignettes/openCyto/inst/doc/openCytoVignette.html htmlTitles: "How to write a csv gating template", "An Introduction to the openCyto package" Package: OrderedList Version: 1.36.0 Depends: R (>= 2.1.0), Biobase (>= 1.5.12), twilight (>= 1.9.2), methods Imports: Biobase, graphics, methods, stats, twilight License: GPL (>= 2) MD5sum: 7377463b72f2385c003a0799426a3c96 NeedsCompilation: no Title: Similarities of Ordered Gene Lists Description: Detection of similarities between ordered lists of genes. Thereby, either simple lists can be compared or gene expression data can be used to deduce the lists. Significance of similarities is evaluated by shuffling lists or by resampling in microarray data, respectively. biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Xinan Yang, Stefanie Scheid, Claudio Lottaz Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/OrderedList_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OrderedList_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OrderedList_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OrderedList_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OrderedList_1.36.0.tgz vignettes: vignettes/OrderedList/inst/doc/tr_2006_01.pdf vignetteTitles: Similarities of Ordered Gene Lists hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OrderedList/inst/doc/tr_2006_01.R Package: OrganismDbi Version: 1.6.0 Depends: R (>= 2.14.0), methods, AnnotationDbi (>= 1.16.10), GenomicFeatures Imports: BiocGenerics, graph, RBGL, AnnotationDbi Suggests: Homo.sapiens, Rattus.norvegicus, RUnit License: Artistic-2.0 MD5sum: 8f6a468d2edc730f5bd8d276bf793495 NeedsCompilation: no Title: Software to enable the smooth interfacing of different database packages. Description: The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods. biocViews: Annotation, Infrastructure Author: Marc Carlson, Herve Pages, Martin Morgan, Valerie Obenchain Maintainer: Biocore Data Team source.ver: src/contrib/OrganismDbi_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OrganismDbi_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OrganismDbi_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OrganismDbi_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OrganismDbi_1.6.0.tgz vignettes: vignettes/OrganismDbi/inst/doc/OrganismDbi.pdf vignetteTitles: OrganismDbi: A meta framework for Annotation Packages hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OrganismDbi/inst/doc/OrganismDbi.R Package: OSAT Version: 1.12.0 Depends: methods,stats Suggests: xtable, Biobase License: Artistic-2.0 MD5sum: 72d97d1427b8f3a69fe1510e64cd52b3 NeedsCompilation: no Title: OSAT: Optimal Sample Assignment Tool Description: A sizable genomics study such as microarray often involves the use of multiple batches (groups) of experiment due to practical complication. To minimize batch effects, a careful experiment design should ensure the even distribution of biological groups and confounding factors across batches. OSAT (Optimal Sample Assignment Tool) is developed to facilitate the allocation of collected samples to different batches. With minimum steps, it produces setup that optimizes the even distribution of samples in groups of biological interest into different batches, reducing the confounding or correlation between batches and the biological variables of interest. It can also optimize the even distribution of confounding factors across batches. Our tool can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideal balanced RCBD. OSAT provides a number of predefined layout for some of the most commonly used genomics platform. Related paper can be find at http://www.biomedcentral.com/1471-2164/13/689 . biocViews: DataRepresentation, Visualization, ExperimentalDesign, QualityControl Author: Li Yan Maintainer: Li Yan URL: http://www.biomedcentral.com/1471-2164/13/689 source.ver: src/contrib/OSAT_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OSAT_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OSAT_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OSAT_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OSAT_1.12.0.tgz vignettes: vignettes/OSAT/inst/doc/OSAT.pdf vignetteTitles: An introduction to OSAT hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OSAT/inst/doc/OSAT.R Package: OTUbase Version: 1.14.0 Depends: R (>= 2.9.0), methods, ShortRead (>= 1.4.0), Biobase, vegan Imports: Biostrings, ShortRead, IRanges License: Artistic-2.0 MD5sum: 8a51a48aebad266bddbecfe1d9848f8a NeedsCompilation: no Title: Provides structure and functions for the analysis of OTU data Description: Provides a platform for Operational Taxonomic Unit based analysis biocViews: Sequencing, DataImport Author: Daniel Beck, Matt Settles, and James A. Foster Maintainer: Daniel Beck source.ver: src/contrib/OTUbase_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OTUbase_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OTUbase_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OTUbase_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OTUbase_1.14.0.tgz vignettes: vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.pdf vignetteTitles: An introduction to OTUbase hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OTUbase/inst/doc/Introduction_to_OTUbase.R dependsOnMe: mcaGUI Package: OutlierD Version: 1.28.0 Depends: R (>= 2.3.0), Biobase, quantreg License: GPL (>= 2) MD5sum: 03be721293e0f46a35ebecb22799b2b2 NeedsCompilation: no Title: Outlier detection using quantile regression on the M-A scatterplots of high-throughput data Description: This package detects outliers using quantile regression on the M-A scatterplots of high-throughput data. biocViews: Microarray Author: HyungJun Cho Maintainer: Sukwoo Kim URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/OutlierD_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/OutlierD_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/OutlierD_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/OutlierD_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/OutlierD_1.28.0.tgz vignettes: vignettes/OutlierD/inst/doc/OutlierD.pdf vignetteTitles: Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OutlierD/inst/doc/OutlierD.R Package: PADOG Version: 1.6.0 Depends: R (>= 2.14.0), KEGGdzPathwaysGEO, graphics, limma, AnnotationDbi, Biobase, methods, nlme, GSA,KEGG.db Imports: graphics, limma, hgu133plus2.db, hgu133a.db, KEGG.db, AnnotationDbi, Biobase, methods, nlme Suggests: parallel License: GPL (>= 2) MD5sum: 13213849ea498cf07dd7f03c8cc9d12d NeedsCompilation: no Title: Pathway Analysis with Down-weighting of Overlapping Genes (PADOG) Description: This package implements a general purpose gene set analysis method called PADOG that downplays the importance of genes that apear often accross the sets of genes to be analyzed. The package provides also a benchmark for gene set analysis methods in terms of sensitivity and ranking using 24 public datasets from KEGGdzPathwaysGEO package. biocViews: Microarray, OneChannel, TwoChannel Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca source.ver: src/contrib/PADOG_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PADOG_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PADOG_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PADOG_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PADOG_1.6.0.tgz vignettes: vignettes/PADOG/inst/doc/PADOG.pdf vignetteTitles: PADOG hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PADOG/inst/doc/PADOG.R Package: paircompviz Version: 1.2.0 Depends: R (>= 2.10), Rgraphviz Imports: Rgraphviz Suggests: multcomp, reshape, rpart, plyr, xtable License: GPL (>=3.0) MD5sum: d41a7c7bd96306e94a799c3a65c7dd50 NeedsCompilation: no Title: Multiple comparison test visualization Description: This package provides visualization of the results from the multiple (i.e. pairwise) comparison tests such as pairwise.t.test, pairwise.prop.test or pairwise.wilcox.test. The groups being compared are visualized as nodes in Hasse diagram. Such approach enables very clear and vivid depiction of which group is significantly greater than which others, especially if comparing a large number of groups. biocViews: GraphAndNetwork Author: Michal Burda Maintainer: Michal Burda source.ver: src/contrib/paircompviz_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/paircompviz_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/paircompviz_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/paircompviz_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/paircompviz_1.2.0.tgz vignettes: vignettes/paircompviz/inst/doc/vignette.pdf vignetteTitles: Using paircompviz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/paircompviz/inst/doc/vignette.R Package: PAnnBuilder Version: 1.28.0 Depends: R (>= 2.7.0), methods, utils, RSQLite, Biobase (>= 1.17.0), AnnotationDbi (>= 1.3.12) Imports: methods, utils, Biobase, DBI, RSQLite, AnnotationDbi Suggests: org.Hs.ipi.db License: LGPL (>= 2.0) MD5sum: 5c2a83260b694b8c7f5966cfdffbbcf0 NeedsCompilation: no Title: Protein annotation data package builder Description: Processing annotation data from public data repositories and building protein-centric annotation data packages. biocViews: Annotation, Proteomics Author: Li Hong lihong@sibs.ac.cn Maintainer: Li Hong URL: http://www.biosino.org/PAnnBuilder source.ver: src/contrib/PAnnBuilder_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PAnnBuilder_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PAnnBuilder_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PAnnBuilder_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PAnnBuilder_1.28.0.tgz vignettes: vignettes/PAnnBuilder/inst/doc/PAnnBuilder.pdf vignetteTitles: Using the PAnnBuilder Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAnnBuilder/inst/doc/PAnnBuilder.R Package: panp Version: 1.34.0 Depends: R (>= 2.10), affy (>= 1.23.4), Biobase (>= 2.5.5) Imports: Biobase, methods, stats, utils Suggests: gcrma License: GPL (>= 2) MD5sum: 70a3cac1fdeaf217ed81bc7f2d8fd85a NeedsCompilation: no Title: Presence-Absence Calls from Negative Strand Matching Probesets Description: A function to make gene presence/absence calls based on distance from negative strand matching probesets (NSMP) which are derived from Affymetrix annotation. PANP is applied after gene expression values are created, and therefore can be used after any preprocessing method such as MAS5 or GCRMA, or PM-only methods like RMA. NSMP sets have been established for the HGU133A and HGU133-Plus-2.0 chipsets to date. biocViews: Infrastructure Author: Peter Warren Maintainer: Peter Warren source.ver: src/contrib/panp_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/panp_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/panp_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/panp_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/panp_1.34.0.tgz vignettes: vignettes/panp/inst/doc/panp.pdf vignetteTitles: gene presence/absence calls hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/panp/inst/doc/panp.R Package: PANR Version: 1.10.0 Depends: R (>= 2.14), igraph Imports: graphics, grDevices, MASS, methods, pvclust, stats, utils Suggests: snow, RedeR License: Artistic-2.0 MD5sum: 7a72ed7515c009558aa51f8ced3e72b7 NeedsCompilation: no Title: Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations Description: This package provides S4 classes and methods for inferring functional gene networks with edges encoding posterior beliefs of gene association types and nodes encoding perturbation effects. biocViews: NetworkInference, Visualization, GraphAndNetwork, Clustering, CellBasedAssays Author: Xin Wang Maintainer: Xin Wang source.ver: src/contrib/PANR_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PANR_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PANR_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PANR_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PANR_1.10.0.tgz vignettes: vignettes/PANR/inst/doc/PANR-Vignette.pdf vignetteTitles: Main vignette:Posterior association network and enriched functional gene modules inferred from rich phenotypes of gene perturbations hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PANR/inst/doc/PANR-Vignette.R suggestsMe: RedeR Package: PAPi Version: 1.4.0 Depends: R (>= 2.15.2), svDialogs, KEGGREST License: GPL(>= 2) MD5sum: 77a2783167d32633c26a4fb105c958cf NeedsCompilation: no Title: Predict metabolic pathway activity based on metabolomics data Description: The Pathway Activity Profiling - PAPi - is an R package for predicting the activity of metabolic pathways based solely on a metabolomics data set containing a list of metabolites identified and their respective abundances in different biological samples. PAPi generates hypothesis that improves the final biological interpretation. See Aggio, R.B.M; Ruggiero, K. and Villas-Boas, S.G. (2010) - Pathway Activity Profiling (PAPi): from metabolite profile to metabolic pathway activity. Bioinformatics. biocViews: MassSpectrometry, Metabolomics Author: Raphael Aggio Maintainer: Raphael Aggio source.ver: src/contrib/PAPi_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PAPi_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PAPi_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PAPi_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PAPi_1.4.0.tgz vignettes: vignettes/PAPi/inst/doc/PAPiPackage.pdf, vignettes/PAPi/inst/doc/PAPi.pdf vignetteTitles: Applying PAPi, PAPi.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAPi/inst/doc/PAPiPackage.R Package: parody Version: 1.22.0 Depends: R (>= 2.5.0), methods, tools, utils License: Artistic-2.0 MD5sum: 3add047e6b3970d909713e84d823e1ee NeedsCompilation: no Title: Parametric And Resistant Outlier DYtection Description: routines for univariate and multivariate outlier detection with a focus on parametric methods, but support for some methods based on resistant statistics biocViews: MultipleComparison Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/parody_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/parody_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/parody_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/parody_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/parody_1.22.0.tgz vignettes: vignettes/parody/inst/doc/parody.pdf vignetteTitles: parody: parametric and resistant outlier detection hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/parody/inst/doc/parody.R dependsOnMe: arrayMvout, flowQ Package: pathifier Version: 1.2.0 Imports: R.oo, princurve License: Artistic-1.0 MD5sum: 734bd61840e337ce10667ef8099a70da NeedsCompilation: no Title: Quantify deregulation of pathways in cancer Description: Pathifier is an algorithm that infers pathway deregulation scores for each tumor sample on the basis of expression data. This score is determined, in a context-specific manner, for every particular dataset and type of cancer that is being investigated. The algorithm transforms gene-level information into pathway-level information, generating a compact and biologically relevant representation of each sample. biocViews: Network Author: Yotam Drier Maintainer: Assif Yitzhaky source.ver: src/contrib/pathifier_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pathifier_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pathifier_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pathifier_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pathifier_1.2.0.tgz vignettes: vignettes/pathifier/inst/doc/Overview.pdf vignetteTitles: Quantify deregulation of pathways in cancer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pathifier/inst/doc/Overview.R Package: PathNet Version: 1.4.0 Depends: R (>= 1.14.0) Suggests: PathNetData, RUnit, BiocGenerics License: GPL-3 MD5sum: a3efb0ef754da81637034517b7e9e029 NeedsCompilation: no Title: An R package for pathway analysis using topological information Description: PathNet uses topological information present in pathways and differential expression levels of genes (obtained from microarray experiment) to identify pathways that are 1) significantly enriched and 2) associated with each other in the context of differential expression. The algorithm is described in: PathNet: A tool for pathway analysis using topological information. Dutta B, Wallqvist A, and Reifman J. Source Code for Biology and Medicine 2012 Sep 24;7(1):10. biocViews: Pathways, DifferentialExpression, MultipleComparison Author: Bhaskar Dutta , Anders Wallqvist , and Jaques Reifman Maintainer: Jason B. Smith source.ver: src/contrib/PathNet_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PathNet_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PathNet_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PathNet_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PathNet_1.4.0.tgz vignettes: vignettes/PathNet/inst/doc/PathNet.pdf vignetteTitles: PathNet hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PathNet/inst/doc/PathNet.R Package: pathRender Version: 1.32.0 Depends: graph, Rgraphviz, RColorBrewer, cMAP, AnnotationDbi, methods Suggests: ALL, hgu95av2.db License: LGPL MD5sum: 25359ee768e2ae2946c0d4a6112cef13 NeedsCompilation: no Title: Render molecular pathways Description: build graphs from pathway databases, render them by Rgraphviz biocViews: GraphAndNetwork, Pathways, Visualization Author: Li Long Maintainer: Li Long URL: http://www.bioconductor.org source.ver: src/contrib/pathRender_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pathRender_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pathRender_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pathRender_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pathRender_1.32.0.tgz vignettes: vignettes/pathRender/inst/doc/pathRender.pdf, vignettes/pathRender/inst/doc/plotExG.pdf vignetteTitles: pathRender overview, pathway graphs colored by expression map hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pathRender/inst/doc/pathRender.R, vignettes/pathRender/inst/doc/plotExG.R Package: pathview Version: 1.4.2 Depends: R (>= 2.10), KEGGgraph, org.Hs.eg.db Imports: Rgraphviz, graph, png, AnnotationDbi, KEGGREST, methods, utils Suggests: gage, org.Mm.eg.db, RUnit, BiocGenerics License: GPL (>=3.0) MD5sum: c6a0b623597dfd981141d36286828616 NeedsCompilation: no Title: a tool set for pathway based data integration and visualization Description: Pathview is a tool set for pathway based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis. biocViews: Pathways, GraphAndNetwork, Visualization, GeneSetEnrichment, DifferentialExpression, GeneExpression, Microarray, RNASeq, Genetics, Metabolomics, Proteomics, SystemsBiology, Sequencing Author: Weijun Luo Maintainer: Weijun Luo URL: http://pathview.r-forge.r-project.org/ source.ver: src/contrib/pathview_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/pathview_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/pathview_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/pathview_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pathview_1.4.2.tgz vignettes: vignettes/pathview/inst/doc/pathview.pdf vignetteTitles: Pathview: pathway based data integration and visualization hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pathview/inst/doc/pathview.R suggestsMe: clusterProfiler, gage Package: pcaGoPromoter Version: 1.8.0 Depends: R (>= 2.14.0) , ellipse Imports: Biobase (>= 2.10.0) , AnnotationDbi Suggests: Rgraphviz, GO.db, hgu133plus2.db, mouse4302.db, rat2302.db, hugene10sttranscriptcluster.db, mogene10sttranscriptcluster.db, Biostrings, pcaGoPromoter.Hs.hg19, pcaGoPromoter.Mm.mm9, pcaGoPromoter.Rn.rn4, serumStimulation, parallel License: GPL (>= 2) MD5sum: dcbef8ba8ba2dd933a743a6e89c8718c NeedsCompilation: no Title: pcaGoPromoter is used to analyze DNA micro array data Description: This package contains functions to ease the analyses of DNA micro arrays. It utilizes principal component analysis as the initial multivariate analysis, followed by functional interpretation of the principal component dimensions with overrepresentation analysis for GO terms and regulatory interpretations using overrepresentation analysis of predicted transcription factor binding sites with the primo algorithm. biocViews: GeneExpression, Microarray, GO , Visualization Author: Morten Hansen, Jorgen Olsen Maintainer: Morten Hansen source.ver: src/contrib/pcaGoPromoter_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pcaGoPromoter_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pcaGoPromoter_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pcaGoPromoter_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pcaGoPromoter_1.8.0.tgz vignettes: vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.pdf vignetteTitles: pcaGoPromoter hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcaGoPromoter/inst/doc/pcaGoPromoter.R Package: pcaMethods Version: 1.54.0 Depends: Biobase, methods, Rcpp (>= 0.8.7) Imports: BiocGenerics, MASS LinkingTo: Rcpp Suggests: matrixStats, lattice License: GPL (>= 3) Archs: i386, x64 MD5sum: ba338a68efd8a6f0b17cf645c7c419ba NeedsCompilation: yes Title: A collection of PCA methods. Description: Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany. biocViews: Bayesian Author: Wolfram Stacklies, Henning Redestig, Kevin Wright Maintainer: Henning Redestig SystemRequirements: Rcpp source.ver: src/contrib/pcaMethods_1.54.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pcaMethods_1.54.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pcaMethods_1.54.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pcaMethods_1.54.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pcaMethods_1.54.0.tgz vignettes: vignettes/pcaMethods/inst/doc/missingValues.pdf, vignettes/pcaMethods/inst/doc/outliers.pdf, vignettes/pcaMethods/inst/doc/pcaMethods.pdf vignetteTitles: Missing value imputation, Data with outliers, Introduction hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/pcaMethods/inst/doc/missingValues.R, vignettes/pcaMethods/inst/doc/outliers.R, vignettes/pcaMethods/inst/doc/pcaMethods.R dependsOnMe: DeconRNASeq importsMe: MSnbase, SomaticSignatures Package: pcot2 Version: 1.32.0 Depends: R (>= 2.0.0), grDevices, Biobase, amap Suggests: multtest, hu6800.db, KEGG.db, mvtnorm License: GPL (>= 2) MD5sum: 626663ca7904937b54c7bdd3a7c835ba NeedsCompilation: no Title: Principal Coordinates and Hotelling's T-Square method Description: PCOT2 is a permutation-based method for investigating changes in the activity of multi-gene networks. It utilizes inter-gene correlation information to detect significant alterations in gene network activities. Currently it can be applied to two-sample comparisons. biocViews: Microarray, DifferentialExpression Author: Sarah Song, Mik Black Maintainer: Sarah Song source.ver: src/contrib/pcot2_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pcot2_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pcot2_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pcot2_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pcot2_1.32.0.tgz vignettes: vignettes/pcot2/inst/doc/pcot2.pdf vignetteTitles: PCOT2 Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcot2/inst/doc/pcot2.R Package: PCpheno Version: 1.26.0 Depends: R (>= 2.10), Category, ScISI (>= 1.3.0), SLGI, ppiStats, ppiData, annotate (>= 1.17.4) Imports: AnnotationDbi, Biobase, Category, GO.db, graph, graphics, GSEABase, KEGG.db, methods, ScISI, stats, stats4 Suggests: KEGG.db, GO.db, org.Sc.sgd.db License: Artistic-2.0 MD5sum: b79e6ca15d0393ce85e96cdbc1301cb9 NeedsCompilation: no Title: Phenotypes and cellular organizational units Description: Tools to integrate, annotate, and link phenotypes to cellular organizational units such as protein complexes and pathways. biocViews: GraphAndNetwork, Proteomics, Network Author: Nolwenn Le Meur and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/PCpheno_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PCpheno_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PCpheno_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PCpheno_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PCpheno_1.26.0.tgz vignettes: vignettes/PCpheno/inst/doc/PCpheno.pdf vignetteTitles: PCpheno Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PCpheno/inst/doc/PCpheno.R Package: pdInfoBuilder Version: 1.28.0 Depends: R (>= 2.15.0), methods, Biobase (>= 2.17.7), RSQLite (>= 0.11.1), affxparser (>= 1.29.12), oligo (>= 1.27.3) Imports: Biostrings (>= 2.25.12), IRanges (>= 1.15.44) License: Artistic-2.0 Archs: i386, x64 MD5sum: 14ad17916ac808214629638c4301e3fa NeedsCompilation: yes Title: Platform Design Information Package Builder Description: Builds platform design information packages. These consist of a SQLite database containing feature-level data such as x, y position on chip and featureSet ID. The database also incorporates featureSet-level annotation data. The products of this packages are used by the oligo pkg. biocViews: Annotation, Infrastructure Author: Seth Falcon, Benilton Carvalho with contributions by Vince Carey, Matt Settles and Kristof de Beuf Maintainer: Benilton Carvalho source.ver: src/contrib/pdInfoBuilder_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pdInfoBuilder_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pdInfoBuilder_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pdInfoBuilder_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pdInfoBuilder_1.28.0.tgz vignettes: vignettes/pdInfoBuilder/inst/doc/BuildingPDInfoPkgs.pdf, vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.pdf vignetteTitles: Building Annotation Packages with pdInfoBuilder for Use with the oligo Package, PDInfo Package Building Affymetrix Mapping Chips hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pdInfoBuilder/inst/doc/BuildingPDInfoPkgs.R, vignettes/pdInfoBuilder/inst/doc/howto-AffymetrixMapping.R Package: pdmclass Version: 1.36.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), fibroEset, mda License: Artistic-2.0 MD5sum: 5d74479bc65653dc762b2a8a8e8907cf NeedsCompilation: no Title: Classification of Microarray Samples using Penalized Discriminant Methods Description: This package can be used to classify microarray data using one of three penalized regression methods; partial least squares, principal components regression, or ridge regression. biocViews: Classification Author: James W. MacDonald, Debashis Ghosh, based in part on pls code of Mike Denham Maintainer: James W. MacDonald source.ver: src/contrib/pdmclass_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pdmclass_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pdmclass_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pdmclass_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pdmclass_1.36.0.tgz vignettes: vignettes/pdmclass/inst/doc/pdmclass.pdf vignetteTitles: pdmclass Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pdmclass/inst/doc/pdmclass.R suggestsMe: oneChannelGUI Package: PECA Version: 1.0.0 Imports: limma, affy, genefilter, preprocessCore Suggests: SpikeIn, ROCR, multtest License: GPL (>= 2) MD5sum: 5abab331654df29061d298b9ff71d9cc NeedsCompilation: no Title: Probe-level Expression Change Averaging Description: Calculates Probe-level Expression Change Averages (PECA) to identify differential expression in Affymetrix gene expression microarray studies or in proteomic studies using peptide-level mesurements respectively. biocViews: Software, Preprocessing, Microarray, DifferentialExpression, GeneExpression Author: Tomi Suomi, Jukka Hiissa, Laura L. Elo Maintainer: Tomi Suomi source.ver: src/contrib/PECA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PECA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PECA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PECA_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PECA_1.0.0.tgz vignettes: vignettes/PECA/inst/doc/PECA.pdf vignetteTitles: PECA: Probe-level Expression Change Averaging hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PECA/inst/doc/PECA.R Package: PGSEA Version: 1.38.0 Depends: R (>= 2.10), GO.db, KEGG.db, AnnotationDbi, annaffy, methods, Biobase (>= 2.5.5) Suggests: GSEABase, GEOquery, org.Hs.eg.db, hgu95av2.db, limma License: GPL-2 MD5sum: ae76c1cdfeb3e419fd624720296f916d NeedsCompilation: no Title: Parametric Gene Set Enrichment Analysis Description: Parametric Analysis of Gene Set Enrichment biocViews: Microarray Author: Kyle Furge and Karl Dykema Maintainer: Karl Dykema source.ver: src/contrib/PGSEA_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PGSEA_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PGSEA_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PGSEA_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PGSEA_1.38.0.tgz vignettes: vignettes/PGSEA/inst/doc/PGSEA2.pdf, vignettes/PGSEA/inst/doc/PGSEA.pdf vignetteTitles: HOWTO: PGSEA Example Workflow, HOWTO: PGSEA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PGSEA/inst/doc/PGSEA2.R, vignettes/PGSEA/inst/doc/PGSEA.R dependsOnMe: GeneExpressionSignature Package: phenoDist Version: 1.12.0 Depends: R (>= 2.9.0), imageHTS, e1071 Suggests: GOstats, MASS License: LGPL-2.1 MD5sum: bc367b7913ad96b06ebd28355d9209dc NeedsCompilation: no Title: Phenotypic distance measures Description: PhenoDist is designed for measuring phenotypic distance in image-based high-throughput screening, in order to identify strong phenotypes and to group treatments into functional clusters. biocViews: CellBasedAssays Author: Xian Zhang, Gregoire Pau, Wolfgang Huber, Michael Boutros Maintainer: Xian Zhang URL: http://www.dkfz.de/signaling, http://www.embl.de/research/units/genome_biology/huber/ source.ver: src/contrib/phenoDist_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/phenoDist_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/phenoDist_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/phenoDist_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/phenoDist_1.12.0.tgz vignettes: vignettes/phenoDist/inst/doc/phenoDist.pdf vignetteTitles: Introduction to phenoDist hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phenoDist/inst/doc/phenoDist.R Package: phenoTest Version: 1.12.0 Depends: R (>= 2.12.0), Biobase, methods, annotate, Heatplus, BMA, ggplot2, gridExtra Imports: survival, limma, Hmisc, gplots, Category, AnnotationDbi, hopach, biomaRt, GSEABase, genefilter, xtable, annotate, mgcv, SNPchip, hgu133a.db, HTSanalyzeR, ellipse Suggests: GSEABase, KEGG.db, GO.db Enhances: parallel, org.Ce.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Hs.eg.db, org.Dm.eg.db License: GPL (>=2) MD5sum: 21312a475007fc8b571eea828d4ccaf7 NeedsCompilation: no Title: Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation. Description: Tools to test correlation between gene expression and phenotype in a way that is efficient, structured, fast and scalable. GSEA is also provided. biocViews: Microarray, DifferentialExpression, MultipleComparison, Clustering, Classification Author: Evarist Planet Maintainer: Evarist Planet source.ver: src/contrib/phenoTest_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/phenoTest_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/phenoTest_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/phenoTest_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/phenoTest_1.12.0.tgz vignettes: vignettes/phenoTest/inst/doc/phenoTest.pdf vignetteTitles: Manual for the phenoTest library hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phenoTest/inst/doc/phenoTest.R Package: PhenStat Version: 1.2.0 Depends: R (>= 2.3.0) Imports: methods, car, nlme, nortest, vcd, limma Suggests: RUnit, BiocGenerics License: file LICENSE MD5sum: 64b0018fd4e37038a1c33b094f598f79 NeedsCompilation: no Title: Statistical analysis of phenotypic data Description: Package contains methods for statistical analysis of phenotypic data such as Mixed Models and Fisher Exact Test. Author: Natalja Kurbatova, Natasha Karp, Jeremy Mason Maintainer: Natasha Karp source.ver: src/contrib/PhenStat_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PhenStat_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PhenStat_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PhenStat_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PhenStat_1.2.0.tgz vignettes: vignettes/PhenStat/inst/doc/PhenStat.pdf, vignettes/PhenStat/inst/doc/PhenStatUsersGuide.pdf vignetteTitles: PhenStat Vignette, PhenStatUsersGuide.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/PhenStat/inst/doc/PhenStat.R Package: phyloseq Version: 1.8.2 Depends: R (>= 3.0.0) Imports: ade4 (>= 1.6.2), ape (>= 3.1.1), biom (>= 0.3.9), Biostrings (>= 2.28.0), cluster (>= 1.14.4), data.table (>= 1.9.2), DESeq2 (>= 1.4.0), foreach (>= 1.4.2), ggplot2 (>= 1.0.0), igraph (>= 0.6.5.2), methods (>= 3.0.0), multtest (>= 2.16.0), plyr (>= 1.8), reshape2 (>= 1.2.2), scales (>= 0.2.3), vegan (>= 2.0.10) Suggests: genefilter (>= 1.42.0), testthat (>= 0.7.1), knitr (>= 1.3) Enhances: doParallel (>= 1.0.1) License: AGPL-3 MD5sum: fc4df3319bf008f626cea43f2af537f2 NeedsCompilation: no Title: Handling and analysis of high-throughput microbiome census data. Description: phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data. biocViews: Clustering, Classification, MultipleComparisons, QualityControl, GeneticVariability, HighThroughputSequencing Author: Paul J. McMurdie , Susan Holmes , with contributions from Gregory Jordan and Scott Chamberlain Maintainer: Paul J. McMurdie URL: http://dx.plos.org/10.1371/journal.pone.0061217 VignetteBuilder: knitr source.ver: src/contrib/phyloseq_1.8.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/phyloseq_1.8.2.zip win64.binary.ver: bin/windows64/contrib/3.1/phyloseq_1.8.2.zip mac.binary.ver: bin/macosx/contrib/3.1/phyloseq_1.8.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/phyloseq_1.8.2.tgz vignettes: vignettes/phyloseq/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/phyloseq/inst/doc/phyloseq_analysis.R, vignettes/phyloseq/inst/doc/phyloseq-analysis.R, vignettes/phyloseq/inst/doc/phyloseq_basics.R, vignettes/phyloseq/inst/doc/phyloseq-basics.R, vignettes/phyloseq/inst/doc/phyloseq-mixture-models.R htmlDocs: vignettes/phyloseq/inst/doc/phyloseq-analysis.html, vignettes/phyloseq/inst/doc/phyloseq-basics.html, vignettes/phyloseq/inst/doc/phyloseq-mixture-models.html htmlTitles: "phyloseq analysis vignette", "phyloseq basics vignette", "phyloseq and DESeq2 on Colorectal Cancer Data" Package: piano Version: 1.4.2 Depends: R (>= 2.14.0) Imports: Biobase, gplots, igraph, relations, marray Suggests: yeast2.db, rsbml, plotrix, limma, affy, plier, affyPLM, gtools, biomaRt, snowfall License: GPL (>=2) MD5sum: 98590cb8e3c549b825b3a5093b6bc8a5 NeedsCompilation: no Title: Platform for integrative analysis of omics data Description: Piano performs gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. Furthermore, the Piano package contains functions for combining the results of multiple runs of gene set analyses. biocViews: Microarray, Preprocessing, QualityControl, DifferentialExpression, Visualization, GeneExpression, GeneSetEnrichment, Pathways Author: Leif Varemo and Intawat Nookaew Maintainer: Leif Varemo URL: http://www.sysbio.se/piano source.ver: src/contrib/piano_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/piano_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/piano_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/piano_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/piano_1.4.2.tgz vignettes: vignettes/piano/inst/doc/piano-vignette.pdf vignetteTitles: Piano - Platform for Integrative Analysis of Omics data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/piano/inst/doc/piano-vignette.R Package: pickgene Version: 1.36.0 Imports: graphics, grDevices, MASS, stats, utils License: GPL (>= 2) MD5sum: c36bb21cdb0b5539acbb126e0bc93632 NeedsCompilation: no Title: Adaptive Gene Picking for Microarray Expression Data Analysis Description: Functions to Analyze Microarray (Gene Expression) Data. biocViews: Microarray, DifferentialExpression Author: Brian S. Yandell Maintainer: Brian S. Yandell URL: http://www.stat.wisc.edu/~yandell/statgen source.ver: src/contrib/pickgene_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pickgene_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pickgene_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pickgene_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pickgene_1.36.0.tgz vignettes: vignettes/pickgene/inst/doc/pickgene.pdf vignetteTitles: Adaptive Gene Picking for Microarray Expression Data Analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pickgene/inst/doc/pickgene.R Package: PICS Version: 2.8.0 Depends: R (>= 2.14.0), BiocGenerics (>= 0.1.3) Imports: methods, stats4, IRanges, GenomicRanges, graphics, grDevices, stats, Rsamtools, GenomicAlignments Suggests: ShortRead, rtracklayer, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 2d6043422098fa67a64821284f7f2c87 NeedsCompilation: yes Title: Probabilistic inference of ChIP-seq Description: Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach. biocViews: Clustering, Visualization, Sequencing, ChIPSeq Author: Xuekui Zhang , Raphael Gottardo Maintainer: Renan Sauteraud source.ver: src/contrib/PICS_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PICS_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PICS_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PICS_2.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PICS_2.8.0.tgz vignettes: vignettes/PICS/inst/doc/PICS.pdf vignetteTitles: The PICS users guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PICS/inst/doc/PICS.R importsMe: PING Package: PING Version: 2.8.0 Depends: R(>= 2.15.0), chipseq, IRanges, GenomicRanges Imports: methods, PICS, graphics, grDevices, stats, Gviz, fda, BSgenome, stats4, BiocGenerics Suggests: parallel, ShortRead, rtracklayer License: Artistic-2.0 Archs: i386, x64 MD5sum: e7ff11f513b292202db7422d5b595d80 NeedsCompilation: yes Title: Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data Description: Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach. biocViews: Clustering, StatisticalMethod, Visualization, Sequencing Author: Xuekui Zhang , Raphael Gottardo , Sangsoon Woo, Maintainer: Renan Sauteraud source.ver: src/contrib/PING_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PING_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PING_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PING_2.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PING_2.8.0.tgz vignettes: vignettes/PING/inst/doc/PING.pdf, vignettes/PING/inst/doc/PING-PE.pdf vignetteTitles: The PING users guide, Using PING with paired-end sequencing data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PING/inst/doc/PING-PE.R, vignettes/PING/inst/doc/PING.R Package: pint Version: 1.16.0 Depends: mvtnorm, methods, graphics, Matrix, dmt License: BSD_2_clause + file LICENSE MD5sum: 250b9c41435ec5bd4c21c6e3afe12bbb NeedsCompilation: no Title: Pairwise INTegration of functional genomics data Description: Pairwise data integration for functional genomics, including tools for DNA/RNA/miRNA dependency screens. biocViews: aCGH, GeneExpression, Genetics, DifferentialExpression, Microarray Author: Olli-Pekka Huovilainen and Leo Lahti Maintainer: Olli-Pekka Huovilainen source.ver: src/contrib/pint_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pint_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pint_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pint_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pint_1.16.0.tgz vignettes: vignettes/pint/inst/doc/depsearch.pdf vignetteTitles: pint hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/pint/inst/doc/depsearch.R Package: pkgDepTools Version: 1.30.0 Depends: methods, graph, RBGL Imports: graph, RBGL Suggests: Biobase, Rgraphviz, RCurl, BiocInstaller License: GPL-2 MD5sum: 21a0c9612651e1c6bbe95c0459046d1b NeedsCompilation: no Title: Package Dependency Tools Description: This package provides tools for computing and analyzing dependency relationships among R packages. It provides tools for building a graph-based representation of the dependencies among all packages in a list of CRAN-style package repositories. There are also utilities for computing installation order of a given package. If the RCurl package is available, an estimate of the download size required to install a given package and its dependencies can be obtained. biocViews: Infrastructure, GraphAndNetwork Author: Seth Falcon Maintainer: Seth Falcon source.ver: src/contrib/pkgDepTools_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pkgDepTools_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pkgDepTools_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pkgDepTools_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pkgDepTools_1.30.0.tgz vignettes: vignettes/pkgDepTools/inst/doc/pkgDepTools.pdf vignetteTitles: How to Use pkgDepTools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pkgDepTools/inst/doc/pkgDepTools.R Package: plateCore Version: 1.22.1 Depends: R (>= 2.10), flowCore, flowViz, lattice, latticeExtra Imports: Biobase, flowCore, graphics, grDevices, lattice, MASS, methods, robustbase, stats, utils, flowStats Suggests: gplots License: Artistic-2.0 MD5sum: e53852ea41db9ea50cd85ec194bfc94c NeedsCompilation: no Title: Statistical tools and data structures for plate-based flow cytometry Description: Provides basic S4 data structures and routines for analyzing plate based flow cytometry data. biocViews: FlowCytometry, Infrastructure, CellBasedAssays Author: Errol Strain, Florian Hahne, and Perry Haaland Maintainer: Errol Strain URL: http://www.bioconductor.org source.ver: src/contrib/plateCore_1.22.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/plateCore_1.22.1.zip win64.binary.ver: bin/windows64/contrib/3.1/plateCore_1.22.1.zip mac.binary.ver: bin/macosx/contrib/3.1/plateCore_1.22.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plateCore_1.22.1.tgz vignettes: vignettes/plateCore/inst/doc/plateCoreVig.pdf vignetteTitles: An R Package for Analysis of High Throughput Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plateCore/inst/doc/plateCoreVig.R Package: plethy Version: 1.2.2 Depends: R (>= 3.1.0), methods Imports: Streamer, DBI, RSQLite, IRanges, reshape2, plyr, batch, RColorBrewer Suggests: RUnit, BiocGenerics, BiocStyle License: GPL-3 MD5sum: 167a1756b805fab2bcc22c6fd7616696 NeedsCompilation: no Title: R framework for exploration and analysis of respirometry data Description: This package provides the infrastructure and tools to import, query and perform basic analysis of whole body plethysmography and metabolism data. Currently support is limited to data derived from Buxco respirometry instruments as exported by their FinePointe software. biocViews: DataImport, biocViews, Infastructure, DataRepresentation,TimeCourse Author: Daniel Bottomly, Marty Ferris Maintainer: Daniel Bottomly source.ver: src/contrib/plethy_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/plethy_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.1/plethy_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.1/plethy_1.2.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plethy_1.2.2.tgz vignettes: vignettes/plethy/inst/doc/plethy.pdf vignetteTitles: plethy hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plethy/inst/doc/plethy.R Package: plgem Version: 1.36.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), MASS Imports: utils License: GPL-2 MD5sum: ff3b3ff93a227b941b274381901b7667 NeedsCompilation: no Title: Detect differential expression in microarray and proteomics datasets with the Power Law Global Error Model (PLGEM) Description: The Power Law Global Error Model (PLGEM) has been shown to faithfully model the variance-versus-mean dependence that exists in a variety of genome-wide datasets, including microarray and proteomics data. The use of PLGEM has been shown to improve the detection of differentially expressed genes or proteins in these datasets. biocViews: Microarray, DifferentialExpression, Proteomics Author: Mattia Pelizzola and Norman Pavelka Maintainer: Norman Pavelka URL: http://www.genopolis.it source.ver: src/contrib/plgem_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/plgem_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/plgem_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/plgem_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plgem_1.36.0.tgz vignettes: vignettes/plgem/inst/doc/plgem.pdf vignetteTitles: An introduction to PLGEM hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plgem/inst/doc/plgem.R Package: plier Version: 1.34.0 Depends: R (>= 2.0), methods Imports: affy, Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 209d7b32bc95ae09970c4e234df2c94a NeedsCompilation: yes Title: Implements the Affymetrix PLIER algorithm Description: The PLIER (Probe Logarithmic Error Intensity Estimate) method produces an improved signal by accounting for experimentally observed patterns in probe behavior and handling error at the appropriately at low and high signal values. biocViews: Software Author: Affymetrix Inc., Crispin J Miller, PICR Maintainer: Crispin Miller source.ver: src/contrib/plier_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/plier_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/plier_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/plier_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plier_1.34.0.tgz hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE suggestsMe: piano, virtualArray Package: PLPE Version: 1.24.0 Depends: R (>= 2.6.2), Biobase (>= 2.5.5), LPE, MASS, methods License: GPL (>= 2) MD5sum: 03f85a5cb38138ee02c8c57b92b43e4d NeedsCompilation: no Title: Local Pooled Error Test for Differential Expression with Paired High-throughput Data Description: This package performs tests for paired high-throughput data. biocViews: Proteomics, Microarray, DifferentialExpression Author: HyungJun Cho and Jae K. Lee Maintainer: Soo-heang Eo URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/PLPE_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PLPE_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PLPE_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PLPE_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PLPE_1.24.0.tgz vignettes: vignettes/PLPE/inst/doc/PLPE.pdf vignetteTitles: PLPE Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PLPE/inst/doc/PLPE.R Package: plrs Version: 1.4.0 Depends: R (>= 2.10), Biobase Imports: BiocGenerics, CGHbase, graphics, grDevices, ic.infer, marray, methods, quadprog, Rcsdp, stats, stats4, utils Suggests: mvtnorm, methods License: GPL (>=2.0) MD5sum: d901ee3f8121188cc4963cfd7e5b5a45 NeedsCompilation: no Title: Piecewise Linear Regression Splines (PLRS) for the association between DNA copy number and gene expression Description: The present package implements a flexible framework for modeling the relationship between DNA copy number and gene expression data using Piecewise Linear Regression Splines (PLRS). biocViews: Regression Author: Gwenael G.R. Leday Maintainer: Gwenael G.R. Leday to source.ver: src/contrib/plrs_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/plrs_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/plrs_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/plrs_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plrs_1.4.0.tgz vignettes: vignettes/plrs/inst/doc/plrs_vignette.pdf vignetteTitles: plrs hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plrs/inst/doc/plrs_vignette.R Package: plw Version: 1.24.0 Depends: R (>= 2.10), affy (>= 1.23.4) Imports: MASS, affy, graphics, splines, stats Suggests: limma License: GPL-2 Archs: i386, x64 MD5sum: abc3ea97703ddb63e4364695c12e6a69 NeedsCompilation: yes Title: Probe level Locally moderated Weighted t-tests. Description: Probe level Locally moderated Weighted median-t (PLW) and Locally Moderated Weighted-t (LMW). biocViews: Microarray, OneChannel, TwoChannel, DifferentialExpression Author: Magnus Astrand Maintainer: Magnus Astrand source.ver: src/contrib/plw_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/plw_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/plw_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/plw_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/plw_1.24.0.tgz vignettes: vignettes/plw/inst/doc/HowToPLW.pdf vignetteTitles: HowTo plw hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/plw/inst/doc/HowToPLW.R Package: ppiStats Version: 1.30.0 Depends: ScISI (>= 1.13.2), lattice, ppiData (>= 0.1.19) Imports: Biobase, Category, graph, graphics, grDevices, lattice, methods, RColorBrewer, stats Suggests: yeastExpData, xtable License: Artistic-2.0 MD5sum: 85fcb75a6491708bde991e4fadbad62d NeedsCompilation: no Title: Protein-Protein Interaction Statistical Package Description: Tools for the analysis of protein interaction data. biocViews: Proteomics, GraphAndNetwork, Network Author: T. Chiang and D. Scholtens with contributions from W. Huber and L. Wang Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ppiStats_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ppiStats_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ppiStats_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ppiStats_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ppiStats_1.30.0.tgz vignettes: vignettes/ppiStats/inst/doc/ppiStats.pdf vignetteTitles: ppiStats hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ppiStats/inst/doc/ppiStats.R dependsOnMe: PCpheno suggestsMe: BiocCaseStudies, RpsiXML Package: prada Version: 1.40.0 Depends: R (>= 2.10), Biobase, RColorBrewer, grid, methods, rrcov Imports: Biobase, BiocGenerics, graphics, grDevices, grid, MASS, methods, RColorBrewer, rrcov, stats4, utils Suggests: cellHTS, tcltk License: LGPL Archs: i386, x64 MD5sum: 87b43b5558cf3ff2217f175c75875e01 NeedsCompilation: yes Title: Data analysis for cell-based functional assays Description: Tools for analysing and navigating data from high-throughput phenotyping experiments based on cellular assays and fluorescent detection (flow cytometry (FACS), high-content screening microscopy). biocViews: CellBasedAssays, Visualization Author: Florian Hahne , Wolfgang Huber , Markus Ruschhaupt, Joern Toedling , Joseph Barry Maintainer: Florian Hahne source.ver: src/contrib/prada_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/prada_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/prada_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/prada_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/prada_1.40.0.tgz vignettes: vignettes/prada/inst/doc/norm2.pdf, vignettes/prada/inst/doc/prada2cellHTS.pdf vignetteTitles: Removal of contaminants from FACS data, Combining prada output and cellHTS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/prada/inst/doc/norm2.R, vignettes/prada/inst/doc/prada2cellHTS.R dependsOnMe: cellHTS, domainsignatures, RNAither importsMe: cellHTS2 Package: prebs Version: 1.4.0 Depends: R (>= 2.14.0), GenomicAlignments, affy Imports: parallel, methods, stats, GenomicRanges (>= 1.13.3), IRanges Suggests: prebsdata, hgu133plus2cdf, hgu133plus2probe License: Artistic-2.0 MD5sum: 6ff8432b9e11854ccd93d870ed927e95 NeedsCompilation: no Title: Probe region expression estimation for RNA-seq data for improved microarray comparability Description: The prebs package aims at making RNA-sequencing (RNA-seq) data more comparable to microarray data. The comparability is achieved by summarizing sequencing-based expressions of probe regions using a modified version of RMA algorithm. The pipeline takes mapped reads in BAM format as an input and produces either gene expressions or original microarray probe set expressions as an output. biocViews: Microarray, RNASeq, Sequencing, GeneExpression, Preprocessing Author: Karolis Uziela and Antti Honkela Maintainer: Karolis Uziela source.ver: src/contrib/prebs_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/prebs_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/prebs_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/prebs_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/prebs_1.4.0.tgz vignettes: vignettes/prebs/inst/doc/prebs.pdf vignetteTitles: prebs User Guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/prebs/inst/doc/prebs.R Package: PREDA Version: 1.10.0 Depends: R (>= 2.9.0), Biobase, lokern (>= 1.0.9), multtest, stats, methods, annotate Suggests: quantsmooth, qvalue, samr, limma, caTools, affy, PREDAsampledata Enhances: Rmpi, rsprng License: GPL-2 MD5sum: 064808d9e45fce1acfd86512039e2f3e NeedsCompilation: no Title: Position RElated Data Anlysis Description: Package for the position related analysis of quantitative functional genomics data. biocViews: Software, CopyNumberVariation, GeneExpression, Genetics Author: Francesco Ferrari Maintainer: Francesco Ferrari source.ver: src/contrib/PREDA_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PREDA_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PREDA_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PREDA_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PREDA_1.10.0.tgz vignettes: vignettes/PREDA/inst/doc/PREDAclasses.pdf, vignettes/PREDA/inst/doc/PREDAtutorial.pdf vignetteTitles: PREDA S4-classes, PREDA tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PREDA/inst/doc/PREDAclasses.R, vignettes/PREDA/inst/doc/PREDAtutorial.R Package: predictionet Version: 1.10.0 Depends: igraph, catnet Imports: penalized, RBGL, MASS Suggests: network, minet, knitr License: Artistic-2.0 MD5sum: 7a2a3254d02e3177ce85b45c00581fa2 NeedsCompilation: yes Title: Inference for predictive networks designed for (but not limited to) genomic data Description: This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases. The main function is able to generate networks using Bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer networks with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen. biocViews: GraphAndNetwork, NetworkInference Author: Benjamin Haibe-Kains, Catharina Olsen, Gianluca Bontempi, John Quackenbush Maintainer: Benjamin Haibe-Kains , Catharina Olsen URL: http://compbio.dfci.harvard.edu, http://www.ulb.ac.be/di/mlg source.ver: src/contrib/predictionet_1.10.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/predictionet_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/predictionet_1.10.0.tgz vignettes: vignettes/predictionet/inst/doc/predictionet.pdf vignetteTitles: predictionet hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/predictionet/inst/doc/predictionet.R Package: preprocessCore Version: 1.26.1 Depends: methods Imports: stats License: LGPL (>= 2) Archs: i386, x64 MD5sum: bfac63ebbee13b22849ea37fd56657a6 NeedsCompilation: yes Title: A collection of pre-processing functions Description: A library of core preprocessing routines biocViews: Infrastructure Author: Benjamin Milo Bolstad Maintainer: Benjamin Milo Bolstad source.ver: src/contrib/preprocessCore_1.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/preprocessCore_1.26.1.zip win64.binary.ver: bin/windows64/contrib/3.1/preprocessCore_1.26.1.zip mac.binary.ver: bin/macosx/contrib/3.1/preprocessCore_1.26.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/preprocessCore_1.26.1.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affyPLM, CopyNumber450k, cqn, crlmm, RefPlus, virtualArray importsMe: affy, AffyTiling, ChAMP, charm, cn.farms, ExiMiR, frma, frmaTools, lumi, MBCB, minfi, MSnbase, MSstats, oligo, PECA, waveTiling suggestsMe: oneChannelGUI Package: PROcess Version: 1.40.0 Depends: Icens Imports: graphics, grDevices, Icens, stats, utils License: Artistic-2.0 MD5sum: 8a84dad6a306e808ec6c2a6e246928a5 NeedsCompilation: no Title: Ciphergen SELDI-TOF Processing Description: A package for processing protein mass spectrometry data. biocViews: MassSpectrometry, Proteomics Author: Xiaochun Li Maintainer: Xiaochun Li source.ver: src/contrib/PROcess_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PROcess_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PROcess_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PROcess_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PROcess_1.40.0.tgz vignettes: vignettes/PROcess/inst/doc/howtoprocess.pdf vignetteTitles: HOWTO PROcess hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PROcess/inst/doc/howtoprocess.R Package: procoil Version: 1.14.0 Depends: R (>= 2.12.0) Imports: methods, stats, graphics Suggests: Biostrings License: GPL (>= 2) MD5sum: aff9adf11c3fdb601fb46029109c262f NeedsCompilation: no Title: Prediction of Oligomerization of Coiled Coil Proteins Description: The procoil package allows to predict whether a coiled coil sequence (amino acid sequence plus heptad register) is more likely to form a dimer or more likely to form a trimer. The predict function not only computes the prediction itself, but also a profile which allows to determine the strengths to which the individual residues are indicative for either class. Profiles can also be plotted and exported to files. biocViews: Proteomics, Classification Author: Ulrich Bodenhofer Maintainer: Ulrich Bodenhofer URL: http://www.bioinf.jku.at/software/procoil/ https://github.com/UBod/procoil source.ver: src/contrib/procoil_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/procoil_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/procoil_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/procoil_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/procoil_1.14.0.tgz vignettes: vignettes/procoil/inst/doc/procoil.pdf vignetteTitles: PrOCoil - A Web Service and an R Package for Predicting the Oligomerization of Coiled-Coil Proteins hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/procoil/inst/doc/procoil.R Package: ProCoNA Version: 1.2.0 Depends: R (>= 2.10), methods, WGCNA, MSnbase Imports: BiocGenerics, GOstats Suggests: RUnit License: GPL (>= 2) MD5sum: de009234b762aa33bf894ba2f61179b3 NeedsCompilation: no Title: Protein co-expression network analysis (ProCoNA). Description: Protein co-expression network construction using peptide level data, with statisical analysis. (Journal of Clinical Bioinformatics 2013, 3:11 doi:10.1186/2043-9113-3-11) biocViews: GraphAndNetwork, Software, Proteomics Author: David L Gibbs Maintainer: David L Gibbs source.ver: src/contrib/ProCoNA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ProCoNA_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ProCoNA_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ProCoNA_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ProCoNA_1.2.0.tgz vignettes: vignettes/ProCoNA/inst/doc/ProCoNA_Vignette.pdf vignetteTitles: De Novo Peptide Network Example hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ProCoNA/inst/doc/ProCoNA_Vignette.R Package: pRoloc Version: 1.4.0 Depends: R (>= 2.15), MSnbase (>= 1.7.23), MLInterfaces (>= 1.37.1), methods, Rcpp (>= 0.10.3), BiocParallel Imports: mclust (>= 4.3), MSBVAR, caret, e1071, sampling, class, kernlab, lattice, nnet, randomForest, proxy, FNN, BiocGenerics, stats4, RColorBrewer, scales, MASS, knitr LinkingTo: Rcpp, RcppArmadillo Suggests: testthat, pRolocdata, roxygen2, synapter, xtable License: GPL-2 Archs: i386, x64 MD5sum: ae22843e21edb36bd4c4d1c211f96fb0 NeedsCompilation: yes Title: A unifying bioinformatics framework for spatial proteomics Description: This package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation. biocViews: Proteomics, MassSpectrometry, Classification, Clustering Author: Laurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek Maintainer: Laurent Gatto VignetteBuilder: knitr source.ver: src/contrib/pRoloc_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pRoloc_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pRoloc_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pRoloc_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pRoloc_1.4.0.tgz vignettes: vignettes/pRoloc/inst/doc/HUPO_2011_poster.pdf, vignettes/pRoloc/inst/doc/pRoloc-ml.pdf, vignettes/pRoloc/inst/doc/pRoloc-tutorial.pdf vignetteTitles: pRoloc -- A unifying bioinformatics framework for organelle proteomics, Machine learning techniques available in pRoloc, pRoloc tutorial hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pRoloc/inst/doc/HUPO_2011_poster.R, vignettes/pRoloc/inst/doc/pRoloc-ml.R, vignettes/pRoloc/inst/doc/pRoloc-tutorial.R Package: PROMISE Version: 1.16.0 Depends: R (>= 2.11.0), Biobase, GSEABase Imports: Biobase, GSEABase, stats License: GPL (>= 2) MD5sum: 6e1774b297793dc9a6a7f47f8a5635c1 NeedsCompilation: no Title: PRojection Onto the Most Interesting Statistical Evidence Description: A general tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables as described in Pounds et. al. (2009) Bioinformatics 25: 2013-2019 biocViews: Microarray, OneChannel, MultipleComparison, GeneExpression Author: Stan Pounds , Xueyuan Cao Maintainer: Stan Pounds , Xueyuan Cao source.ver: src/contrib/PROMISE_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/PROMISE_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/PROMISE_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/PROMISE_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PROMISE_1.16.0.tgz vignettes: vignettes/PROMISE/inst/doc/PROMISE.pdf vignetteTitles: An introduction to PROMISE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PROMISE/inst/doc/PROMISE.R Package: prot2D Version: 1.2.0 Depends: R (>= 2.15),fdrtool,st,samr,Biobase,limma,Mulcom,impute,MASS,qvalue Suggests: made4,affy License: GPL (>= 2) MD5sum: dff0e37ebfd565ce468754d90226fb45 NeedsCompilation: no Title: Statistical Tools for volume data from 2D Gel Electrophoresis Description: The purpose of this package is to analyze (i.e. Normalize and select significant spots) data issued from 2D GEl experiments biocViews: DifferentialExpression, MultipleComparison, Proteomics Author: Sebastien Artigaud Maintainer: Sebastien Artigaud source.ver: src/contrib/prot2D_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/prot2D_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/prot2D_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/prot2D_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/prot2D_1.2.0.tgz vignettes: vignettes/prot2D/inst/doc/prot2D.pdf vignetteTitles: prot2D hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/prot2D/inst/doc/prot2D.R Package: proteinProfiles Version: 1.4.0 Depends: R (>= 2.15.2) Imports: graphics, stats Suggests: testthat License: GPL-3 MD5sum: 52a9026b570904b44ed467df7b439508 NeedsCompilation: no Title: Protein Profiling Description: Significance assessment for distance measures of time-course protein profiles Author: Julian Gehring Maintainer: Julian Gehring source.ver: src/contrib/proteinProfiles_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/proteinProfiles_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/proteinProfiles_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/proteinProfiles_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/proteinProfiles_1.4.0.tgz vignettes: vignettes/proteinProfiles/inst/doc/proteinProfiles.pdf vignetteTitles: The proteinProfiles package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/proteinProfiles/inst/doc/proteinProfiles.R Package: PSICQUIC Version: 1.2.1 Depends: R (>= 2.15.0), methods, IRanges, biomaRt, BiocGenerics Imports: RCurl Suggests: org.Hs.eg.db License: Apache License 2.0 MD5sum: 736ffc97b3277ceaa21df9e1ea464954 NeedsCompilation: no Title: Protemics Standard Initiative Common QUery InterfaCe Description: PSICQUIC is a project within the HUPO Proteomics Standard Initiative (HUPO-PSI). It standardises programmatic access to molecular interaction databases. biocViews: DataImport, GraphAndNetwork, ThirdPartyClient Author: Paul Shannon Maintainer: Paul Shannon source.ver: src/contrib/PSICQUIC_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/PSICQUIC_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/PSICQUIC_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/PSICQUIC_1.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PSICQUIC_1.2.1.tgz vignettes: vignettes/PSICQUIC/inst/doc/PSICQUIC.pdf vignetteTitles: PSICQUIC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PSICQUIC/inst/doc/PSICQUIC.R dependsOnMe: RefNet Package: puma Version: 3.6.0 Depends: R (>= 3.0), Biobase (>= 2.5.5), affy (>= 1.41.3), graphics, grDevices, methods, stats, utils, mclust, oligo, Imports: Biobase (>= 2.5.5), affy (>= 1.41.3), affyio Suggests: pumadata, affydata, snow, limma, ROCR,annotate License: LGPL Archs: i386, x64 MD5sum: ac1613e96d99ef958df382cb1afd511d NeedsCompilation: yes Title: Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) Description: Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions. biocViews: Microarray, OneChannel, Preprocessing, Bioinformatics, DifferentialExpression, Clustering Author: Richard D. Pearson, Xuejun Liu, Magnus Rattray, Marta Milo, Neil D. Lawrence, Guido Sanguinetti, Li Zhang Maintainer: Richard Pearson URL: http://umber.sbs.man.ac.uk/resources/puma source.ver: src/contrib/puma_3.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/puma_3.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/puma_3.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/puma_3.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/puma_3.6.0.tgz vignettes: vignettes/puma/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE importsMe: tigre Package: pvac Version: 1.12.0 Depends: R (>= 2.8.0) Imports: affy (>= 1.20.0), stats, Biobase Suggests: pbapply, affydata, ALLMLL, genefilter License: LGPL (>= 2.0) MD5sum: 3f7c972b0f8a4ab4a09a8cf9ed63e17c NeedsCompilation: no Title: PCA-based gene filtering for Affymetrix arrays Description: The package contains the function for filtering genes by the proportion of variation accounted for by the first principal component (PVAC). biocViews: Microarray, OneChannel, QualityControl Author: Jun Lu and Pierre R. Bushel Maintainer: Jun Lu , Pierre R. Bushel source.ver: src/contrib/pvac_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pvac_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pvac_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pvac_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pvac_1.12.0.tgz vignettes: vignettes/pvac/inst/doc/pvac.pdf vignetteTitles: PCA-based gene filtering for Affymetrix GeneChips hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pvac/inst/doc/pvac.R Package: pvca Version: 1.4.0 Depends: R (>= 2.15.1) Imports: Matrix, Biobase, vsn, lme4 Suggests: golubEsets License: LGPL (>= 2.0) MD5sum: 5b3e72ae74e99380b60900181a23a97f NeedsCompilation: no Title: Principal Variance Component Analysis (PVCA) Description: This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12. biocViews: Microarray, BatchEffect Author: Pierre Bushel Maintainer: Jianying LI source.ver: src/contrib/pvca_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/pvca_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/pvca_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/pvca_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/pvca_1.4.0.tgz vignettes: vignettes/pvca/inst/doc/pvca.pdf vignetteTitles: Batch effect estimation in Microarray data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pvca/inst/doc/pvca.R Package: PWMEnrich Version: 3.6.1 Depends: methods, grid, BiocGenerics, Biostrings, Imports: seqLogo, gdata, evd Suggests: MotifDb, BSgenome.Dmelanogaster.UCSC.dm3, PWMEnrich.Dmelanogaster.background, testthat, gtools, parallel License: LGPL (>= 2) MD5sum: 5a005dd3ebd0655f3add0945fd9af424 NeedsCompilation: no Title: PWM enrichment analysis Description: A toolkit of high-level functions for DNA motif scanning and enrichment analysis built upon Biostrings. The main functionality is PWM enrichment analysis of already known PWMs (e.g. from databases such as MotifDb), but the package also implements high-level functions for PWM scanning and visualisation. The package does not perform "de novo" motif discovery, but is instead focused on using motifs that are either experimentally derived or computationally constructed by other tools. biocViews: SequenceMatching, GenomicSequence, Software Author: Robert Stojnic, Diego Diez Maintainer: Robert Stojnic source.ver: src/contrib/PWMEnrich_3.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/PWMEnrich_3.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/PWMEnrich_3.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/PWMEnrich_3.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/PWMEnrich_3.6.1.tgz vignettes: vignettes/PWMEnrich/inst/doc/PWMEnrich.pdf vignetteTitles: Overview of the 'PWMEnrich' package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PWMEnrich/inst/doc/PWMEnrich.R suggestsMe: rTRM Package: qcmetrics Version: 1.2.0 Depends: R (>= 2.10) Imports: Biobase, methods, knitr, tools, Nozzle.R1, xtable, pander Suggests: affy, MSnbase, ggplot2, lattice, yaqcaffy, MAQCsubsetAFX, RforProteomics, AnnotationDbi, mzR, hgu133plus2cdf License: GPL-2 MD5sum: c4df8195ba757745fa987af94f7ab866 NeedsCompilation: no Title: A Framework for Quality Control Description: The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats. biocViews: Software, QualityControl, Proteomics, Microarray, MassSpectrometry, Visualization Author: Laurent Gatto Maintainer: Laurent Gatto URL: https://github.com/lgatto/qcmetrics VignetteBuilder: knitr source.ver: src/contrib/qcmetrics_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/qcmetrics_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/qcmetrics_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/qcmetrics_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qcmetrics_1.2.0.tgz vignettes: vignettes/qcmetrics/inst/doc/qcmetrics.pdf vignetteTitles: The 'qcmetrics' infrastructure for quality control and reporting hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qcmetrics/inst/doc/qcmetrics.R Package: QDNAseq Version: 1.0.5 Depends: R (>= 2.15.0) Imports: graphics, methods, stats, utils, matrixStats (>= 0.9.4), R.utils (>= 1.28.4), Biobase (>= 2.18.0), CGHbase (>= 1.18.0), CGHcall (>= 2.18.0), DNAcopy (>= 1.32.0), Rsamtools (>= 1.10.0) Suggests: R.cache (>= 0.9.0), digest, snowfall, BSgenome, GenomeInfoDb, GenomicRanges License: GPL MD5sum: 8ade2fbf3a766560a6727fcc5be004c0 NeedsCompilation: no Title: Quantitative DNA sequencing for chromosomal aberrations Description: Quantitative DNA sequencing for chromosomal aberrations. biocViews: CopyNumberVariation, DNASeq, Genetics, GenomeAnnotation, Preprocessing, QualityControl, Sequencing Author: Ilari Scheinin Maintainer: Ilari Scheinin URL: https://github.com/ccagc/QDNAseq source.ver: src/contrib/QDNAseq_1.0.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/QDNAseq_1.0.5.zip win64.binary.ver: bin/windows64/contrib/3.1/QDNAseq_1.0.5.zip mac.binary.ver: bin/macosx/contrib/3.1/QDNAseq_1.0.5.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/QDNAseq_1.0.5.tgz vignettes: vignettes/QDNAseq/inst/doc/QDNAseq.pdf vignetteTitles: Introduction to QDNAseq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QDNAseq/inst/doc/QDNAseq.R Package: qpcrNorm Version: 1.22.0 Depends: methods, Biobase, limma, affy License: LGPL (>= 2) MD5sum: f2e78f88a4dd421ce606a5790e343610 NeedsCompilation: no Title: Data-driven normalization strategies for high-throughput qPCR data. Description: The package contains functions to perform normalization of high-throughput qPCR data. Basic functions for processing raw Ct data plus functions to generate diagnostic plots are also available. biocViews: Preprocessing, GeneExpression Author: Jessica Mar Maintainer: Jessica Mar source.ver: src/contrib/qpcrNorm_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/qpcrNorm_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/qpcrNorm_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/qpcrNorm_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qpcrNorm_1.22.0.tgz vignettes: vignettes/qpcrNorm/inst/doc/qpcrNorm.pdf vignetteTitles: qPCR Normalization Example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qpcrNorm/inst/doc/qpcrNorm.R suggestsMe: EasyqpcR Package: qpgraph Version: 1.20.2 Depends: R (>= 3.0.0) Imports: methods, parallel, Matrix (>= 1.0), annotate, graph (>= 1.41.2), Biobase, GGBase, AnnotationDbi, mvtnorm, qtl, Rgraphviz Suggests: BiocStyle, genefilter, org.EcK12.eg.db Enhances: rlecuyer, snow, Category, GOstats License: GPL (>= 2) Archs: i386, x64 MD5sum: 304dcb639b31acc0f9cb452497696459 NeedsCompilation: yes Title: Reverse engineering of molecular regulatory networks with qp-graphs Description: q-order partial correlation graphs, or qp-graphs for short, are undirected Gaussian graphical Markov models built from q-order partial correlations. They are useful for learning undirected graphical Gaussian Markov models from data sets where the number of random variables p exceeds the available sample size n as, for instance, in the case of microarray data where they can be employed to reverse engineer a molecular regulatory network. biocViews: Microarray, GeneExpression, Transcription, Pathways, NetworkInference, GraphAndNetwork, GeneRegulation Author: R. Castelo and A. Roverato Maintainer: Robert Castelo URL: http://functionalgenomics.upf.edu/qpgraph source.ver: src/contrib/qpgraph_1.20.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/qpgraph_1.20.2.zip win64.binary.ver: bin/windows64/contrib/3.1/qpgraph_1.20.2.zip mac.binary.ver: bin/macosx/contrib/3.1/qpgraph_1.20.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qpgraph_1.20.2.tgz vignettes: vignettes/qpgraph/inst/doc/BasicUsersGuide.pdf, vignettes/qpgraph/inst/doc/qpgraphSimulate.pdf, vignettes/qpgraph/inst/doc/qpTxRegNet.pdf vignetteTitles: BasicUsersGuide.pdf, Simulating molecular regulatory networks using qpgraph, Reverse-engineer transcriptional regulatory networks using qpgraph hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qpgraph/inst/doc/qpgraphSimulate.R, vignettes/qpgraph/inst/doc/qpTxRegNet.R importsMe: clipper Package: qrqc Version: 1.18.0 Depends: reshape, ggplot2, Biostrings, biovizBase, brew, xtable, Rsamtools (>= 1.3.28), testthat Imports: reshape, ggplot2, Biostrings, biovizBase, graphics, methods, plyr, stats LinkingTo: Rsamtools License: GPL (>=2) Archs: i386, x64 MD5sum: 0cab4c8ef66ab85ece1a8b84f67e0e39 NeedsCompilation: yes Title: Quick Read Quality Control Description: Quickly scans reads and gathers statistics on base and quality frequencies, read length, k-mers by position, and frequent sequences. Produces graphical output of statistics for use in quality control pipelines, and an optional HTML quality report. S4 SequenceSummary objects allow specific tests and functionality to be written around the data collected. biocViews: Sequencing, QualityControl, DataImport, Preprocessing, Visualization Author: Vince Buffalo Maintainer: Vince Buffalo URL: http://github.com/vsbuffalo/qrqc source.ver: src/contrib/qrqc_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/qrqc_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/qrqc_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/qrqc_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qrqc_1.18.0.tgz vignettes: vignettes/qrqc/inst/doc/qrqc.pdf vignetteTitles: Using the qrqc package to gather information about sequence qualities hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qrqc/inst/doc/qrqc.R Package: QUALIFIER Version: 1.8.23 Depends: R (>= 2.14.0),flowCore,flowViz,ncdfFlow,flowWorkspace, data.table,reshape Imports: MASS,hwriter,lattice,stats4,flowCore,flowViz,methods,flowWorkspace,latticeExtra,grDevices,tools, Biobase,XML Suggests: RSVGTipsDevice License: Artistic-2.0 MD5sum: ca7b57689e76b7d4c26b0f5a1b31b0f4 NeedsCompilation: no Title: Quality Control of Gated Flow Cytometry Experiments Description: Provides quality control and quality assessment tools for gated flow cytometry data. biocViews: Infrastructure, FlowCytometry, CellBasedAssays Author: Mike Jiang,Greg Finak,Raphael Gottardo Maintainer: Mike Jiang source.ver: src/contrib/QUALIFIER_1.8.23.tar.gz win.binary.ver: bin/windows/contrib/3.1/QUALIFIER_1.8.23.zip win64.binary.ver: bin/windows64/contrib/3.1/QUALIFIER_1.8.23.zip mac.binary.ver: bin/macosx/contrib/3.1/QUALIFIER_1.8.23.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/QUALIFIER_1.8.23.tgz vignettes: vignettes/QUALIFIER/inst/doc/QUALIFIER.pdf vignetteTitles: Quality assessment for gated Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QUALIFIER/inst/doc/QUALIFIER.R Package: quantsmooth Version: 1.30.0 Depends: R(>= 2.10.0), quantreg, grid License: GPL-2 MD5sum: 0c92ecf3ae8c34d5cd0717499422d001 NeedsCompilation: no Title: Quantile smoothing and genomic visualization of array data Description: Implements quantile smoothing as introduced in: Quantile smoothing of array CGH data; Eilers PH, de Menezes RX; Bioinformatics. 2005 Apr 1;21(7):1146-53. biocViews: Visualization, CopyNumberVariation Author: Jan Oosting, Paul Eilers, Renee Menezes Maintainer: Jan Oosting source.ver: src/contrib/quantsmooth_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/quantsmooth_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/quantsmooth_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/quantsmooth_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/quantsmooth_1.30.0.tgz vignettes: vignettes/quantsmooth/inst/doc/quantsmooth.pdf vignetteTitles: quantsmooth hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/quantsmooth/inst/doc/quantsmooth.R dependsOnMe: beadarraySNP importsMe: GWASTools, SIM suggestsMe: PREDA Package: QuasR Version: 1.4.2 Depends: parallel, GenomicRanges (>= 1.13.3), Rbowtie Imports: methods, zlibbioc, BiocGenerics, IRanges, BiocInstaller, Biobase, Biostrings, GenomicRanges, BSgenome, Rsamtools (>= 1.13.1), GenomicFeatures, ShortRead (>= 1.19.1), GenomicAlignments LinkingTo: Rsamtools Suggests: Rsamtools, rtracklayer, Gviz, RUnit, BiocStyle License: GPL-2 Archs: i386, x64 MD5sum: 3603366a7415b37fc82eab1cc2f56589 NeedsCompilation: yes Title: Quantify and Annotate Short Reads in R Description: This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. biocViews: Genetics, Preprocessing, Sequencing, ChIPSeq, RNASeq, MethylSeq Author: Anita Lerch, Dimos Gaiditzis and Michael Stadler Maintainer: Michael Stadler source.ver: src/contrib/QuasR_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/QuasR_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/QuasR_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/QuasR_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/QuasR_1.4.2.tgz vignettes: vignettes/QuasR/inst/doc/QuasR.pdf vignetteTitles: An introduction to QuasR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QuasR/inst/doc/QuasR-Overview.R, vignettes/QuasR/inst/doc/QuasR.R Package: qusage Version: 1.4.0 Depends: R (>= 2.10), limma (>= 3.14), methods Imports: utils, Biobase License: GPL (>= 2) MD5sum: 0756127f96c0ea93651dd97cc741ee50 NeedsCompilation: no Title: qusage: Quantitative Set Analysis for Gene Expression Description: This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu) biocViews: GeneSetEnrichment, Microarray, RNASeq, Software Author: Christopher Bolen and Gur Yaari, with contributions from Juilee Thakar and Steven Kleinstein Maintainer: Christopher Bolen URL: http://clip.med.yale.edu/qusage source.ver: src/contrib/qusage_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/qusage_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/qusage_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/qusage_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qusage_1.4.0.tgz vignettes: vignettes/qusage/inst/doc/qusage.pdf vignetteTitles: Running qusage hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qusage/inst/doc/qusage.R Package: qvalue Version: 1.38.0 Imports: graphics, grDevices, stats, tcltk License: LGPL MD5sum: d3a580ea20b886f5f05a24c5174035cf NeedsCompilation: no Title: Q-value estimation for false discovery rate control Description: This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. Various plots are automatically generated, allowing one to make sensible significance cut-offs. Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining. biocViews: MultipleComparison Author: Alan Dabney and John D. Storey Maintainer: John D. Storey source.ver: src/contrib/qvalue_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/qvalue_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/qvalue_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/qvalue_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/qvalue_1.38.0.tgz vignettes: vignettes/qvalue/inst/doc/qvalue.pdf vignetteTitles: qvalue Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qvalue/inst/doc/qvalue.R dependsOnMe: anota, CancerMutationAnalysis, DEGseq, DrugVsDisease, metaseqR, netresponse, SSPA, webbioc importsMe: anota, DOSE, msmsTests, sRAP, synapter, trigger, webbioc suggestsMe: LBE, maanova, PREDA Package: r3Cseq Version: 1.10.0 Depends: GenomicRanges,Rsamtools,data.table,rtracklayer,VGAM,qvalue,RColorBrewer,sqldf,methods Suggests: BSgenome.Mmusculus.UCSC.mm9.masked,BSgenome.Hsapiens.UCSC.hg18.masked,BSgenome.Hsapiens.UCSC.hg19.masked License: GPL-3 MD5sum: b5e99276514c1dda8ebf5b155e61c410 NeedsCompilation: no Title: Analysis of Chromosome Conformation Capture and Next-generation Sequencing (3C-seq) Description: This package is an implementation of data analysis for the long-range interactions from 3C-seq assay. biocViews: Preprocessing, Sequencing Author: Supat Thongjuea, MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, UK Maintainer: Supat Thongjuea URL: http://r3cseq.genereg.net source.ver: src/contrib/r3Cseq_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/r3Cseq_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/r3Cseq_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/r3Cseq_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/r3Cseq_1.10.0.tgz vignettes: vignettes/r3Cseq/inst/doc/r3Cseq.pdf vignetteTitles: r3Cseq hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/r3Cseq/inst/doc/r3Cseq.R Package: R453Plus1Toolbox Version: 1.14.0 Depends: R (>= 2.12.0), Biobase, Biostrings, GenomicRanges Imports: BiocGenerics (>= 0.1.3), biomaRt, BSgenome, IRanges, XVector, methods, R2HTML, Rsamtools, ShortRead, VariantAnnotation, xtable, tools, TeachingDemos Suggests: rtracklayer, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Scerevisiae.UCSC.sacCer2 License: LGPL-3 Archs: i386, x64 MD5sum: 3c0d780eddfcb6fcc2b81370c86f71d6 NeedsCompilation: yes Title: A package for importing and analyzing data from Roche's Genome Sequencer System. Description: The R453Plus1 Toolbox comprises useful functions for the analysis of data generated by Roche's 454 sequencing platform. It adds functions for quality assurance as well as for annotation and visualization of detected variants, complementing the software tools shipped by Roche with their product. Further, a pipeline for the detection of structural variants is provided. biocViews: Sequencing, Infrastructure, DataImport, DataRepresentation, Visualization, QualityControl, ReportWriting Author: Hans-Ulrich Klein, Christoph Bartenhagen, Christian Ruckert Maintainer: Hans-Ulrich Klein source.ver: src/contrib/R453Plus1Toolbox_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/R453Plus1Toolbox_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/R453Plus1Toolbox_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/R453Plus1Toolbox_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/R453Plus1Toolbox_1.14.0.tgz vignettes: vignettes/R453Plus1Toolbox/inst/doc/vignette.pdf vignetteTitles: A package for importing and analyzing data from Roche's Genome Sequencer System hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/R453Plus1Toolbox/inst/doc/vignette.R Package: rama Version: 1.38.0 Depends: R(>= 2.5.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: f916fb59cc93f96d639d5d5900b137a2 NeedsCompilation: yes Title: Robust Analysis of MicroArrays Description: Robust estimation of cDNA microarray intensities with replicates. The package uses a Bayesian hierarchical model for the robust estimation. Outliers are modeled explicitly using a t-distribution, and the model also addresses classical issues such as design effects, normalization, transformation, and nonconstant variance. biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/rama_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rama_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rama_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rama_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rama_1.38.0.tgz vignettes: vignettes/rama/inst/doc/rama.pdf vignetteTitles: rama Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rama/inst/doc/rama.R dependsOnMe: bridge Package: RamiGO Version: 1.10.0 Depends: gsubfn,methods Imports: igraph,RCurl,png,RCytoscape,graph License: Artistic-2.0 MD5sum: 10efbe664ac08bdda8f375264b591916 NeedsCompilation: no Title: AmiGO visualize R interface Description: R interface sending requests to AmiGO visualize, retrieving DAG GO trees, parsing GraphViz DOT format files and exporting GML files for Cytoscape. Also uses RCytoscape to interactively display AmiGO trees in Cytoscape. biocViews: GO, Visualization, GraphAndNetwork, Classification, ThirdPartyClient Author: Markus Schroeder, Daniel Gusenleitner, John Quackenbush, Aedin Culhane, Benjamin Haibe-Kains Maintainer: Markus Schroeder source.ver: src/contrib/RamiGO_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RamiGO_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RamiGO_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RamiGO_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RamiGO_1.10.0.tgz vignettes: vignettes/RamiGO/inst/doc/RamiGO.pdf vignetteTitles: RamiGO: An Introduction (HowTo) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RamiGO/inst/doc/RamiGO.R Package: randPack Version: 1.10.0 Depends: methods Imports: Biobase License: Artistic 2.0 MD5sum: 81333fea32efbfdd5e7740f2e6397bd7 NeedsCompilation: no Title: Randomization routines for Clinical Trials Description: A suite of classes and functions for randomizing patients in clinical trials. biocViews: StatisticalMethod Author: Vincent Carey and Robert Gentleman Maintainer: Robert Gentleman source.ver: src/contrib/randPack_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/randPack_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/randPack_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/randPack_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/randPack_1.10.0.tgz vignettes: vignettes/randPack/inst/doc/randPack.pdf vignetteTitles: Clinical trial randomization infrastructure hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/randPack/inst/doc/randPack.R Package: RankProd Version: 2.36.0 Depends: R (>= 1.9.0) Imports: graphics License: file LICENSE License_restricts_use: yes MD5sum: b6495bd4649fc45da64ad8250b105046 NeedsCompilation: no Title: Rank Product method for identifying differentially expressed genes with application in meta-analysis Description: Non-parametric method for identifying differentially expressed (up- or down- regulated) genes based on the estimated percentage of false predictions (pfp). The method can combine data sets from different origins (meta-analysis) to increase the power of the identification. biocViews: DifferentialExpression Author: Fangxin Hong and Ben Wittner with contribution from Rainer Breitling , Colin Smith , and Florian Battke Maintainer: Fangxin Hong source.ver: src/contrib/RankProd_2.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RankProd_2.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RankProd_2.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RankProd_2.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RankProd_2.36.0.tgz vignettes: vignettes/RankProd/inst/doc/RankProd.pdf vignetteTitles: RankProd Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RankProd/inst/doc/RankProd.R dependsOnMe: RNAither, tRanslatome importsMe: HTSanalyzeR suggestsMe: oneChannelGUI Package: Rariant Version: 1.0.0 Depends: R (>= 3.0.2) Imports: IRanges, ggbio, ggplot2, VariantAnnotation, h5vc, exomeCopy, SomaticSignatures, Rsamtools, shiny, GenomicRanges Suggests: h5vcData, testthat, knitr, BiocStyle, biovizBase, optparse License: GPL-3 MD5sum: 47beebbfe1fa433d604d20b045924b06 NeedsCompilation: no Title: Identification and Assessment of Single Nucleotide Variants through Shifts in Non-Consensus Base Call Frequencies Description: The 'Rariant' package identifies single nucleotide variants from sequencing data based on the difference of binomially distributed mismatch rates between matched samples. biocViews: Sequencing, StatisticalMethod, GenomicVariation, SomaticMutation, VariantDetection, Visualization Author: Julian Gehring, Simon Anders, Bernd Klaus (EMBL Heidelberg) Maintainer: Julian Gehring VignetteBuilder: knitr source.ver: src/contrib/Rariant_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rariant_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rariant_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rariant_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rariant_1.0.0.tgz vignettes: vignettes/Rariant/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rariant/inst/doc/Rariant-vignette.R htmlDocs: vignettes/Rariant/inst/doc/Rariant-vignette.html htmlTitles: "Rariant - HTML" Package: RbcBook1 Version: 1.32.0 Depends: R (>= 2.10), Biobase, graph, rpart License: Artistic-2.0 MD5sum: b895de489e1e0ecb3f27cffe1b41b7a9 NeedsCompilation: no Title: Support for Springer monograph on Bioconductor Description: tools for building book biocViews: Software Author: Vince Carey and Wolfgang Huber Maintainer: Vince Carey URL: http://www.biostat.harvard.edu/~carey source.ver: src/contrib/RbcBook1_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RbcBook1_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RbcBook1_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RbcBook1_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RbcBook1_1.32.0.tgz vignettes: vignettes/RbcBook1/inst/doc/RbcBook1.pdf vignetteTitles: RbcBook1 Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RbcBook1/inst/doc/RbcBook1.R Package: RBGL Version: 1.40.1 Depends: graph, methods Imports: methods Suggests: Rgraphviz, XML License: Artistic-2.0 Archs: i386, x64 MD5sum: 9b92ab942e08916c62d40fe42b71ebf0 NeedsCompilation: yes Title: An interface to the BOOST graph library Description: A fairly extensive and comprehensive interface to the graph algorithms contained in the BOOST library. biocViews: GraphAndNetwork, Network Author: Vince Carey , Li Long , R. Gentleman Maintainer: Bioconductor Package Maintainer URL: http://www.bioconductor.org source.ver: src/contrib/RBGL_1.40.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/RBGL_1.40.1.zip win64.binary.ver: bin/windows64/contrib/3.1/RBGL_1.40.1.zip mac.binary.ver: bin/macosx/contrib/3.1/RBGL_1.40.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RBGL_1.40.1.tgz vignettes: vignettes/RBGL/inst/doc/RBGL.pdf vignetteTitles: RBGL Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RBGL/inst/doc/RBGL.R dependsOnMe: apComplex, BioNet, CellNOptR, joda, pkgDepTools, RpsiXML importsMe: biocViews, CAMERA, Category, clipper, DEGraph, flowWorkspace, GeneAnswers, GOSim, GOstats, NCIgraph, nem, OrganismDbi, pkgDepTools, predictionet, RDAVIDWebService, Streamer suggestsMe: BiocCaseStudies, DEGraph, GeneNetworkBuilder, graph, KEGGgraph, rBiopaxParser, VariantTools Package: RBioinf Version: 1.24.0 Depends: graph, methods Suggests: Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: a9a14512b58a18274be35a461ce67f26 NeedsCompilation: yes Title: RBioinf Description: Functions and datasets and examples to accompany the monograph R For Bioinformatics. biocViews: GeneExpression, Microarray, Preprocessing, QualityControl, Classification, Clustering, MultipleComparison, Annotation Author: Robert Gentleman Maintainer: Robert Gentleman source.ver: src/contrib/RBioinf_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RBioinf_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RBioinf_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RBioinf_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RBioinf_1.24.0.tgz vignettes: vignettes/RBioinf/inst/doc/RBioinf.pdf vignetteTitles: RBioinf Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RBioinf/inst/doc/RBioinf.R Package: rBiopaxParser Version: 2.2.0 Depends: R (>= 3.0.0), data.table Imports: XML Suggests: Rgraphviz, RCurl, graph, RUnit, BiocGenerics, nem, RBGL License: GPL (>= 2) MD5sum: 7ca1d9eeef3b55b660a6387f87eeb721 NeedsCompilation: no Title: Parses BioPax files and represents them in R Description: Parses BioPAX files and represents them in R, at the moment BioPAX level 2 and level 3 are supported. biocViews: DataRepresentation Author: Frank Kramer Maintainer: Frank Kramer URL: https://github.com/frankkramer/rBiopaxParser source.ver: src/contrib/rBiopaxParser_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rBiopaxParser_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rBiopaxParser_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rBiopaxParser_2.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rBiopaxParser_2.2.0.tgz vignettes: vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.pdf vignetteTitles: rBiopaxParser Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.R suggestsMe: NetPathMiner Package: Rbowtie Version: 1.4.5 Suggests: parallel License: Artistic-1.0 | file LICENSE MD5sum: c0c4caba91563a8e0f067114dce72e55 NeedsCompilation: yes Title: R bowtie wrapper Description: This package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool. The package is used by the QuasR bioconductor package. We recommend to use the QuasR package instead of using Rbowtie directly. biocViews: Sequencing, Alignment Author: Florian Hahne, Anita Lerch, Michael B Stadler Maintainer: Michael Stadler source.ver: src/contrib/Rbowtie_1.4.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rbowtie_1.4.5.zip win64.binary.ver: bin/windows64/contrib/3.1/Rbowtie_1.4.5.zip mac.binary.ver: bin/macosx/contrib/3.1/Rbowtie_1.4.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rbowtie_1.4.5.tgz vignettes: vignettes/Rbowtie/inst/doc/Rbowtie-Overview.pdf vignetteTitles: An introduction to Rbowtie hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/Rbowtie/inst/doc/Rbowtie-Overview.R dependsOnMe: QuasR Package: rbsurv Version: 2.22.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), survival License: GPL (>= 2) MD5sum: 067f1a0901313da9ec5d541e2139e43a NeedsCompilation: no Title: Robust likelihood-based survival modeling with microarray data Description: This package selects genes associated with survival. biocViews: Microarray Author: HyungJun Cho , Sukwoo Kim , Soo-heang Eo , Jaewoo Kang Maintainer: Soo-heang Eo URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/rbsurv_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rbsurv_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rbsurv_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rbsurv_2.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rbsurv_2.22.0.tgz vignettes: vignettes/rbsurv/inst/doc/rbsurv.pdf vignetteTitles: Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rbsurv/inst/doc/rbsurv.R Package: Rcade Version: 1.6.0 Depends: R (>= 2.14.0), methods, GenomicRanges, baySeq, Rsamtools Imports: graphics, IRanges, rgl Suggests: limma, biomaRt, RUnit, BiocGenerics, BiocStyle License: GPL-2 MD5sum: a235e17714a7b98bc24980812c1b2bb4 NeedsCompilation: no Title: R-based analysis of ChIP-seq And Differential Expression - a tool for integrating a count-based ChIP-seq analysis with differential expression summary data. Description: Rcade (which stands for "R-based analysis of ChIP-seq And Differential Expression") is a tool for integrating ChIP-seq data with differential expression summary data, through a Bayesian framework. A key application is in identifing the genes targeted by a transcription factor of interest - that is, we collect genes that are associated with a ChIP-seq peak, and differential expression under some perturbation related to that TF. biocViews: DifferentialExpression, GeneExpression, Transcription, ChIPSeq, Sequencing, Genetics Author: Jonathan Cairns Maintainer: Jonathan Cairns source.ver: src/contrib/Rcade_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rcade_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rcade_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rcade_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rcade_1.6.0.tgz vignettes: vignettes/Rcade/inst/doc/Rcade.pdf vignetteTitles: Rcade Vignette hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rcade/inst/doc/Rcade.R Package: RCASPAR Version: 1.10.0 License: GPL (>=3) MD5sum: 628986373c826a618bfe0f0afe4a1524 NeedsCompilation: no Title: A package for survival time prediction based on a piecewise baseline hazard Cox regression model. Description: The package is the R-version of the C-based software \bold{CASPAR} (Kaderali,2006: \url{http://bioinformatics.oxfordjournals.org/content/22/12/1495}). It is meant to help predict survival times in the presence of high-dimensional explanatory covariates. The model is a piecewise baseline hazard Cox regression model with an Lq-norm based prior that selects for the most important regression coefficients, and in turn the most relevant covariates for survival analysis. It was primarily tried on gene expression and aCGH data, but can be used on any other type of high-dimensional data and in disciplines other than biology and medicine. biocViews: aCGH, GeneExpression, Genetics, Proteomics, Visualization Author: Douaa Mugahid Maintainer: Douaa Mugahid , Lars Kaderali source.ver: src/contrib/RCASPAR_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RCASPAR_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RCASPAR_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RCASPAR_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RCASPAR_1.10.0.tgz vignettes: vignettes/RCASPAR/inst/doc/RCASPAR.pdf vignetteTitles: RCASPAR: Software for high-dimentional-data driven survival time prediction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RCASPAR/inst/doc/RCASPAR.R Package: Rchemcpp Version: 2.2.0 Depends: R (>= 2.15.0) Imports: Rcpp (>= 0.11.1), methods, ChemmineR LinkingTo: Rcpp Suggests: apcluster, kernlab License: GPL (>= 2.1) Archs: i386, x64 MD5sum: 2eab5f3431ae6f851548016b0892897a NeedsCompilation: yes Title: Similarity measures for chemical compounds Description: The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules. biocViews: Bioinformatics, CellBasedAssays, Clustering, DataImport, Infrastructure, MicrotitrePlateAssay, Proteomics, Software, Visualization Author: Michael Mahr, Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/Rchemcpp source.ver: src/contrib/Rchemcpp_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rchemcpp_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rchemcpp_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rchemcpp_2.2.0.tgz vignettes: vignettes/Rchemcpp/inst/doc/Rchemcpp.pdf vignetteTitles: Rchemcpp hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rchemcpp/inst/doc/Rchemcpp.R Package: RchyOptimyx Version: 2.4.0 Depends: R (>= 2.10) Imports: Rgraphviz, sfsmisc, graphics, methods, graph, grDevices, flowType (>= 2.0.0) Suggests: flowCore License: Artistic-2.0 Archs: i386, x64 MD5sum: 0f188ffcfcbc6383bf000b614759db5f NeedsCompilation: yes Title: Optimyzed Cellular Hierarchies for Flow Cytometry Description: Constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response). biocViews: FlowCytometry Author: Adrin Jalali, Nima Aghaeepour Maintainer: Adrin Jalali , Nima Aghaeepour source.ver: src/contrib/RchyOptimyx_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RchyOptimyx_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RchyOptimyx_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RchyOptimyx_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RchyOptimyx_2.4.0.tgz vignettes: vignettes/RchyOptimyx/inst/doc/RchyOptimyx.pdf vignetteTitles: flowType package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RchyOptimyx/inst/doc/RchyOptimyx.R Package: Rcpi Version: 1.0.2 Imports: RCurl, rjson, rcdk, foreach, doParallel, Biostrings, GOSemSim, ChemmineR, fmcsR Suggests: RUnit, BiocGenerics Enhances: ChemmineOB License: Artistic-2.0 MD5sum: ad0eca2f70a1d5432dbb1a3fb3712716 NeedsCompilation: no Title: Toolkit for Compound-Protein Interaction in Drug Discovery Description: The Rcpi package offers an R/Bioconductor package emphasizing the comprehensive integration of bioinformatics and chemoinformatics into a molecular informatics platform for drug discovery. biocViews: Software, DataImport, DataRepresentation, FeatureExtraction, Cheminformatics, BiomedicalInformatics, Proteomics, GO, GraphAndNetwork, SystemsBiology Author: Nan Xiao , Dongsheng Cao , Qingsong Xu Maintainer: Nan Xiao URL: https://github.com/road2stat/Rcpi source.ver: src/contrib/Rcpi_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rcpi_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/Rcpi_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/Rcpi_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rcpi_1.0.2.tgz vignettes: vignettes/Rcpi/inst/doc/Rcpi.pdf, vignettes/Rcpi/inst/doc/Rcpi-quickref.pdf vignetteTitles: Rcpi: R/Bioconductor Package as an Integrated Informatics Platform in Drug Discovery, Rcpi Quick Reference Card hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rcpi/inst/doc/Rcpi-quickref.R, vignettes/Rcpi/inst/doc/Rcpi.R Package: RCytoscape Version: 1.14.0 Depends: R (>= 2.14.0), graph (>= 1.31.0), XMLRPC (>= 0.2.4) Imports: methods, XMLRPC, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: eb08c22f5fdc63eeeadee28bcd5e11b7 NeedsCompilation: no Title: Display and manipulate graphs in Cytoscape Description: Interactvive viewing and exploration of graphs, connecting R to Cytoscape. biocViews: Visualization, GraphAndNetwork, ThirdPartyClient Author: Paul Shannon Maintainer: Paul Shannon URL: http://rcytoscape.systemsbiology.net source.ver: src/contrib/RCytoscape_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RCytoscape_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RCytoscape_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RCytoscape_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RCytoscape_1.14.0.tgz vignettes: vignettes/RCytoscape/inst/doc/RCytoscape.pdf vignetteTitles: RCytoscape Overview hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RCytoscape/inst/doc/RCytoscape.R importsMe: categoryCompare, NCIgraph suggestsMe: clipper, GeneNetworkBuilder, graphite, mmnet, NetPathMiner Package: RDAVIDWebService Version: 1.2.0 Depends: R (>= 2.14.1), methods, graph, GOstats, ggplot2 Imports: Category, GO.db, RBGL, rJava Suggests: Rgraphviz License: GPL (>=2) MD5sum: 73df072f6a592ea242530394ae14063a NeedsCompilation: no Title: An R Package for retrieving data from DAVID into R objects using Web Services API. Description: Tools for retrieving data from the Database for Annotation, Visualization and Integrated Discovery (DAVID) using Web Services into R objects. This package offers the main functionalities of DAVID website including: i) user friendly connectivity to upload gene/background list/s, change gene/background position, select current specie/s, select annotations, etc. ii) Reports of the submitted Gene List, Annotation Category Summary, Gene/Term Clusters, Functional Annotation Chart, Functional Annotation Table biocViews: Visualization, DifferentialExpression, ExperimentData, Cancer Author: Cristobal Fresno and Elmer A. Fernandez Maintainer: Cristobal Fresno URL: http://www.bdmg.com.ar, http://david.abcc.ncifcrf.gov/ source.ver: src/contrib/RDAVIDWebService_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RDAVIDWebService_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RDAVIDWebService_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RDAVIDWebService_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RDAVIDWebService_1.2.0.tgz vignettes: vignettes/RDAVIDWebService/inst/doc/RDavidWS-vignette.pdf vignetteTitles: RDAVIDWebService: a versatile R interface to DAVID hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RDAVIDWebService/inst/doc/RDavidWS-vignette.R dependsOnMe: CompGO Package: Rdisop Version: 1.24.1 Depends: R (>= 2.0.0), RcppClassic LinkingTo: RcppClassic, Rcpp Suggests: RUnit License: GPL-2 Archs: i386, x64 MD5sum: 2ac72bd7832d8ace208611a6386146e5 NeedsCompilation: yes Title: Decomposition of Isotopic Patterns Description: Identification of metabolites using high precision mass spectrometry. MS Peaks are used to derive a ranked list of sum formulae, alternatively for a given sum formula the theoretical isotope distribution can be calculated to search in MS peak lists. biocViews: MassSpectrometry Author: Anton Pervukhin , Steffen Neumann Maintainer: Steffen Neumann URL: http://msbi.ipb-halle.de/ SystemRequirements: None source.ver: src/contrib/Rdisop_1.24.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rdisop_1.24.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Rdisop_1.24.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Rdisop_1.24.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rdisop_1.24.1.tgz vignettes: vignettes/Rdisop/inst/doc/Rdisop.pdf vignetteTitles: Molecule Identification with Rdisop hasREADME: FALSE hasNEWS: FALSE hasINSTALL: TRUE hasLICENSE: FALSE Rfiles: vignettes/Rdisop/inst/doc/Rdisop.R suggestsMe: MSnbase Package: RDRToolbox Version: 1.14.0 Depends: R (>= 2.9.0) Imports: graphics, grDevices, methods, stats, MASS, rgl Suggests: golubEsets License: GPL (>= 2) MD5sum: 7e0fd28b0be4b0c96b0504c52ac67b24 NeedsCompilation: no Title: A package for nonlinear dimension reduction with Isomap and LLE. Description: A package for nonlinear dimension reduction using the Isomap and LLE algorithm. It also includes a routine for computing the Davis-Bouldin-Index for cluster validation, a plotting tool and a data generator for microarray gene expression data and for the Swiss Roll dataset. biocViews: Dimension, DimensionReduction, FeatureExtraction, Visualization, Clustering, Microarray Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RDRToolbox_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RDRToolbox_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RDRToolbox_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RDRToolbox_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RDRToolbox_1.14.0.tgz vignettes: vignettes/RDRToolbox/inst/doc/vignette.pdf vignetteTitles: A package for nonlinear dimension reduction with Isomap and LLE. hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RDRToolbox/inst/doc/vignette.R Package: ReactomePA Version: 1.8.1 Imports: AnnotationDbi, reactome.db, org.Hs.eg.db, DOSE, igraph, graphite Suggests: clusterProfiler, GOSemSim, ChIPseeker, knitr License: GPL-2 MD5sum: e81c2797d8bcf5625b9bc08ea328caf9 NeedsCompilation: no Title: Reactome Pathway Analysis Description: This package provides functions for pathway analysis based on REACTOME pathway database. It will implement enrichment analysis, gene set enrichment analysis and functional modules detection. biocViews: Pathways, Visualization, Annotation Author: Guangchuang Yu Maintainer: Guangchuang Yu VignetteBuilder: knitr source.ver: src/contrib/ReactomePA_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/ReactomePA_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/ReactomePA_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/ReactomePA_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ReactomePA_1.8.1.tgz vignettes: vignettes/ReactomePA/inst/doc/ReactomePA.pdf vignetteTitles: ReactomePA - an R package for Reactome Pathway Analysis hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReactomePA/inst/doc/ReactomePA.R suggestsMe: ChIPseeker, clusterProfiler, DOSE Package: ReadqPCR Version: 1.10.0 Depends: R(>= 2.14.0), Biobase, methods, affy Imports: Biobase Suggests: qpcR License: LGPL-3 MD5sum: e39a6ea2737bc90d617b24b71ac2c522 NeedsCompilation: no Title: Read qPCR data Description: The package provides functions to read raw RT-qPCR data of different platforms. biocViews: DataImport, MicrotitrePlateAssay, GeneExpression, qPCR Author: James Perkins, Matthias Kohl, Nor Izayu Abdul Rahman Maintainer: James Perkins URL: http://www.bioconductor.org/packages/release/bioc/html/ReadqPCR.html source.ver: src/contrib/ReadqPCR_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ReadqPCR_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ReadqPCR_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ReadqPCR_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ReadqPCR_1.10.0.tgz vignettes: vignettes/ReadqPCR/inst/doc/ReadqPCR.pdf vignetteTitles: Functions to load RT-qPCR data into R hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReadqPCR/inst/doc/ReadqPCR.R dependsOnMe: NormqPCR Package: reb Version: 1.42.0 Depends: R (>= 2.0), Biobase, idiogram (>= 1.5.3) License: GPL-2 Archs: i386, x64 MD5sum: 2aa657fb1f10d8010b0d5e2d4dbaf28b NeedsCompilation: yes Title: Regional Expression Biases Description: A set of functions to dentify regional expression biases biocViews: Microarray, CopyNumberVariation, Visualization Author: Kyle A. Furge and Karl Dykema Maintainer: Karl J. Dykema source.ver: src/contrib/reb_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/reb_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/reb_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/reb_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/reb_1.42.0.tgz vignettes: vignettes/reb/inst/doc/reb.pdf vignetteTitles: Smoothing of Microarray Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/reb/inst/doc/reb.R Package: RedeR Version: 1.12.9 Depends: R (>= 2.15), methods, igraph Imports: RCurl, XML Suggests: PANR, pvclust License: GPL (>= 2) MD5sum: 2cad007bd71ea666bf67e21d3c33483c NeedsCompilation: no Title: Interactive visualization and manipulation of nested networks Description: RedeR is an R-based package combined with a stand-alone Java application for interactive visualization and manipulation of modular structures, nested networks and multiple levels of hierarchical associations. biocViews: Infrastructure, GraphAndNetwork, Software, Network, Visualization, DataRepresentation Author: Mauro Castro, Xin Wang, Florian Markowetz Maintainer: Mauro Castro URL: http://genomebiology.com/2012/13/4/R29 source.ver: src/contrib/RedeR_1.12.9.tar.gz win.binary.ver: bin/windows/contrib/3.1/RedeR_1.12.9.zip win64.binary.ver: bin/windows64/contrib/3.1/RedeR_1.12.9.zip mac.binary.ver: bin/macosx/contrib/3.1/RedeR_1.12.9.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RedeR_1.12.9.tgz vignettes: vignettes/RedeR/inst/doc/RedeR.pdf vignetteTitles: Main vignette: interactive visualization and manipulation of nested networks hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RedeR/inst/doc/RedeR.R importsMe: RTN suggestsMe: PANR Package: REDseq Version: 1.10.0 Depends: R (>= 2.15.0), BiocGenerics (>= 0.1.0), BSgenome.Celegans.UCSC.ce2, multtest, Biostrings, BSgenome, ChIPpeakAnno Imports: BiocGenerics, AnnotationDbi, Biostrings, ChIPpeakAnno, graphics, IRanges (>= 1.13.5), multtest, stats, utils License: GPL (>=2) MD5sum: b3bcddd851316e37b77d548b24dd9150 NeedsCompilation: no Title: Analysis of high-throughput sequencing data processed by restriction enzyme digestion Description: The package includes functions to build restriction enzyme cut site (RECS) map, distribute mapped sequences on the map with five different approaches, find enriched/depleted RECSs for a sample, and identify differentially enriched/depleted RECSs between samples. biocViews: Sequencing, SequenceMatching, Preprocessing Author: Lihua Julie Zhu and Thomas Fazzio Maintainer: Lihua Julie Zhu source.ver: src/contrib/REDseq_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/REDseq_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/REDseq_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/REDseq_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/REDseq_1.10.0.tgz vignettes: vignettes/REDseq/inst/doc/REDseq.pdf vignetteTitles: REDseq Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/REDseq/inst/doc/REDseq.R Package: RefNet Version: 1.0.4 Depends: R (>= 2.15.0), methods, IRanges, PSICQUIC, AnnotationHub, RCurl Imports: BiocGenerics Suggests: RUnit, BiocStyle, org.Hs.eg.db License: Artistic-2.0 MD5sum: a7811ff69ca6397776d3d68862bff28b NeedsCompilation: no Title: A queryable collection of molecular interactions, from many sources Description: Molecular interactions with metadata, some archived, some dynamically obtained biocViews: GraphAndNetwork Author: Paul Shannon Maintainer: Paul Shannon source.ver: src/contrib/RefNet_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/RefNet_1.0.4.zip win64.binary.ver: bin/windows64/contrib/3.1/RefNet_1.0.4.zip mac.binary.ver: bin/macosx/contrib/3.1/RefNet_1.0.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RefNet_1.0.4.tgz vignettes: vignettes/RefNet/inst/doc/RefNet.pdf vignetteTitles: RefNet hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RefNet/inst/doc/RefNet.R Package: RefPlus Version: 1.34.0 Depends: R (>= 2.8.0), Biobase (>= 2.1.0), affy (>= 1.20.0), affyPLM (>= 1.18.0), preprocessCore (>= 1.4.0) Suggests: affydata License: GPL (>= 2) MD5sum: ecde2300c4e3884d0760091d2ecba337 NeedsCompilation: no Title: A function set for the Extrapolation Strategy (RMA+) and Extrapolation Averaging (RMA++) methods. Description: The package contains functions for pre-processing Affymetrix data using the RMA+ and the RMA++ methods. biocViews: Microarray, OneChannel, Preprocessing Author: Kai-Ming Chang , Chris Harbron , Marie C South Maintainer: Kai-Ming Chang source.ver: src/contrib/RefPlus_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RefPlus_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RefPlus_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RefPlus_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RefPlus_1.34.0.tgz vignettes: vignettes/RefPlus/inst/doc/RefPlus.pdf vignetteTitles: RefPlus Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RefPlus/inst/doc/RefPlus.R Package: Repitools Version: 1.10.1 Depends: R (>= 3.0.0), methods, BiocGenerics (>= 0.8.0) Imports: IRanges (>= 1.20.0), GenomicRanges, GenomicAlignments, BSgenome, gplots, grid, MASS, gsmoothr, edgeR (>= 3.4.0), DNAcopy, Ringo, aroma.affymetrix, Rsolnp, parallel, Biostrings, Rsamtools, cluster Suggests: ShortRead, BSgenome.Hsapiens.UCSC.hg18, rtracklayer License: LGPL (>= 2) Archs: i386, x64 MD5sum: 1492dff34d67382fd33587ab15a317aa NeedsCompilation: yes Title: Epigenomic tools Description: Tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc. biocViews: DNAMethylation, GeneExpression, MethylSeq Author: Mark Robinson , Dario Strbenac , Aaron Statham , Andrea Riebler Maintainer: Mark Robinson source.ver: src/contrib/Repitools_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Repitools_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Repitools_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Repitools_1.10.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Repitools_1.10.1.tgz vignettes: vignettes/Repitools/inst/doc/Repitools_vignette.pdf vignetteTitles: Using Repitools for Epigenomic Sequencing Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Repitools/inst/doc/Repitools_vignette.R Package: ReportingTools Version: 2.4.0 Depends: methods, knitr Imports: Biobase,hwriter,Category,GOstats,limma(>= 3.17.5),lattice,AnnotationDbi,edgeR, annotate,PFAM.db, GSEABase, BiocGenerics(>= 0.1.6), grid, XML, R.utils, DESeq2(>= 1.3.41), IRanges, ggplot2, ggbio Suggests: RUnit, ALL, hgu95av2.db, org.Mm.eg.db, shiny, pasilla, License: Artistic-2.0 MD5sum: 6bae53b1b4b8a7e210a490840ed57e3a NeedsCompilation: no Title: Tools for making reports in various formats Description: The ReportingTools software package enables users to easily display reports of analysis results generated from sources such as microarray and sequencing data. The package allows users to create HTML pages that may be viewed on a web browser such as Safari, or in other formats readable by programs such as Excel. Users can generate tables with sortable and filterable columns, make and display plots, and link table entries to other data sources such as NCBI or larger plots within the HTML page. Using the package, users can also produce a table of contents page to link various reports together for a particular project that can be viewed in a web browser. For more examples, please visit our site: http:// research-pub.gene.com/ReportingTools. biocViews: Software, Visualization, Microarray, RNASeq, GO, Bioinformatics, DataRepresentation, Enrichment, GeneSetEnrichment Author: Jason A. Hackney, Melanie Huntley, Jessica L. Larson, Christina Chaivorapol, Gabriel Becker, and Josh Kaminker Maintainer: Jason A. Hackney , Gabriel Becker , Jessica L. Larson VignetteBuilder: utils, knitr source.ver: src/contrib/ReportingTools_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ReportingTools_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ReportingTools_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ReportingTools_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ReportingTools_2.4.0.tgz vignettes: vignettes/ReportingTools/inst/doc/basicReportingTools.pdf, vignettes/ReportingTools/inst/doc/microarrayAnalysis.pdf, vignettes/ReportingTools/inst/doc/rnaseqAnalysis.pdf, vignettes/ReportingTools/inst/doc/shiny.pdf vignetteTitles: ReportingTools basics, Reporting on microarray differential expression, Reporting on RNA-seq differential expression, ReportingTools shiny hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReportingTools/inst/doc/basicReportingTools.R, vignettes/ReportingTools/inst/doc/knitr.R, vignettes/ReportingTools/inst/doc/microarrayAnalysis.R, vignettes/ReportingTools/inst/doc/rnaseqAnalysis.R, vignettes/ReportingTools/inst/doc/shiny.R htmlDocs: vignettes/ReportingTools/inst/doc/knitr.html htmlTitles: "Knitr and ReportingTools" importsMe: affycoretools, biosvd suggestsMe: GSEABase, npGSEA Package: ReQON Version: 1.10.0 Depends: R (>= 3.0.2), Rsamtools, seqbias Imports: rJava, graphics, stats, utils, grDevices Suggests: BiocStyle License: GPL-2 MD5sum: 9b48ccd475b6462ad8939275c7145dad NeedsCompilation: no Title: Recalibrating Quality Of Nucleotides Description: Algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format. biocViews: Sequencing, Preprocessing, QualityControl Author: Christopher Cabanski, Keary Cavin, Chris Bizon Maintainer: Christopher Cabanski SystemRequirements: Java version >= 1.6 source.ver: src/contrib/ReQON_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ReQON_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ReQON_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ReQON_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ReQON_1.10.0.tgz vignettes: vignettes/ReQON/inst/doc/ReQON.pdf vignetteTitles: ReQON Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ReQON/inst/doc/ReQON.R Package: Resourcerer Version: 1.38.0 Depends: R (>= 1.9.0), Biobase, AnnotationDbi (>= 1.4.0) Suggests: human.db0, mouse.db0, rat.db0 License: LGPL MD5sum: 53c5f3e4a7b17db7466bdabd86aec5d4 NeedsCompilation: no Title: Reads annotation data from TIGR Resourcerer or convert the annotation data into Bioconductor data pacakge. Description: This package allows user either to read an annotation data file from TIGR Resourcerer as a matrix or convert the file into a Bioconductor annotation data package using the AnnBuilder package. biocViews: Annotation, Microarray Author: Jianhua Zhang Maintainer: Jianhua Zhang source.ver: src/contrib/Resourcerer_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Resourcerer_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Resourcerer_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Resourcerer_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Resourcerer_1.38.0.tgz vignettes: vignettes/Resourcerer/inst/doc/Resourcerer.pdf vignetteTitles: Resourcerer Resourcerer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Resourcerer/inst/doc/Resourcerer.R Package: rfPred Version: 1.2.0 Depends: Rsamtools, GenomicRanges, IRanges, data.table, methods, parallel Suggests: BiocStyle License: GPL (>=2 ) Archs: i386, x64 MD5sum: 4374eedf7ad41dc1f0e9f08cbf92255d NeedsCompilation: yes Title: Assign rfPred functional prediction scores to a missense variants list Description: Based on external numerous data files where rfPred scores are pre-calculated on all genomic positions of the human exome, the package gives rfPred scores to missense variants identified by the chromosome, the position (hg19 version), the referent and alternative nucleotids and the uniprot identifier of the protein. Note that for using the package, the user has to be connected on the Internet or to download the TabixFile and index (approximately 3.3 Go). biocViews: Software, Homo-sapiens, Annotation, Classification Author: Fabienne Jabot-Hanin, Hugo Varet and Jean-Philippe Jais Maintainer: Hugo Varet URL: http://www.sbim.fr/rfPred source.ver: src/contrib/rfPred_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rfPred_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rfPred_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rfPred_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rfPred_1.2.0.tgz vignettes: vignettes/rfPred/inst/doc/vignette.pdf vignetteTitles: CalculatingrfPredscoreswithpackagerfPred hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rfPred/inst/doc/vignette.R Package: rGADEM Version: 2.12.0 Depends: R (>= 2.11.0), Biostrings, IRanges, BSgenome, methods, seqLogo Imports: Biostrings, IRanges, methods, graphics, seqLogo Suggests: BSgenome.Hsapiens.UCSC.hg18 License: Artistic-2.0 Archs: i386, x64 MD5sum: 4a9468700dfe896dd3cf1a3b760b7a6b NeedsCompilation: yes Title: de novo motif discovery Description: rGADEM is an efficient de novo motif discovery tool for large-scale genomic sequence data. It is an open-source R package, which is based on the GADEM software. biocViews: Microarray, ChIPchip, Sequencing, ChIPSeq, GenomicSequence, MotifDiscovery Author: Arnaud Droit, Raphael Gottardo, Gordon Robertson and Leiping Li Maintainer: Arnaud Droit source.ver: src/contrib/rGADEM_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rGADEM_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rGADEM_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rGADEM_2.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rGADEM_2.12.0.tgz vignettes: vignettes/rGADEM/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rGADEM/inst/doc/rGADEM.R importsMe: MotIV Package: RGalaxy Version: 1.8.1 Depends: XML, methods, tools, optparse, digest, Imports: BiocGenerics, Biobase, roxygen2 Suggests: RUnit, hgu95av2.db, knitr, formatR, Rserve Enhances: RSclient License: Artistic-2.0 MD5sum: 42c20d72e25098da5d1b1b046fc1998c NeedsCompilation: no Title: Make an R function available in the Galaxy web platform Description: Given an R function and its manual page, make the documented function available in Galaxy. biocViews: Infrastructure Author: Dan Tenenbaum Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/RGalaxy_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/RGalaxy_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/RGalaxy_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/RGalaxy_1.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RGalaxy_1.8.1.tgz vignettes: vignettes/RGalaxy/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RGalaxy/inst/doc/RGalaxy-vignette.R htmlDocs: vignettes/RGalaxy/inst/doc/RGalaxy-vignette.html htmlTitles: "Introduction to RGalaxy" Package: Rgraphviz Version: 2.8.1 Depends: R (>= 2.6.0), methods, utils, graph, grid Imports: stats4, graphics, grDevices Suggests: RUnit, BiocGenerics, XML License: EPL Archs: i386, x64 MD5sum: 37ddbd4d31e4203d6124288647f8cadb NeedsCompilation: yes Title: Provides plotting capabilities for R graph objects Description: Interfaces R with the AT and T graphviz library for plotting R graph objects from the graph package. biocViews: GraphAndNetwork, Visualization Author: Kasper Daniel Hansen [cre, aut], Jeff Gentry [aut], Li Long [aut], Robert Gentleman [aut], Seth Falcon [aut], Florian Hahne [aut], Deepayan Sarkar [aut] Maintainer: Kasper Daniel Hansen SystemRequirements: optionally Graphviz (>= 2.16) source.ver: src/contrib/Rgraphviz_2.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rgraphviz_2.8.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Rgraphviz_2.8.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Rgraphviz_2.8.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rgraphviz_2.8.1.tgz vignettes: vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.pdf, vignettes/Rgraphviz/inst/doc/Rgraphviz.pdf vignetteTitles: A New Interface to Plot Graphs Using Rgraphviz, How To Plot A Graph Using Rgraphviz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.R, vignettes/Rgraphviz/inst/doc/Rgraphviz.R dependsOnMe: biocGraph, BioMVCClass, CellNOptR, flowCL, gaucho, GOFunction, MineICA, nem, netresponse, paircompviz, pathRender, ROntoTools, SplicingGraphs, TDARACNE importsMe: apComplex, biocGraph, CompGO, DEGraph, GOFunction, hyperdraw, nem, paircompviz, pathview, qpgraph, RchyOptimyx, SplicingGraphs suggestsMe: altcdfenvs, annotate, BiocCaseStudies, Category, CNORfeeder, CNORfuzzy, ddgraph, DEGraph, flowCore, GeneNetworkBuilder, geneplotter, GlobalAncova, globaltest, GOstats, GSEABase, KEGGgraph, MLP, NCIgraph, oneChannelGUI, pcaGoPromoter, pkgDepTools, RBGL, RBioinf, rBiopaxParser, RDAVIDWebService, Rtreemix, safe, SPIA, SRAdb, Streamer, topGO, vtpnet Package: rhdf5 Version: 2.8.0 Depends: methods Imports: zlibbioc Suggests: bit64,BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: 33767e9a4bb07c1de12776c3590c3777 NeedsCompilation: yes Title: HDF5 interface to R Description: This R/Bioconductor package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM. biocViews: Infrastructure, DataImport Author: Bernd Fischer, Gregoire Pau Maintainer: Bernd Fischer SystemRequirements: GNU make source.ver: src/contrib/rhdf5_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rhdf5_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rhdf5_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rhdf5_2.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rhdf5_2.8.0.tgz vignettes: vignettes/rhdf5/inst/doc/rhdf5.pdf vignetteTitles: rhdf5 hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rhdf5/inst/doc/rhdf5.R dependsOnMe: GENE.E, GSCA importsMe: GENE.E, h5vc Package: rHVDM Version: 1.30.0 Depends: R (>= 2.10), R2HTML (>= 1.5), affy (>= 1.23.4), minpack.lm (>= 1.0-5), Biobase (>= 2.5.5) License: GPL-2 MD5sum: eada13f56ec8b4f9dd0fa2200299e916 NeedsCompilation: no Title: Hidden Variable Dynamic Modeling Description: A R implementation of HVDM (Genome Biol 2006, V7(3) R25) biocViews: Microarray, GraphAndNetwork, Transcription, Classification, NetworkInference Author: Martino Barenco Maintainer: Martino Barenco source.ver: src/contrib/rHVDM_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rHVDM_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rHVDM_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rHVDM_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rHVDM_1.30.0.tgz vignettes: vignettes/rHVDM/inst/doc/rHVDM.pdf vignetteTitles: rHVDM primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rHVDM/inst/doc/rHVDM.R Package: Ringo Version: 1.28.0 Depends: methods, Biobase (>= 1.14.1), RColorBrewer, limma, Matrix, grid, lattice Imports: BiocGenerics (>= 0.1.11), genefilter, limma, vsn, stats4 Suggests: rtracklayer (>= 1.3.1), mclust, topGO (>= 1.15.0) License: Artistic-2.0 Archs: i386, x64 MD5sum: ec5c8731b5ab79a2353acb62d7e96299 NeedsCompilation: yes Title: R Investigation of ChIP-chip Oligoarrays Description: The package Ringo facilitates the primary analysis of ChIP-chip data. The main functionalities of the package are data read-in, quality assessment, data visualisation and identification of genomic regions showing enrichment in ChIP-chip. The package has functions to deal with two-color oligonucleotide microarrays from NimbleGen used in ChIP-chip projects, but also contains more general functions for ChIP-chip data analysis, given that the data is supplied as RGList (raw) or ExpressionSet (pre- processed). The package employs functions from various other packages of the Bioconductor project and provides additional ChIP-chip-specific and NimbleGen-specific functionalities. biocViews: Microarray,TwoChannel,DataImport,QualityControl,Preprocessing Author: Joern Toedling, Oleg Sklyar, Tammo Krueger, Matt Ritchie, Wolfgang Huber Maintainer: J. Toedling source.ver: src/contrib/Ringo_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Ringo_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Ringo_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Ringo_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Ringo_1.28.0.tgz vignettes: vignettes/Ringo/inst/doc/Ringo.pdf vignetteTitles: R Investigation of NimbleGen Oligoarrays hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Ringo/inst/doc/Ringo.R dependsOnMe: SimBindProfiles, Starr importsMe: Repitools Package: RIPSeeker Version: 1.4.0 Depends: R (>= 2.15), methods, IRanges, GenomicRanges, Rsamtools, GenomicAlignments, rtracklayer Suggests: biomaRt, ChIPpeakAnno, parallel, GenomicFeatures License: GPL-2 MD5sum: 3943c4528b51e44105e43f882a15a781 NeedsCompilation: no Title: RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments Description: Infer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation. biocViews: Sequencing, RIPSeq Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/software.html source.ver: src/contrib/RIPSeeker_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RIPSeeker_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RIPSeeker_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RIPSeeker_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RIPSeeker_1.4.0.tgz vignettes: vignettes/RIPSeeker/inst/doc/RIPSeeker.pdf vignetteTitles: RIPSeeker: a statistical package for identifying protein-associated transcripts from RIP-seq experiments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RIPSeeker/inst/doc/RIPSeeker.R Package: Risa Version: 1.6.0 Depends: R (>= 2.0.9), Biobase (>= 2.4.0), methods, Rcpp (>= 0.9.13), biocViews, affy Imports: xcms Suggests: faahKO (>= 1.2.11) License: LGPL MD5sum: ad9afaa4f4eee9470a21e406df122ec5 NeedsCompilation: no Title: Converting experimental metadata from ISA-tab into Bioconductor data structures Description: The Investigation / Study / Assay (ISA) tab-delimited format is a general purpose framework with which to collect and communicate complex metadata (i.e. sample characteristics, technologies used, type of measurements made) from experiments employing a combination of technologies, spanning from traditional approaches to high-throughput techniques. Risa allows to access metadata/data in ISA-Tab format and build Bioconductor data structures. Currently, data generated from microarray, flow cytometry and metabolomics-based (i.e. mass spectrometry) assays are supported. The package is extendable and efforts are undergoing to support metadata associated to proteomics assays. biocViews: Annotation, DataImport, MassSpectrometry Author: Alejandra Gonzalez-Beltran, Audrey Kauffmann, Steffen Neumann, Gabriella Rustici, ISA Team Maintainer: Alejandra Gonzalez-Beltran, ISA Team URL: http://isatab.sourceforge.net/ source.ver: src/contrib/Risa_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Risa_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Risa_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Risa_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Risa_1.6.0.tgz vignettes: vignettes/Risa/inst/doc/Risa.pdf vignetteTitles: Risa: converts experimental metadata from ISA-tab into Bioconductor data structures hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Risa/inst/doc/Risa.R Package: RLMM Version: 1.26.0 Depends: R (>= 2.1.0) Imports: graphics, grDevices, MASS, stats, utils License: LGPL (>= 2) MD5sum: 8b1a3041c8b8af45dd41c8720ba7c26d NeedsCompilation: no Title: A Genotype Calling Algorithm for Affymetrix SNP Arrays Description: A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now. biocViews: Microarray, OneChannel, SNP, GeneticVariability Author: Nusrat Rabbee , Gary Wong Maintainer: Nusrat Rabbee URL: http://www.stat.berkeley.edu/users/nrabbee/RLMM SystemRequirements: Internal files Xba.CQV, Xba.regions (or other regions file) source.ver: src/contrib/RLMM_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RLMM_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RLMM_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RLMM_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RLMM_1.26.0.tgz vignettes: vignettes/RLMM/inst/doc/RLMM.pdf vignetteTitles: RLMM Doc hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RLMM/inst/doc/RLMM.R Package: Rmagpie Version: 1.20.0 Depends: R (>= 2.6.1), Biobase (>= 2.5.5) Imports: Biobase (>= 2.5.5), e1071, graphics, grDevices, kernlab, methods, pamr, stats, utils Suggests: xtable License: GPL (>= 3) MD5sum: 809356723910e63f94c7ca9644273d58 NeedsCompilation: no Title: MicroArray Gene-expression-based Program In Error rate estimation Description: Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes. biocViews: Microarray, Classification Author: Camille Maumet , with contributions from C. Ambroise J. Zhu Maintainer: Camille Maumet URL: http://www.bioconductor.org/ source.ver: src/contrib/Rmagpie_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rmagpie_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rmagpie_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rmagpie_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rmagpie_1.20.0.tgz vignettes: vignettes/Rmagpie/inst/doc/Magpie_examples.pdf vignetteTitles: Rmagpie Examples hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rmagpie/inst/doc/Magpie_examples.R Package: RMAPPER Version: 1.14.0 Depends: methods Suggests: RCurl License: Artistic 2.0 MD5sum: 3edbccdfec39be5776bc250df4cc9433 NeedsCompilation: no Title: R interface to the MAPPER database of transcription factor binding sites Description: The RMAPPER package allows you to retrieve a set of predicted transcription factor binding sites from the MAPPER database (http://genome.ufl.edu/mapper/) through a simple HTTP request. biocViews: Annotation, Genetics Author: VJ Carey Maintainer: Heike Sichtig , Alberto Riva source.ver: src/contrib/RMAPPER_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RMAPPER_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RMAPPER_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RMAPPER_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RMAPPER_1.14.0.tgz vignettes: vignettes/RMAPPER/inst/doc/readMAPPER.pdf vignetteTitles: Interface to MAPPER TFBS database hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RMAPPER/inst/doc/readMAPPER.R Package: RMassBank Version: 1.6.0 Depends: Rcpp Imports: XML,RCurl,rjson, rcdk,yaml,mzR,methods Suggests: gplots,RMassBankData, xcms (>= 1.37.1), CAMERA, ontoCAT, RUnit License: Artistic-2.0 MD5sum: 9846557740513ea7c41c0c15111b7ff3 NeedsCompilation: no Title: Workflow to process tandem MS files and build MassBank records Description: Workflow to process tandem MS files and build MassBank records. Functions include automated extraction of tandem MS spectra, formula assignment to tandem MS fragments, recalibration of tandem MS spectra with assigned fragments, spectrum cleanup, automated retrieval of compound information from Internet databases, and export to MassBank records. biocViews: Bioinformatics, MassSpectrometry, Metabolomics, Software Author: Michael Stravs, Emma Schymanski, Steffen Neumann, Erik Mueller, with contributions from Tobias Schulze Maintainer: RMassBank at Eawag SystemRequirements: OpenBabel source.ver: src/contrib/RMassBank_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RMassBank_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RMassBank_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RMassBank_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RMassBank_1.6.0.tgz vignettes: vignettes/RMassBank/inst/doc/RMassBankNonstandard.pdf, vignettes/RMassBank/inst/doc/RMassBank.pdf, vignettes/RMassBank/inst/doc/RMassBankXCMS.pdf vignetteTitles: RMassBank non-standard usage, RMassBank walkthrough, RMassBank using XCMS walkthrough hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RMassBank/inst/doc/RMassBankNonstandard.R, vignettes/RMassBank/inst/doc/RMassBank.R, vignettes/RMassBank/inst/doc/RMassBankXCMS.R Package: rMAT Version: 3.14.0 Depends: R(>= 2.9.0), BiocGenerics (>= 0.1.3), IRanges (>= 1.13.10), Biobase (>= 2.15.1), affxparser Imports: stats, methods, BiocGenerics, IRanges, Biobase, affxparser, stats4 Suggests: GenomeGraphs, rtracklayer License: Artistic-2.0 MD5sum: 13a9b4e1d5a13e1c45ed1b52add24db5 NeedsCompilation: yes Title: R implementation from MAT program to normalize and analyze tiling arrays and ChIP-chip data. Description: This package is an R version of the package MAT and contains functions to parse and merge Affymetrix BPMAP and CEL tiling array files (using C++ based Fusion SDK and Bioconductor package affxparser), normalize tiling arrays using sequence specific models, detect enriched regions from ChIP-chip experiments. Note: users should have GSL and GenomeGraphs installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. Snow Leopard users can take advantage of increase speed with Grand Central Dispatch! biocViews: Microarray, Preprocessing Author: Charles Cheung and Arnaud Droit and Raphael Gottardo Maintainer: Arnaud Droit and Raphael Gottardo URL: http://www.rglab.org source.ver: src/contrib/rMAT_3.14.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/rMAT_3.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rMAT_3.14.0.tgz vignettes: vignettes/rMAT/inst/doc/rMAT.pdf vignetteTitles: The rMAT users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rMAT/inst/doc/rMAT.R Package: RmiR Version: 1.20.0 Depends: R (>= 2.7.0), RmiR.Hs.miRNA, RSVGTipsDevice Imports: DBI, methods, stats Suggests: hgug4112a.db,org.Hs.eg.db License: Artistic-2.0 MD5sum: 8f8df136d1282c00019ed898c0504b1d NeedsCompilation: no Title: Package to work with miRNAs and miRNA targets with R Description: Useful functions to merge microRNA and respective targets using differents databases biocViews: Software,GeneExpression,Microarray,TimeCourse,Visualization Author: Francesco Favero Maintainer: Francesco Favero source.ver: src/contrib/RmiR_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RmiR_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RmiR_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RmiR_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RmiR_1.20.0.tgz vignettes: vignettes/RmiR/inst/doc/RmiR.pdf vignetteTitles: RmiR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RmiR/inst/doc/RmiR.R suggestsMe: oneChannelGUI Package: RNAinteract Version: 1.12.0 Depends: R (>= 2.12.0), abind, locfit, Biobase Imports: RColorBrewer, ICS, ICSNP, cellHTS2, geneplotter, gplots, grid, hwriter, lattice, latticeExtra, limma, methods, splots (>= 1.13.12) License: Artistic-2.0 MD5sum: 4dce0bdeae427bf7537f38f1941d69a6 NeedsCompilation: no Title: Estimate Pairwise Interactions from multidimensional features Description: RNAinteract estimates genetic interactions from multi-dimensional read-outs like features extracted from images. The screen is assumed to be performed in multi-well plates or similar designs. Starting from a list of features (e.g. cell number, area, fluorescence intensity) per well, genetic interactions are estimated. The packages provides functions for reporting interacting gene pairs, plotting heatmaps and double RNAi plots. An HTML report can be written for quality control and analysis. biocViews: CellBasedAssays, QualityControl, Preprocessing, Visualization Author: Bernd Fischer Maintainer: Bernd Fischer source.ver: src/contrib/RNAinteract_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RNAinteract_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RNAinteract_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RNAinteract_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RNAinteract_1.12.0.tgz vignettes: vignettes/RNAinteract/inst/doc/RNAinteract.pdf vignetteTitles: RNAinteract hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNAinteract/inst/doc/RNAinteract.R Package: RNAither Version: 2.12.0 Depends: R (>= 2.10), topGO, RankProd, prada Imports: geneplotter, limma, biomaRt, car, splots, methods License: Artistic-2.0 MD5sum: 42b486bc6608bf3b33d10273473aa487 NeedsCompilation: no Title: Statistical analysis of high-throughput RNAi screens Description: RNAither analyzes cell-based RNAi screens, and includes quality assessment, customizable normalization and statistical tests, leading to lists of significant genes and biological processes. biocViews: CellBasedAssays, QualityControl, Preprocessing, Visualization, Annotation, GO Author: Nora Rieber and Lars Kaderali, University of Heidelberg, Viroquant Research Group Modeling, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Maintainer: Nora Rieber source.ver: src/contrib/RNAither_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RNAither_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RNAither_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RNAither_2.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RNAither_2.12.0.tgz vignettes: vignettes/RNAither/inst/doc/vignetteRNAither.pdf vignetteTitles: RNAither,, an automated pipeline for the statistical analysis of high-throughput RNAi screens hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNAither/inst/doc/vignetteRNAither.R Package: rnaSeqMap Version: 2.20.0 Depends: R (>= 2.11.0), methods, Biobase, Rsamtools, GenomicAlignments Imports: GenomicRanges , IRanges, edgeR, DESeq, DBI License: GPL-2 Archs: i386, x64 MD5sum: 77ef6bc050c7bfd1a77c5207d6f3b346 NeedsCompilation: yes Title: rnaSeq secondary analyses Description: The rnaSeqMap library provides classes and functions to analyze the RNA-sequencing data using the coverage profiles in multiple samples at a time biocViews: Annotation, ReportWriting, Transcription, GeneExpression, DifferentialExpression, Sequencing, RNASeq, SAGE, Visualization Author: Anna Lesniewska ; Michal Okoniewski Maintainer: Michal Okoniewski source.ver: src/contrib/rnaSeqMap_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rnaSeqMap_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rnaSeqMap_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rnaSeqMap_2.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rnaSeqMap_2.20.0.tgz vignettes: vignettes/rnaSeqMap/inst/doc/rnaSeqMap.pdf vignetteTitles: rnaSeqMap primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rnaSeqMap/inst/doc/rnaSeqMap.R dependsOnMe: ampliQueso Package: RNASeqPower Version: 1.4.0 License: LGPL (>=2) MD5sum: 80afff847658fae7a3a030f0c9df2b7b NeedsCompilation: no Title: Sample size for RNAseq studies Description: RNA-seq, sample size biocViews: RNASeq Author: Terry M Therneau [aut, cre], Hart Stephen [ctb] Maintainer: Terry M Therneau source.ver: src/contrib/RNASeqPower_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RNASeqPower_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RNASeqPower_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RNASeqPower_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RNASeqPower_1.4.0.tgz vignettes: vignettes/RNASeqPower/inst/doc/samplesize.pdf vignetteTitles: RNAseq samplesize hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RNASeqPower/inst/doc/samplesize.R Package: roar Version: 1.0.0 Depends: R (>= 3.0.1) Imports: GenomicRanges, GenomicAlignments(>= 0.99.4), methods, rtracklayer, IRanges Suggests: RUnit, BiocGenerics, RNAseqData.HNRNPC.bam.chr14 License: GPL-3 MD5sum: af6bfdf2e438952baad06c0409bc406d NeedsCompilation: no Title: Identify differential APA usage from RNA-seq alignments Description: Identify preferential usage of APA sites, comparing two biological conditions, starting from known alternative sites and alignments obtained from standard RNA-seq experiments. biocViews: Sequencing, RNASeq, Transcription Author: Elena Grassi Maintainer: Elena Grassi source.ver: src/contrib/roar_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/roar_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/roar_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/roar_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/roar_1.0.0.tgz vignettes: vignettes/roar/inst/doc/roar.pdf vignetteTitles: Identify differential APA usage from RNA-seq alignments hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/roar/inst/doc/roar.R Package: ROC Version: 1.40.0 Depends: R (>= 1.9.0), utils, methods Suggests: Biobase License: Artistic-2.0 Archs: i386, x64 MD5sum: edde9a3f4e5a07275f389885283007c7 NeedsCompilation: yes Title: utilities for ROC, with uarray focus Description: utilities for ROC, with uarray focus biocViews: DifferentialExpression Author: Vince Carey , Henning Redestig for C++ language enhancements Maintainer: Vince Carey URL: http://www.bioconductor.org source.ver: src/contrib/ROC_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ROC_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ROC_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ROC_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ROC_1.40.0.tgz vignettes: vignettes/ROC/inst/doc/ROCnotes.pdf vignetteTitles: ROC notes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ROC/inst/doc/ROCnotes.R dependsOnMe: TCC, wateRmelon importsMe: clst suggestsMe: genefilter, MCRestimate Package: Roleswitch Version: 1.2.0 Depends: R (>= 2.10), pracma, reshape, plotrix, microRNA, biomaRt, Biostrings, Biobase, DBI Suggests: ggplot2 License: GPL-2 MD5sum: 394e3ba868a3be18c7214a45ceb24ddc NeedsCompilation: no Title: Infer miRNA-mRNA interactions using paired expression data from a single sample Description: Infer Probabilities of MiRNA-mRNA Interaction Signature (ProMISe) using paired expression data from a single sample. Roleswitch operates in two phases by inferring the probability of mRNA (miRNA) being the targets ("targets") of miRNA (mRNA), taking into account the expression of all of the mRNAs (miRNAs) due to their potential competition for the same miRNA (mRNA). Due to dynamic miRNA repression in the cell, Roleswitch assumes that the total transcribed mRNA levels are higher than the observed (equilibrium) mRNA levels and iteratively updates the total transcription of each mRNA targets based on the above inference. NB: in the paper, we used ProMISe as both the model name and inferred score name. biocViews: miRNA Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/roleswitch.html source.ver: src/contrib/Roleswitch_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Roleswitch_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Roleswitch_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Roleswitch_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Roleswitch_1.2.0.tgz vignettes: vignettes/Roleswitch/inst/doc/Roleswitch.pdf vignetteTitles: Roleswitch hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Roleswitch/inst/doc/Roleswitch.R Package: Rolexa Version: 1.20.0 Depends: R (>= 2.9.0), graphics, grDevices, methods, ShortRead Imports: mclust, Biostrings, graphics, grDevices, IRanges, methods, ShortRead, stats Enhances: fork License: GPL-2 MD5sum: b97f51aa173505e3e1e674d72d5e4ac1 NeedsCompilation: no Title: Statistical analysis of Solexa sequencing data Description: Provides probabilistic base calling, quality checks and diagnostic plots for Solexa sequencing data biocViews: Sequencing, DataImport, Preprocessing, QualityControl Author: Jacques Rougemont, Arnaud Amzallag, Christian Iseli, Laurent Farinelli, Ioannis Xenarios, Felix Naef Maintainer: Jacques Rougemont source.ver: src/contrib/Rolexa_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rolexa_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rolexa_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rolexa_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rolexa_1.20.0.tgz vignettes: vignettes/Rolexa/inst/doc/Rolexa-vignette.pdf vignetteTitles: Rolexa hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rolexa/inst/doc/Rolexa-vignette.R Package: rols Version: 1.6.1 Depends: methods Imports: XML, XMLSchema (>= 0.6.0), SSOAP (>= 0.8.0), Biobase Suggests: xtable, GO.db, knitr (>= 1.1.0), BiocStyle License: GPL-2 MD5sum: 8262fcdb4f9bc6678a481b06d59f58a2 NeedsCompilation: no Title: An R interface to the Ontology Lookup Service Description: This package allows to query EBI's Ontology Lookup Service (OLS) using Simple Object Access Protocol (SOAP). biocViews: Software, Annotation, MassSpectrometry, GO Author: Laurent Gatto Maintainer: Laurent Gatto URL: http://lgatto.github.com/rols/ VignetteBuilder: knitr source.ver: src/contrib/rols_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/rols_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.1/rols_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.1/rols_1.6.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rols_1.6.1.tgz vignettes: vignettes/rols/inst/doc/rols.pdf vignetteTitles: The rols interface to the Ontology Lookup Service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rols/inst/doc/rols.R suggestsMe: MSnbase Package: ROntoTools Version: 1.4.0 Depends: methods, graph, boot, KEGGREST, KEGGgraph, Rgraphviz Suggests: RUnit, BiocGenerics License: GPL (>= 3) MD5sum: 20be22821c46d088ea6afcec79964119 NeedsCompilation: no Title: R Onto-Tools suite Description: Suite of tools for functional analysis biocViews: Network, Microarray, GraphAndNetwork Author: Calin Voichita and Sorin Draghici Maintainer: Calin Voichita source.ver: src/contrib/ROntoTools_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ROntoTools_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ROntoTools_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ROntoTools_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ROntoTools_1.4.0.tgz vignettes: vignettes/ROntoTools/inst/doc/rontotools.pdf vignetteTitles: ROntoTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ROntoTools/inst/doc/rontotools.R Package: RPA Version: 1.20.01 Depends: R (>= 2.15.0), affy, affydata, methods, parallel License: BSD_2_clause + file LICENSE MD5sum: 9928f480d784f3d11e46add9c37f96c0 NeedsCompilation: no Title: RPA: Robust Probabilistic Averaging for probe-level analysis Description: Probabilistic analysis of probe reliability and differential gene expression on short oligonucleotide arrays. Lahti et al. "Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays", TCBB/IEEE, 2011. http://doi.ieeecomputersociety.org/10.1109/TCBB.2009.38 biocViews: GeneExpression, Microarray, Preprocessing, QualityControl Author: Leo Lahti Maintainer: Leo Lahti source.ver: src/contrib/RPA_1.20.01.tar.gz win.binary.ver: bin/windows/contrib/3.1/RPA_1.20.01.zip win64.binary.ver: bin/windows64/contrib/3.1/RPA_1.20.01.zip mac.binary.ver: bin/macosx/contrib/3.1/RPA_1.20.01.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RPA_1.20.01.tgz vignettes: vignettes/RPA/inst/doc/RPA.pdf vignetteTitles: RPA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RPA/inst/doc/RPA.R Package: RpsiXML Version: 2.6.0 Depends: methods, annotate (>= 1.21.0), graph (>= 1.21.0), Biobase, RBGL (>= 1.17.0), XML (>= 2.4.0), hypergraph (>= 1.15.2), AnnotationDbi Suggests: org.Hs.eg.db, org.Mm.eg.db, org.Dm.eg.db, org.Rn.eg.db, org.Sc.sgd.db,hom.Hs.inp.db, hom.Mm.inp.db, hom.Dm.inp.db, hom.Rn.inp.db, hom.Sc.inp.db,Rgraphviz, ppiStats, ScISI License: LGPL-3 MD5sum: 4eed4f01d66445ba522e96611667b20f NeedsCompilation: no Title: R interface to PSI-MI 2.5 files Description: Queries, data structure and interface to visualization of interaction datasets. This package inplements the PSI-MI 2.5 standard and supports up to now 8 databases. Further databases supporting PSI-MI 2.5 standard will be added continuously. biocViews: Infrastructure, Proteomics Author: Jitao David Zhang, Stefan Wiemann, Marc Carlson, with contributions from Tony Chiang Maintainer: Jitao David Zhang URL: http://www.bioconductor.org source.ver: src/contrib/RpsiXML_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RpsiXML_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RpsiXML_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RpsiXML_2.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RpsiXML_2.6.0.tgz vignettes: vignettes/RpsiXML/inst/doc/RpsiXMLApp.pdf, vignettes/RpsiXML/inst/doc/RpsiXML.pdf vignetteTitles: Application Examples of RpsiXML package, Reading PSI-25 XML files hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RpsiXML/inst/doc/RpsiXMLApp.R, vignettes/RpsiXML/inst/doc/RpsiXML.R dependsOnMe: ScISI importsMe: ScISI Package: rpx Version: 1.0.1 Depends: methods Imports: XML, RCurl, utils Suggests: MSnbase, Biostrings, BiocStyle, BiocGenerics, RUnit, knitr License: GPL-2 MD5sum: 6dddad3476162756cf20dc163a3bebd9 NeedsCompilation: no Title: R Interface to the ProteomeXchange Repository Description: This package implements an interface to proteomics data submitted to the ProteomeXchange consortium. biocViews: Proteomics, MassSpectrometry, DataImport, ThirdPartyClient Author: Laurent Gatto Maintainer: Laurent Gatto VignetteBuilder: knitr source.ver: src/contrib/rpx_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/rpx_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/rpx_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/rpx_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rpx_1.0.1.tgz vignettes: vignettes/rpx/inst/doc/rpx.pdf vignetteTitles: An interface to proteomics data repositories hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rpx/inst/doc/rpx.R Package: rqubic Version: 1.10.0 Depends: methods, Biobase, biclust Imports: Biobase, biclust Suggests: RColorBrewer License: GPL-2 Archs: i386, x64 MD5sum: 5dba51e190b10fd86af817dadcbe52cf NeedsCompilation: yes Title: Qualitative biclustering algorithm for expression data analysis in R Description: This package implements the QUBIC algorithm introduced by Li et al. for the qualitative biclustering with gene expression data. biocViews: Microarray, Clustering Author: Jitao David Zhang, with inputs from Laura Badi and Martin Ebeling Maintainer: Jitao David Zhang source.ver: src/contrib/rqubic_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rqubic_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rqubic_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rqubic_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rqubic_1.10.0.tgz vignettes: vignettes/rqubic/inst/doc/rqubic.pdf vignetteTitles: Qualitative Biclustering with Bioconductor Package rqubic hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rqubic/inst/doc/rqubic.R Package: RRHO Version: 1.2.0 Depends: VennDiagram, grid License: GPL-2 MD5sum: 36e3cf7a04952673b3620ddc7a4a8b7b NeedsCompilation: no Title: Inference on agreement between two lists Description: The package is aimed at inference on the amount of agreement in two sorted lists using the Rank-Rank Hypergeometric Overlap test. biocViews: Genetics, SequenceMatching, Microarray, Transcription Author: Jonathan Rosenblatt and Jason Stein Maintainer: Jonathan Rosenblatt source.ver: src/contrib/RRHO_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RRHO_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RRHO_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RRHO_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RRHO_1.2.0.tgz vignettes: vignettes/RRHO/inst/doc/RRHO.pdf vignetteTitles: RRHO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RRHO/inst/doc/RRHO.R Package: Rsamtools Version: 1.16.1 Depends: methods, IRanges (>= 1.21.10), GenomicRanges (>= 1.15.11), XVector (>= 0.3.2), Biostrings (>= 2.31.3), GenomeInfoDb(>= 0.99.17) Imports: utils, BiocGenerics (>= 0.1.3), zlibbioc, bitops LinkingTo: IRanges, XVector, Biostrings Suggests: GenomicAlignments, ShortRead (>= 1.19.10), GenomicFeatures, TxDb.Dmelanogaster.UCSC.dm3.ensGene, KEGG.db, TxDb.Hsapiens.UCSC.hg18.knownGene, RNAseqData.HNRNPC.bam.chr14, BSgenome.Hsapiens.UCSC.hg19, pasillaBamSubset, RUnit, BiocStyle License: Artistic-2.0 | file LICENSE Archs: i386, x64 MD5sum: 0876502f73b88f0c47034aefbbafc2d3 NeedsCompilation: yes Title: Binary alignment (BAM), variant call (BCF), or tabix file import Description: This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities (see 'LICENCE') for manipulating SAM (Sequence Alignment / Map), binary variant call (BCF) and compressed indexed tab-delimited (tabix) files. biocViews: DataImport, Sequencing Author: Martin Morgan, Herv\'e Pag\`es, Valerie Obenchain Maintainer: Bioconductor Package Maintainer URL: http://bioconductor.org/packages/release/bioc/html/Rsamtools.html source.ver: src/contrib/Rsamtools_1.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rsamtools_1.16.1.zip win64.binary.ver: bin/windows64/contrib/3.1/Rsamtools_1.16.1.zip mac.binary.ver: bin/macosx/contrib/3.1/Rsamtools_1.16.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rsamtools_1.16.1.tgz vignettes: vignettes/Rsamtools/inst/doc/Rsamtools-Overview.pdf, vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.pdf vignetteTitles: An introduction to Rsamtools, Using samtools C libraries hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/Rsamtools/inst/doc/Rsamtools-Overview.R, vignettes/Rsamtools/inst/doc/Rsamtools-UsingCLibraries.R dependsOnMe: ArrayExpressHTS, BitSeq, chimera, CNVrd2, deepSNV, EDASeq, exomeCopy, exomePeak, GenomicAlignments, GenomicFiles, girafe, oneChannelGUI, qrqc, Rcade, ReQON, rfPred, RIPSeeker, rnaSeqMap, ShortRead, TEQC, VariantAnnotation importsMe: AllelicImbalance, annmap, ArrayExpressHTS, biovizBase, BSgenome, CAGEr, casper, CexoR, ChIPQC, customProDB, deepSNV, DEXSeq, DNaseR, easyRNASeq, FunciSNP, GenomicAlignments, ggbio, GGtools, gmapR, Gviz, gwascat, h5vc, HTSeqGenie, MEDIPS, PICS, QDNAseq, QuasR, R453Plus1Toolbox, Rariant, Repitools, rtracklayer, trackViewer, VariantFiltering, VariantTools suggestsMe: AnnotationHub, BaseSpaceR, biomvRCNS, DESeq2, DiffBind, gage, GenomicFeatures, GenomicRanges, metaseqR, QuasR, seqbias, SigFuge, SplicingGraphs, Streamer Package: rsbml Version: 2.22.2 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), methods, utils Imports: BiocGenerics, graph, utils License: Artistic-2.0 Archs: i386, x64 MD5sum: 9efc4f012e347edfbbc9d90db5a3d062 NeedsCompilation: yes Title: R support for SBML, using libsbml Description: Links R to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects. Optionally links to the SBML ODE Solver Library (SOSLib) for simulating models. biocViews: GraphAndNetwork, Pathways, Network Author: Michael Lawrence Maintainer: Michael Lawrence URL: http://www.sbml.org SystemRequirements: libsbml (>=3.0.3) source.ver: src/contrib/rsbml_2.22.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/rsbml_2.22.2.zip win64.binary.ver: bin/windows64/contrib/3.1/rsbml_2.22.2.zip mac.binary.ver: bin/macosx/contrib/3.1/rsbml_2.22.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rsbml_2.22.2.tgz vignettes: vignettes/rsbml/inst/doc/quick-start.pdf vignetteTitles: Quick start for rsbml hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rsbml/inst/doc/quick-start.R dependsOnMe: BiGGR suggestsMe: piano, SBMLR Package: rSFFreader Version: 0.12.0 Depends: R (>= 2.13.0), BiocGenerics, IRanges (>= 1.21.10), XVector (>= 0.3.2), Biostrings (>= 2.31.3), GenomicRanges, ShortRead (>= 1.15.9), xtable, methods Imports: methods, IRanges, XVector, Biostrings, ShortRead, GenomicRanges, Biobase LinkingTo: IRanges, XVector, Biostrings License: Artistic-2.0 MD5sum: 1355df53257a50d8032c11605c623657 NeedsCompilation: yes Title: rSFFreader reads in sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers Description: rSFFreader reads sequence, qualities and clip point values from sff files generated by Roche 454 and Life Sciences Ion Torrent sequencers. The plan is to also write out sff files and to read in flowgrams with some utils biocViews: DataImport, Sequencing Author: Matt Settles , Sam Hunter, Brice Sarver, Ilia Zhbannikov, Kyu-Chul Cho Maintainer: Matt Settles source.ver: src/contrib/rSFFreader_0.12.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/rSFFreader_0.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rSFFreader_0.12.0.tgz vignettes: vignettes/rSFFreader/inst/doc/rSFFreader.pdf vignetteTitles: An introduction to rSFFreader hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rSFFreader/inst/doc/rSFFreader.R Package: Rsubread Version: 1.14.2 License: GPL-3 MD5sum: 6fcf162be4edbdc96d36fd18ff95af29 NeedsCompilation: yes Title: Rsubread package: high-performance read alignment, quantification and mutation discovery Description: This R package provides powerful and easy-to-use tools for analyzing next-gen sequencing read data. Functions of this package include quality assessment of sequence reads, read alignment, read summarization, exon-exon junction detection, fusion detection, detection of short and long indels, absolute expression calling and SNP calling. This package can be used to anlayze data generated from all major sequencing platforms such as Illumina GA/HiSeq/MiSeq, Roche GS-FLX, ABI SOLiD and LifeTech Ion PGM/Proton sequencers. It supports multiple operating systems incluidng Linux, Mac OS X, FreeBSD and Solaris. biocViews: Sequencing, Alignment, SequenceMatching, RNASeq, ChIPSeq, GeneExpression, GeneRegulation, Genetics, SNP, GeneticVariability, Preprocessing, QualityControl, GenomeAnnotation, Software Author: Wei Shi and Yang Liao with contributions from Jenny Zhiyin Dai and Timothy Triche, Jr. Maintainer: Wei Shi URL: http://bioconductor.org/packages/release/bioc/html/Rsubread.html source.ver: src/contrib/Rsubread_1.14.2.tar.gz mac.binary.ver: bin/macosx/contrib/3.1/Rsubread_1.14.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rsubread_1.14.2.tgz vignettes: vignettes/Rsubread/inst/doc/Rsubread.pdf vignetteTitles: Rsubread Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rsubread/inst/doc/Rsubread.R Package: RSVSim Version: 1.4.0 Depends: R (>= 3.0.0), Biostrings, GenomicRanges Imports: methods, IRanges, ShortRead Suggests: BSgenome.Hsapiens.UCSC.hg19, MASS, rtracklayer License: LGPL-3 MD5sum: a7d44a71abd347ddd523fb62ca8274cf NeedsCompilation: no Title: RSVSim: an R/Bioconductor package for the simulation of structural variations Description: RSVSim is a package for the simulation of deletions, insertions, inversion, tandem-duplications and translocations of various sizes in any genome available as FASTA-file or BSgenome data package. SV breakpoints can be placed uniformly accross the whole genome, with a bias towards repeat regions and regions of high homology (for hg19) or at user-supplied coordinates. biocViews: Sequencing Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RSVSim_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RSVSim_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RSVSim_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RSVSim_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RSVSim_1.4.0.tgz vignettes: vignettes/RSVSim/inst/doc/vignette.pdf vignetteTitles: RSVSim: an R/Bioconductor package for the simulation of structural variations hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RSVSim/inst/doc/vignette.R Package: rTANDEM Version: 1.4.0 Depends: XML, Rcpp, data.table (>= 1.8.8) Imports: methods LinkingTo: Rcpp Suggests: biomaRt License: Artistic-1.0 | file LICENSE Archs: i386, x64 MD5sum: 63912445a0e93d380e6c2ab32fbcda8d NeedsCompilation: yes Title: Interfaces the tandem protein identification algorithm in R Description: This package interfaces the tandem protein identification algorithm in R. Identification can be launched in the X!Tandem style, by using as sole parameter the path to a parameter file. But rTANDEM aslo provides extended syntax and functions to streamline launching analyses, as well as function to convert results, parameters and taxonomy to/from R. A related package, shinyTANDEM, provides visualization interface for result objects. biocViews: MassSpectrometry, Proteomics Author: Frederic Fournier , Charles Joly Beauparlant , Rene Paradis , Arnaud Droit Maintainer: Frederic Fournier SystemRequirements: rTANDEM uses expat and pthread libraries. See the README file for details. source.ver: src/contrib/rTANDEM_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rTANDEM_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rTANDEM_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rTANDEM_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rTANDEM_1.4.0.tgz vignettes: vignettes/rTANDEM/inst/doc/rTANDEM.pdf vignetteTitles: The rTANDEM users guide hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/rTANDEM/inst/doc/rTANDEM.R dependsOnMe: shinyTANDEM Package: RTCA Version: 1.16.0 Depends: methods,stats,graphics,Biobase,RColorBrewer, gtools Suggests: xtable License: LGPL-3 MD5sum: acc3772bf7d0fdb1b7556741001ef668 NeedsCompilation: no Title: Open-source toolkit to analyse data from xCELLigence System (RTCA) Description: Import, analyze and visualize data from Roche(R) xCELLigence RTCA systems. The package imports real-time cell electrical impedance data into R. As an alternative to commercial software shipped along the system, the Bioconductor package RTCA provides several unique transformation (normalization) strategies and various visualization tools. biocViews: CellBasedAssays, Infrastructure, Visualization, TimeCourse Author: Jitao David Zhang Maintainer: Jitao David Zhang URL: http://code.google.com/p/xcelligence/,http://www.xcelligence.roche.com/,http://www.nextbiomotif.com/Home/scientific-programming source.ver: src/contrib/RTCA_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RTCA_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RTCA_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RTCA_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RTCA_1.16.0.tgz vignettes: vignettes/RTCA/inst/doc/aboutRTCA.pdf, vignettes/RTCA/inst/doc/RTCAtransformation.pdf vignetteTitles: Introduction to Data Analysis of the Roche xCELLigence System with RTCA Package, RTCAtransformation: Discussion of transformation methods of RTCA data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RTCA/inst/doc/aboutRTCA.R, vignettes/RTCA/inst/doc/RTCAtransformation.R Package: RTN Version: 1.2.7 Depends: R (>= 2.15), methods, igraph Imports: RedeR, minet, snow, limma, data.table, ff, car, IRanges Suggests: HTSanalyzeR, RUnit, BiocGenerics License: Artistic-2.0 MD5sum: ef69c859338b7a0e7a0556f38af5a40b NeedsCompilation: no Title: Reconstruction of transcriptional networks and analysis of master regulators Description: This package provides classes and methods for transcriptional network inference and analysis. Modulators of transcription factor activity are assessed by conditional mutual information, and master regulators are mapped to phenotypes using different strategies, e.g., gene set enrichment, shadow and synergy analyses. Additionally, master regulators can be linked to genetic markers using eQTL/VSE analysis, taking advantage of the haplotype block structure mapped to the human genome in order to explore risk-associated SNPs identified in GWAS studies. biocViews: NetworkInference, NetworkAnalysis, NetworkEnrichment, GeneRegulation, GeneExpression, GraphAndNetwork, GeneSetEnrichment,GeneticVariability,SNP Author: Mauro Castro, Xin Wang, Michael Fletcher, Florian Markowetz and Kerstin Meyer Maintainer: Mauro Castro URL: http://dx.doi.org/10.1038/ncomms3464 source.ver: src/contrib/RTN_1.2.7.tar.gz win.binary.ver: bin/windows/contrib/3.1/RTN_1.2.7.zip win64.binary.ver: bin/windows64/contrib/3.1/RTN_1.2.7.zip mac.binary.ver: bin/macosx/contrib/3.1/RTN_1.2.7.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RTN_1.2.7.tgz vignettes: vignettes/RTN/inst/doc/RTN.pdf vignetteTitles: Main vignette: reconstruction and analysis of transcriptional networks in R hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RTN/inst/doc/RTN.R Package: RTopper Version: 1.10.0 Depends: R (>= 2.11.0), Biobase Imports: limma, multtest Suggests: limma, org.Hs.eg.db, KEGG.db, GO.db License: GPL (>= 3) MD5sum: fef08400d2c86359a1dfb457d5a6395f NeedsCompilation: no Title: This package is designed to perform Gene Set Analysis across multiple genomic platforms Description: the RTopper package is designed to perform and integrate gene set enrichment results across multiple genomic platforms. biocViews: Microarray Author: Luigi Marchionni , Svitlana Tyekucheva Maintainer: Luigi Marchionni source.ver: src/contrib/RTopper_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/RTopper_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/RTopper_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/RTopper_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/RTopper_1.10.0.tgz vignettes: vignettes/RTopper/inst/doc/RTopper.pdf vignetteTitles: RTopper user's manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RTopper/inst/doc/RTopper.R Package: rtracklayer Version: 1.24.2 Depends: R (>= 2.10), methods, GenomicRanges (>= 1.15.26) Imports: XML (>= 1.98-0), BiocGenerics (>= 0.7.7), IRanges (>= 1.19.34), XVector (>= 0.1.3), GenomicRanges (>= 1.15.26), Biostrings (>= 2.29.18), BSgenome (>= 1.23.1), zlibbioc, RCurl (>= 1.4-2), Rsamtools (>= 1.13.1), GenomicAlignments, tools LinkingTo: IRanges, XVector Suggests: humanStemCell, microRNA (>= 1.1.1), genefilter, limma, org.Hs.eg.db, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, hgu133plus2.db License: Artistic-2.0 Archs: i386, x64 MD5sum: 0f1f6fb8785265b84e8964eec9db95b3 NeedsCompilation: yes Title: R interface to genome browsers and their annotation tracks Description: Extensible framework for interacting with multiple genome browsers (currently UCSC built-in) and manipulating annotation tracks in various formats (currently GFF, BED, bedGraph, BED15, WIG, BigWig and 2bit built-in). The user may export/import tracks to/from the supported browsers, as well as query and modify the browser state, such as the current viewport. biocViews: Annotation,Visualization,DataImport Author: Michael Lawrence, Vince Carey, Robert Gentleman Maintainer: Michael Lawrence source.ver: src/contrib/rtracklayer_1.24.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/rtracklayer_1.24.2.zip win64.binary.ver: bin/windows64/contrib/3.1/rtracklayer_1.24.2.zip mac.binary.ver: bin/macosx/contrib/3.1/rtracklayer_1.24.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rtracklayer_1.24.2.tgz vignettes: vignettes/rtracklayer/inst/doc/rtracklayer.pdf vignetteTitles: rtracklayer hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rtracklayer/inst/doc/rtracklayer.R dependsOnMe: cummeRbund, exomePeak, GenomicFiles, MethylSeekR, RIPSeeker, spliceR importsMe: BiSeq, CAGEr, casper, CexoR, ChIPseeker, ChromHeatMap, CNEr, CompGO, customProDB, FunciSNP, GenomicFeatures, ggbio, GGtools, gmapR, GOTHiC, Gviz, gwascat, HiTC, HTSeqGenie, MEDIPS, methyAnalysis, MotifDb, roar, TFBSTools, trackViewer, VariantAnnotation, VariantTools suggestsMe: biovizBase, GenomicAlignments, GenomicRanges, goseq, interactiveDisplay, metaseqR, methylumi, MotIV, NarrowPeaks, oneChannelGUI, PICS, PING, QuasR, R453Plus1Toolbox, Repitools, Ringo, rMAT, RSVSim, triplex, TSSi Package: Rtreemix Version: 1.26.0 Depends: R (>= 2.5.0), methods, graph, Biobase Imports: methods, graph, Biobase, Hmisc Suggests: Rgraphviz License: LGPL Archs: i386, x64 MD5sum: f448d2a625dbc8d4080f30b07eecb147 NeedsCompilation: yes Title: Rtreemix: Mutagenetic trees mixture models. Description: Rtreemix is a package that offers an environment for estimating the mutagenetic trees mixture models from cross-sectional data and using them for various predictions. It includes functions for fitting the trees mixture models, likelihood computations, model comparisons, waiting time estimations, stability analysis, etc. biocViews: StatisctialMethod Author: Jasmina Bogojeska Maintainer: Jasmina Bogojeska source.ver: src/contrib/Rtreemix_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Rtreemix_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Rtreemix_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Rtreemix_1.26.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Rtreemix_1.26.0.tgz vignettes: vignettes/Rtreemix/inst/doc/Rtreemix.pdf vignetteTitles: Rtreemix hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rtreemix/inst/doc/Rtreemix.R Package: rTRM Version: 1.2.0 Depends: R (>= 2.10), igraph (>= 0.7), RSQLite Imports: AnnotationDbi Suggests: RUnit, BiocGenerics, MotifDb, graph, PWMEnrich, biomaRt, knitr, Biostrings, BSgenome.Mmusculus.UCSC.mm8.masked, org.Hs.eg.db, org.Mm.eg.db, ggplot2 License: GPL-3 MD5sum: 0b69533dda5eae04f77f77034998cb62 NeedsCompilation: no Title: Identification of transcriptional regulatory modules from PPI networks Description: rTRM identifies transcriptional regulatory modules (TRMs) from protein-protein interaction networks. biocViews: Transcription, Network, GeneRegulation, GraphAndNetwork Author: Diego Diez Maintainer: Diego Diez VignetteBuilder: knitr source.ver: src/contrib/rTRM_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rTRM_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rTRM_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rTRM_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rTRM_1.2.0.tgz vignettes: vignettes/rTRM/inst/doc/rTRM_Introduction.pdf vignetteTitles: Introduction to rTRM hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rTRM/inst/doc/rTRM_Introduction.R importsMe: rTRMui Package: rTRMui Version: 1.2.0 Imports: shiny (>= 0.5), rTRM, MotifDb, org.Hs.eg.db, org.Mm.eg.db License: GPL-3 MD5sum: b5bd1f424fbc7c5fafed72c8ea02de4e NeedsCompilation: no Title: A shiny user interface for rTRM Description: This package provides a web interface to compute transcriptional regulatory modules with rTRM. biocViews: Transcription, Network, GeneRegulation, GraphAndNetwork, GUI Author: Diego Diez Maintainer: Diego Diez source.ver: src/contrib/rTRMui_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/rTRMui_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/rTRMui_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/rTRMui_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/rTRMui_1.2.0.tgz vignettes: vignettes/rTRMui/inst/doc/rTRMui.pdf vignetteTitles: Introduction to rTRMui hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rTRMui/inst/doc/rTRMui.R Package: RWebServices Version: 1.28.0 Depends: SJava (>= 0.85), TypeInfo, methods, tools (>= 2.10.0), R (>= 2.5.0) Imports: RCurl, SJava License: file LICENSE License_restricts_use: no MD5sum: 2504b02aefeac395be6dec40805606d5 NeedsCompilation: yes Title: Expose R functions as web services through Java/Axis/Apache Description: This package provides mechanisms for automatic function prototyping and exposure of R functionality in a web services environment. biocViews: Infrastructure Author: Nianhua Li, MT Morgan Maintainer: Martin Morgan source.ver: src/contrib/RWebServices_1.28.0.tar.gz vignettes: vignettes/RWebServices/inst/doc/EnablingPackages.pdf, vignettes/RWebServices/inst/doc/InstallingAndTesting.pdf, vignettes/RWebServices/inst/doc/LessonsLearned.pdf, vignettes/RWebServices/inst/doc/RelatedWork.pdf, vignettes/RWebServices/inst/doc/RToJava.pdf vignetteTitles: Enabling packages as web services, Installing and testing RWebServices and enabled packages, Lessons learned exposing web services, RelatedWork, From R to Java hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/RWebServices/inst/doc/EnablingPackages.R, vignettes/RWebServices/inst/doc/InstallingAndTesting.R, vignettes/RWebServices/inst/doc/LessonsLearned.R, vignettes/RWebServices/inst/doc/RelatedWork.R, vignettes/RWebServices/inst/doc/RToJava.R Package: safe Version: 3.4.0 Depends: R (>= 2.4.0), AnnotationDbi, Biobase, methods, SparseM Suggests: GO.db, KEGG.db, PFAM.db, reactome.db, hgu133a.db, breastCancerUPP, survival, foreach, doRNG, Rgraphviz, GOstats License: GPL (>= 2) MD5sum: 8c88d3ccf8cdd583773fdcfab5f3111a NeedsCompilation: no Title: Significance Analysis of Function and Expression Description: SAFE is a resampling-based method for testing functional categories in gene expression experiments. SAFE can be applied to 2-sample and multi-class comparisons, or simple linear regressions. Other experimental designs can also be accommodated through user-defined functions. biocViews: GeneExpression, FunctionalAnnotation Author: William T. Barry Maintainer: William T. Barry source.ver: src/contrib/safe_3.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/safe_3.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/safe_3.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/safe_3.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/safe_3.4.0.tgz vignettes: vignettes/safe/inst/doc/SAFEmanual3.pdf vignetteTitles: SAFE manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/safe/inst/doc/SAFEmanual3.R Package: sagenhaft Version: 1.34.0 Depends: R (>= 2.10), SparseM (>= 0.73), methods Imports: graphics, methods, SparseM, stats, utils License: GPL (>= 2) MD5sum: 2abc04eea091fa17d6954077912775b7 NeedsCompilation: no Title: Collection of functions for reading and comparing SAGE libraries Description: This package implements several functions useful for analysis of gene expression data by sequencing tags as done in SAGE (Serial Analysis of Gene Expressen) data, i.e. extraction of a SAGE library from sequence files, sequence error correction, library comparison. Sequencing error correction is implementing using an Expectation Maximization Algorithm based on a Mixture Model of tag counts. biocViews: SAGE Author: Tim Beissbarth , with contributions from Gordon Smyth and Lavinia Hyde . Maintainer: Tim Beissbarth URL: http://tagcalling.mbgproject.org source.ver: src/contrib/sagenhaft_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sagenhaft_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sagenhaft_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sagenhaft_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sagenhaft_1.34.0.tgz vignettes: vignettes/sagenhaft/inst/doc/SAGEnhaft.pdf vignetteTitles: SAGEnhaft hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sagenhaft/inst/doc/SAGEnhaft.R Package: SAGx Version: 1.38.0 Depends: R (>= 2.5.0), stats, multtest, methods Imports: Biobase, stats4 Suggests: KEGG.db, hu6800.db, MASS License: GPL-3 Archs: i386, x64 MD5sum: dbf58a2cb1bacec5bfcd586ae33ca6a1 NeedsCompilation: yes Title: Statistical Analysis of the GeneChip Description: A package for retrieval, preparation and analysis of data from the Affymetrix GeneChip. In particular the issue of identifying differentially expressed genes is addressed. biocViews: Microarray, OneChannel, Preprocessing, DataImport, DifferentialExpression, Clustering, MultipleComparison Author: Per Broberg Maintainer: Per Broberg, URL: http://home.swipnet.se/pibroberg/expression_hemsida1.html source.ver: src/contrib/SAGx_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SAGx_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SAGx_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SAGx_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SAGx_1.38.0.tgz vignettes: vignettes/SAGx/inst/doc/samroc-ex.pdf vignetteTitles: samroc - example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SAGx/inst/doc/samroc-ex.R Package: SamSPECTRAL Version: 1.18.0 Depends: R (>= 2.10) Imports: methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 583e14f8256f3b196e92df326cf1129e NeedsCompilation: yes Title: Identifies cell population in flow cytometry data. Description: Samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting "connected components" estimate biological cell populations in the data sample. For instructions on manual installation, refer to the PDF file provided in the following documentation. biocViews: FlowCytometry, CellBiology, Clustering, Cancer, FlowCytometry, StemCells, HIV Author: Habil Zare and Parisa Shooshtari Maintainer: Habil Zare source.ver: src/contrib/SamSPECTRAL_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SamSPECTRAL_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SamSPECTRAL_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SamSPECTRAL_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SamSPECTRAL_1.18.0.tgz vignettes: vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.pdf vignetteTitles: A modified spectral clustering method for clustering Flow Cytometry Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SamSPECTRAL/inst/doc/Clustering_by_SamSPECTRAL.R Package: sangerseqR Version: 1.0.0 Depends: R (>= 3.0.2), Biostrings Imports: methods Suggests: BiocStyle, knitr, RUnit, BiocGenerics License: GPL-2 MD5sum: c8b5e768ec52710b39977d9438f722db NeedsCompilation: no Title: Tools for Sanger Sequencing Data in R Description: This package contains several tools for analyzing Sanger Sequencing data files in R, including reading .scf and .ab1 files, making basecalls and plotting chromatograms. biocViews: Sequencing, SNP, Visualization Author: Jonathon T. Hill, Bradley Demarest Maintainer: Jonathon Hill VignetteBuilder: knitr source.ver: src/contrib/sangerseqR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sangerseqR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sangerseqR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sangerseqR_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sangerseqR_1.0.0.tgz vignettes: vignettes/sangerseqR/inst/doc/sangerseq_walkthrough.pdf vignetteTitles: sangerseqR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sangerseqR/inst/doc/sangerseq_walkthrough.R Package: SANTA Version: 1.4.0 Depends: R (>= 2.14), igraph Imports: Matrix, msm, snow Suggests: RUnit, BiocGenerics, org.Sc.sgd.db License: Artistic-2.0 Archs: i386, x64 MD5sum: 3ecd398a129d2236ef8bd08ff0429148 NeedsCompilation: yes Title: Spatial Analysis of Network Associations Description: This package provides methods for measuring the strength of association between a network and a phenotype. It does this by measuring clustering of the phenotype across the network. Vertices can also be individually ranked by their strength of association with high-weight vertices. biocViews: Network, NetworkEnrichment, Clustering Author: Alex Cornish and Florian Markowetz Maintainer: Alex Cornish source.ver: src/contrib/SANTA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SANTA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SANTA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SANTA_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SANTA_1.4.0.tgz vignettes: vignettes/SANTA/inst/doc/SANTA.pdf vignetteTitles: Using SANTA hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SANTA/inst/doc/SANTA.R Package: sapFinder Version: 1.0.1 Depends: R (>= 3.0.0),rTANDEM (>= 1.3.5) Imports: pheatmap,Rcpp (>= 0.10.6),graphics,grDevices,stats, utils LinkingTo: Rcpp Suggests: RUnit, BiocGenerics, BiocStyle License: GPL-2 Archs: i386, x64 MD5sum: e0d47be78cc335a01f70bb89754a73b8 NeedsCompilation: yes Title: A package for variant peptides detection and visualization in shotgun proteomics. Description: sapFinder is developed to automate (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics. biocViews: MassSpectrometry, Proteomics, SNP, RNASeq, Visualization, ReportWriting Author: Shaohang Xu, Bo Wen Maintainer: Shaohang Xu , Bo Wen source.ver: src/contrib/sapFinder_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/sapFinder_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/sapFinder_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/sapFinder_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sapFinder_1.0.1.tgz vignettes: vignettes/sapFinder/inst/doc/sapFinder.pdf vignetteTitles: sapFinder Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sapFinder/inst/doc/sapFinder.R Package: savR Version: 1.2.0 Depends: ggplot2 Imports: methods, reshape2, scales, gridExtra, XML Suggests: Cairo License: AGPL-3 MD5sum: a9f7a5f42e611e5b033fde00b71fce9f NeedsCompilation: no Title: Parse and analyze Illumina SAV files Description: Parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots. biocViews: Sequencing Author: R. Brent Calder Maintainer: R. Brent Calder URL: https://github.com/bcalder/savR source.ver: src/contrib/savR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/savR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/savR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/savR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/savR_1.2.0.tgz vignettes: vignettes/savR/inst/doc/savR.pdf vignetteTitles: Using savR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/savR/inst/doc/savR.R Package: SBMLR Version: 1.60.0 Depends: XML, deSolve Suggests: rsbml License: GPL-2 MD5sum: 0bf1e8d5005ddd494fcfc459b20e7ded NeedsCompilation: no Title: SBML-R Interface and Analysis Tools Description: This package contains a systems biology markup language (SBML) interface to R. biocViews: GraphAndNetwork, Pathways, Network Author: Tomas Radivoyevitch, Vishak Venkateswaran Maintainer: Tomas Radivoyevitch URL: http://epbi-radivot.cwru.edu/SBMLR/SBMLR.html source.ver: src/contrib/SBMLR_1.60.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SBMLR_1.60.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SBMLR_1.60.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SBMLR_1.60.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SBMLR_1.60.0.tgz vignettes: vignettes/SBMLR/inst/doc/quick-start.pdf vignetteTitles: Quick intro to SBMLR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SBMLR/inst/doc/quick-start.R Package: SCAN.UPC Version: 2.6.3 Depends: R (>= 2.14.0), Biobase (>= 2.6.0), oligo, Biostrings, GEOquery, affy, affyio, foreach, sva Imports: utils, methods, MASS, tools Suggests: pd.hg.u95a License: MIT MD5sum: 658f40d2e79d3844178c73a15b9850f4 NeedsCompilation: no Title: Single-channel array normalization (SCAN) and Universal exPression Codes (UPC) Description: SCAN is a microarray normalization method to facilitate personalized-medicine workflows. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The Universal exPression Codes (UPC) method is an extension of SCAN that estimates whether a given gene/transcript is active above background levels in a given sample. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration. biocViews: Software, Microarray, Preprocessing, RNASeq, TwoChannel, OneChannel Author: Stephen R. Piccolo and Andrea H. Bild and W. Evan Johnson Maintainer: Stephen R. Piccolo URL: http://bioconductor.org, http://jlab.bu.edu/software/scan-upc source.ver: src/contrib/SCAN.UPC_2.6.3.tar.gz win.binary.ver: bin/windows/contrib/3.1/SCAN.UPC_2.6.3.zip win64.binary.ver: bin/windows64/contrib/3.1/SCAN.UPC_2.6.3.zip mac.binary.ver: bin/macosx/contrib/3.1/SCAN.UPC_2.6.3.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SCAN.UPC_2.6.3.tgz vignettes: vignettes/SCAN.UPC/inst/doc/SCAN.vignette.pdf vignetteTitles: Primer hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SCAN.UPC/inst/doc/SCAN.vignette.R Package: ScISI Version: 1.36.0 Depends: R (>= 2.10), GO.db, RpsiXML, annotate, apComplex Imports: AnnotationDbi, GO.db, RpsiXML, annotate, methods, org.Sc.sgd.db, utils Suggests: ppiData, xtable License: LGPL MD5sum: 6d1e23327c069c4d8f7a4b73422f96a6 NeedsCompilation: no Title: In Silico Interactome Description: Package to create In Silico Interactomes biocViews: GraphAndNetwork, Proteomics, NetworkInference Author: Tony Chiang Maintainer: Tony Chiang source.ver: src/contrib/ScISI_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ScISI_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ScISI_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ScISI_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ScISI_1.36.0.tgz vignettes: vignettes/ScISI/inst/doc/vignette.pdf vignetteTitles: ScISI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ScISI/inst/doc/vignette.R dependsOnMe: PCpheno, ppiStats, SLGI importsMe: PCpheno, SLGI suggestsMe: RpsiXML Package: scsR Version: 1.0.0 Depends: R (>= 2.14.0), methods, BiocGenerics, Biostrings, IRanges, plyr, STRINGdb, tcltk Imports: sqldf, hash, ggplot2, graphics,grDevices, RColorBrewer Suggests: RUnit License: GPL-2 MD5sum: f85f30278a4b9c462a6fb92c6e176d6f NeedsCompilation: no Title: SiRNA correction for seed mediated off-target effect Description: Corrects genome-wide siRNA screens for seed mediated off-target effect. Suitable functions to identify the effective seeds/miRNAs and to visualize their effect are also provided in the package. biocViews: Preprocessing Author: Andrea Franceschini Maintainer: Andrea Franceschini , Roger Meier , Christian von Mering source.ver: src/contrib/scsR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/scsR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/scsR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/scsR_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/scsR_1.0.0.tgz vignettes: vignettes/scsR/inst/doc/scsR.pdf vignetteTitles: scsR Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/scsR/inst/doc/scsR.R Package: segmentSeq Version: 1.16.0 Depends: R (>= 2.3.0), methods, baySeq (>= 1.15.4), ShortRead, GenomicRanges, IRanges Imports: baySeq, graphics, grDevices, IRanges, methods, utils, GenomicRanges Suggests: snow License: GPL-3 MD5sum: 8197b780736fc0ae9a9cd28f7b040bcb NeedsCompilation: no Title: Methods for identifying small RNA loci from high-throughput sequencing data Description: High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery. biocViews: Bioinformatics, HighThroughputSequencing, MultipleComparisons Author: Thomas J. Hardcastle Maintainer: Thomas J. Hardcastle source.ver: src/contrib/segmentSeq_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/segmentSeq_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/segmentSeq_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/segmentSeq_1.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/segmentSeq_1.16.0.tgz vignettes: vignettes/segmentSeq/inst/doc/methylationAnalysis.pdf, vignettes/segmentSeq/inst/doc/segmentSeq.pdf vignetteTitles: segmentSeq, segmentSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/segmentSeq/inst/doc/methylationAnalysis.R, vignettes/segmentSeq/inst/doc/segmentSeq.R Package: SeqArray Version: 1.4.0 Depends: gdsfmt (>= 1.0.0) Imports: methods, parallel, Biostrings, GenomicRanges, IRanges, VariantAnnotation Suggests: BiocGenerics, RUnit, Rcpp License: GPL-3 Archs: i386, x64 MD5sum: 9380f2001117370ea6bf7a46c6917600 NeedsCompilation: yes Title: Big Data Management of Genome-wide Sequencing Variants Description: Big data management of genome-wide variants using the CoreArray library: genotypic data and annotations are stored in an array-oriented manner, offering efficient access of genetic variants using the R language. biocViews: Infrastructure, Sequencing, Genetics Author: Xiuwen Zheng, Stephanie M. Gogarten, Cathy Laurie Maintainer: Xiuwen Zheng URL: http://corearray.sourceforge.net/tutorials/SeqArray/ source.ver: src/contrib/SeqArray_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SeqArray_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SeqArray_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SeqArray_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SeqArray_1.4.0.tgz vignettes: vignettes/SeqArray/inst/doc/SeqArray-JSM2013.pdf, vignettes/SeqArray/inst/doc/SeqArrayTutorial.pdf vignetteTitles: SeqArray-JSM2013.pdf, SeqArray: an R/Bioconductor Package for Big Data Management of Genome-Wide Sequencing Variants hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SeqArray/inst/doc/SeqArrayTutorial.R dependsOnMe: SeqVarTools Package: seqbias Version: 1.12.0 Depends: R (>= 2.13.0), GenomicRanges (>= 0.1.0), Biostrings (>= 2.15.0), methods Imports: zlibbioc LinkingTo: Rsamtools Suggests: Rsamtools, ggplot2 License: LGPL-3 Archs: i386, x64 MD5sum: 3c8a969be12a3d9a0af1eab0648d33ae NeedsCompilation: yes Title: Estimation of per-position bias in high-throughput sequencing data Description: This package implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence. biocViews: Sequencing Author: Daniel Jones Maintainer: Daniel Jones source.ver: src/contrib/seqbias_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/seqbias_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/seqbias_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/seqbias_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/seqbias_1.12.0.tgz vignettes: vignettes/seqbias/inst/doc/overview.pdf vignetteTitles: Assessing and Adjusting for Technical Bias in High Throughput Sequencing Data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/seqbias/inst/doc/overview.R dependsOnMe: ReQON Package: seqCNA Version: 1.6.0 Depends: R (>= 3.0), GLAD (>= 2.14), doSNOW (>= 1.0.5), adehabitatLT (>= 0.3.4), seqCNA.annot (>= 0.99), methods License: GPL-3 Archs: i386, x64 MD5sum: 036b5ef8cca83e315c6e41d7ceadfecf NeedsCompilation: yes Title: Copy number analysis of high-throughput sequencing cancer data Description: Copy number analysis of high-throughput sequencing cancer data with fast summarization, extensive filtering and improved normalization biocViews: CopyNumberVariation, Genetics, Sequencing Author: David Mosen-Ansorena Maintainer: David Mosen-Ansorena SystemRequirements: samtools source.ver: src/contrib/seqCNA_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/seqCNA_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/seqCNA_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/seqCNA_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/seqCNA_1.6.0.tgz vignettes: vignettes/seqCNA/inst/doc/seqCNA.pdf vignetteTitles: seqCNA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/seqCNA/inst/doc/seqCNA.R Package: SeqGSEA Version: 1.4.2 Depends: Biobase, doParallel, DESeq Imports: methods, biomaRt Suggests: easyRNASeq, GenomicRanges License: GPL (>= 3) MD5sum: f92f999f90aba338d83d740e1b6a7aa3 NeedsCompilation: no Title: Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating differential expression and splicing Description: The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively. biocViews: Sequencing, RNASeq, GeneSetEnrichment, GeneExpression, DifferentialExpression Author: Xi Wang Maintainer: Xi Wang source.ver: src/contrib/SeqGSEA_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/SeqGSEA_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/SeqGSEA_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/SeqGSEA_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SeqGSEA_1.4.2.tgz vignettes: vignettes/SeqGSEA/inst/doc/SeqGSEA.pdf vignetteTitles: Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SeqGSEA/inst/doc/SeqGSEA.R Package: seqLogo Version: 1.30.0 Depends: methods, grid License: LGPL (>= 2) MD5sum: b85a52262827218be7ae0cdf1c1001e3 NeedsCompilation: no Title: Sequence logos for DNA sequence alignments Description: seqLogo takes the position weight matrix of a DNA sequence motif and plots the corresponding sequence logo as introduced by Schneider and Stephens (1990). biocViews: SequenceMatching Author: Oliver Bembom Maintainer: Oliver Bembom source.ver: src/contrib/seqLogo_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/seqLogo_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/seqLogo_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/seqLogo_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/seqLogo_1.30.0.tgz vignettes: vignettes/seqLogo/inst/doc/seqLogo.pdf vignetteTitles: Sequence logos for DNA sequence alignments hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/seqLogo/inst/doc/seqLogo.R dependsOnMe: motifRG, rGADEM importsMe: PWMEnrich, rGADEM, TFBSTools suggestsMe: BCRANK, MotifDb Package: SeqVarTools Version: 1.2.0 Depends: SeqArray (>= 1.1.1) Imports: methods, GenomicRanges, IRanges, GWASExactHW Suggests: BiocGenerics, RUnit License: GPL-3 MD5sum: a072d52a1a0ba6c44d028eb2397ed04f NeedsCompilation: no Title: Tools for variant data Description: An interface to the fast-access storage format for VCF data provided in SeqArray, with tools for common operations and analysis. biocViews: SNP, GeneticVariability, Sequencing, Genetics Author: Stephanie M. Gogarten, Xiuwen Zheng Maintainer: Stephanie M. Gogarten , Xiuwen Zheng source.ver: src/contrib/SeqVarTools_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SeqVarTools_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SeqVarTools_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SeqVarTools_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SeqVarTools_1.2.0.tgz vignettes: vignettes/SeqVarTools/inst/doc/SeqVarTools.pdf vignetteTitles: Introduction to SeqVarTools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SeqVarTools/inst/doc/SeqVarTools.R Package: shinyTANDEM Version: 1.2.0 Depends: rTANDEM (>= 1.3.5), shiny, mixtools, methods, xtable License: GPL-3 MD5sum: 83dbaf6d5e975de32bb14a4ec97c7e6b NeedsCompilation: no Title: Provides a GUI for rTANDEM Description: This package provides a GUI interface for rTANDEM. The GUI is primarily designed to visualize rTANDEM result object or result xml files. But it will also provides an interface for creating parameter objects, launching searches or performing conversions between R objects and xml files. biocViews: MassSpectrometry, Proteomics Author: Frederic Fournier , Arnaud Droit Maintainer: Frederic Fournier source.ver: src/contrib/shinyTANDEM_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/shinyTANDEM_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/shinyTANDEM_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/shinyTANDEM_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/shinyTANDEM_1.2.0.tgz vignettes: vignettes/shinyTANDEM/inst/doc/shinyTANDEM.pdf vignetteTitles: shinyTANDEM user guide hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/shinyTANDEM/inst/doc/shinyTANDEM.R Package: ShortRead Version: 1.22.0 Depends: BiocGenerics (>= 0.1.0), BiocParallel, Biostrings (>= 2.31.14), Rsamtools (>= 1.13.1), GenomicAlignments (>= 0.99.6) Imports: Biobase, GenomicRanges (>= 1.15.26), IRanges (>= 1.21.22), hwriter, methods, zlibbioc, lattice, latticeExtra, LinkingTo: IRanges, XVector, Biostrings Suggests: BiocStyle, RUnit, biomaRt, GenomicFeatures, yeastNagalakshmi License: Artistic-2.0 Archs: i386, x64 MD5sum: 5730295ed8e5c433e52316ac94336dda NeedsCompilation: yes Title: FASTQ input and manipulation Description: This package implements sampling, iteration, and input of FASTQ files. The package includes functions for filtering and trimming reads, and for generating a quality assessment report. Data are represented as DNAStringSet-derived objects, and easily manipulated for a diversity of purposes. The package also contains legacy support for early single-end, ungapped alignment formats. biocViews: DataImport, Sequencing, QualityControl Author: Martin Morgan, Michael Lawrence, Simon Anders Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ShortRead_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ShortRead_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ShortRead_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ShortRead_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ShortRead_1.22.0.tgz vignettes: vignettes/ShortRead/inst/doc/Overview.pdf vignetteTitles: An introduction to ShortRead hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ShortRead/inst/doc/Overview.R dependsOnMe: Basic4Cseq, chipseq, ChIPseqR, EDASeq, girafe, HTSeqGenie, nucleR, OTUbase, Rolexa, rSFFreader, segmentSeq importsMe: ArrayExpressHTS, BEAT, chipseq, ChIPseqR, ChIPsim, easyRNASeq, GOTHiC, nucleR, OTUbase, QuasR, R453Plus1Toolbox, Rolexa, rSFFreader, RSVSim suggestsMe: CSAR, DBChIP, Genominator, PICS, PING, Repitools, Rsamtools Package: sigaR Version: 1.8.0 Depends: Biobase, CGHbase, methods, mvtnorm, penalized Imports: corpcor (>= 1.6.2), graphics, igraph, marray, MASS, mvtnorm, quadprog, penalized (>= 0.9-39), snowfall, stats License: GPL (>= 2) MD5sum: e16d4be042f528bc4e48bd6c4fb3573f NeedsCompilation: no Title: statistics for integrative genomics analyses in R Description: Facilites the joint analysis of high-throughput data from multiple molecular levels. Contains functions for manipulation of objects, various analysis types, and some visualization. biocViews: Microarray, DifferentialExpression, aCGH, GeneExpression, Pathways Author: Wessel N. van Wieringen Maintainer: Wessel N. van Wieringen URL: http://www.few.vu.nl/~wvanwie source.ver: src/contrib/sigaR_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sigaR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sigaR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sigaR_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sigaR_1.8.0.tgz vignettes: vignettes/sigaR/inst/doc/sigaR.pdf vignetteTitles: sigaR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sigaR/inst/doc/sigaR.R dependsOnMe: HCsnip Package: SigFuge Version: 1.2.0 Depends: R (>= 3.0.2), GenomicRanges Imports: ggplot2, matlab, reshape, sigclust Suggests: org.Hs.eg.db, prebsdata, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene, BiocStyle License: GPL-3 MD5sum: 35b574f1da3829acb26e0513dd09409b NeedsCompilation: no Title: SigFuge Description: Algorithm for testing significance of clustering in RNA-seq data. biocViews: Clustering, Visualization, RNASeq Author: Patrick Kimes, Christopher Cabanski Maintainer: Patrick Kimes source.ver: src/contrib/SigFuge_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SigFuge_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SigFuge_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SigFuge_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SigFuge_1.2.0.tgz vignettes: vignettes/SigFuge/inst/doc/SigFuge.pdf vignetteTitles: SigFuge Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SigFuge/inst/doc/SigFuge.R Package: siggenes Version: 1.38.0 Depends: methods, Biobase, multtest, splines, graphics Imports: stats4 Suggests: affy, annotate, genefilter, KernSmooth, scrime (>= 1.2.5) License: LGPL (>= 2) MD5sum: 01c3dafcbcb103173e3c9a653fdae3b3 NeedsCompilation: no Title: Multiple testing using SAM and Efron's empirical Bayes approaches Description: Identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM). biocViews: MultipleComparison, Microarray, GeneExpression, SNP, ExonArray, DifferentialExpression Author: Holger Schwender Maintainer: Holger Schwender source.ver: src/contrib/siggenes_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/siggenes_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/siggenes_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/siggenes_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/siggenes_1.38.0.tgz vignettes: vignettes/siggenes/inst/doc/siggenes.pdf vignetteTitles: siggenes Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/siggenes/inst/doc/siggenes.R htmlDocs: vignettes/siggenes/inst/doc/identify.sam.html, vignettes/siggenes/inst/doc/plot.ebam.html, vignettes/siggenes/inst/doc/plot.finda0.html, vignettes/siggenes/inst/doc/plot.sam.html, vignettes/siggenes/inst/doc/print.ebam.html, vignettes/siggenes/inst/doc/print.finda0.html, vignettes/siggenes/inst/doc/print.sam.html, vignettes/siggenes/inst/doc/summary.ebam.html, vignettes/siggenes/inst/doc/summary.sam.html htmlTitles: "R: SAM specific identify method", "R: EBAM specific plot method", "R: FindA0 specific plot method", "R: SAM specific plot method", "R: EBAM specific print method", "R: FindA0 specific print method", "R: SAM specific print method", "R: EBAM specific summary method", "R: SAM specific summary method" dependsOnMe: KCsmart, oneChannelGUI importsMe: charm, GeneSelector, minfi suggestsMe: GeneSelector, logicFS, trio, XDE Package: sigPathway Version: 1.32.1 Depends: R (>= 2.10) Suggests: hgu133a.db (>= 1.10.0), XML (>= 1.6-3), AnnotationDbi (>= 1.3.12) License: GPL-2 Archs: i386, x64 MD5sum: d47a845f2056d2c86c93512a6fbd4d49 NeedsCompilation: yes Title: Pathway Analysis Description: Conducts pathway analysis by calculating the NT_k and NE_k statistics as described in Tian et al. (2005) biocViews: DifferentialExpression, MultipleComparison Author: Weil Lai (optimized R and C code), Lu Tian and Peter Park (algorithm development and initial R code) Maintainer: Weil Lai URL: http://www.pnas.org/cgi/doi/10.1073/pnas.0506577102, http://www.chip.org/~ppark/Supplements/PNAS05.html source.ver: src/contrib/sigPathway_1.32.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/sigPathway_1.32.1.zip win64.binary.ver: bin/windows64/contrib/3.1/sigPathway_1.32.1.zip mac.binary.ver: bin/macosx/contrib/3.1/sigPathway_1.32.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sigPathway_1.32.1.tgz vignettes: vignettes/sigPathway/inst/doc/sigPathway-vignette.pdf vignetteTitles: sigPathway hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sigPathway/inst/doc/sigPathway-vignette.R dependsOnMe: tRanslatome Package: SIM Version: 1.34.0 Depends: R (>= 2.4), quantreg Imports: graphics, stats, globaltest, quantsmooth Suggests: biomaRt, RColorBrewer License: GPL (>= 2) Archs: i386, x64 MD5sum: b2cbd3b412af648952881a41df1efcea NeedsCompilation: yes Title: Integrated Analysis on two human genomic datasets Description: Finds associations between two human genomic datasets. biocViews: Microarray, Visualization Author: Renee X. de Menezes and Judith M. Boer Maintainer: Renee X. de Menezes source.ver: src/contrib/SIM_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SIM_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SIM_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SIM_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SIM_1.34.0.tgz vignettes: vignettes/SIM/inst/doc/SIM.pdf vignetteTitles: SIM vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SIM/inst/doc/SIM.R Package: SimBindProfiles Version: 1.2.0 Depends: R (>= 2.10), methods, Ringo Imports: limma, mclust, Biobase License: GPL-3 MD5sum: 87a55320f5bbac6aa0641fcf209ff67e NeedsCompilation: no Title: Similar Binding Profiles Description: SimBindProfiles identifies common and unique binding regions in genome tiling array data. This package does not rely on peak calling, but directly compares binding profiles processed on the same array platform. It implements a simple threshold approach, thus allowing retrieval of commonly and differentially bound regions between datasets as well as events of compensation and increased binding. biocViews: Microarray, Software Author: Bettina Fischer, Enrico Ferrero, Robert Stojnic, Steve Russell Maintainer: Bettina Fischer source.ver: src/contrib/SimBindProfiles_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SimBindProfiles_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SimBindProfiles_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SimBindProfiles_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SimBindProfiles_1.2.0.tgz vignettes: vignettes/SimBindProfiles/inst/doc/SimBindProfiles.pdf vignetteTitles: SimBindProfiles: Similar Binding Profiles,, identifies common and unique regions in array genome tiling array data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SimBindProfiles/inst/doc/SimBindProfiles.R Package: simpleaffy Version: 2.40.0 Depends: R (>= 2.0.0), methods, utils, grDevices, graphics, stats, BiocGenerics (>= 0.1.12), Biobase, affy (>= 1.33.6), genefilter, gcrma Imports: methods, utils, grDevices, graphics, stats, BiocGenerics, Biobase, affy, genefilter, gcrma License: GPL (>= 2) Archs: i386, x64 MD5sum: 38fed262d3615bb532a50b3f7be664fa NeedsCompilation: yes Title: Very simple high level analysis of Affymetrix data Description: Provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. Makes heavy use of the affy library. Also has some basic scatter plot functions and mechanisms for generating high resolution journal figures... biocViews: Microarray, OneChannel, QualityControl, Preprocessing, Transcription, DataImport, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Crispin J Miller Maintainer: Crispin Miller URL: http://www.bioconductor.org, http://bioinformatics.picr.man.ac.uk/simpleaffy/ source.ver: src/contrib/simpleaffy_2.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/simpleaffy_2.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/simpleaffy_2.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/simpleaffy_2.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/simpleaffy_2.40.0.tgz vignettes: vignettes/simpleaffy/inst/doc/simpleAffy.pdf vignetteTitles: simpleaffy primer hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/simpleaffy/inst/doc/simpleAffy.R dependsOnMe: yaqcaffy importsMe: affyQCReport, arrayMvout suggestsMe: AffyExpress, ArrayTools, ELBOW Package: sizepower Version: 1.34.0 Depends: stats License: LGPL MD5sum: 7c3e1169e057807ad02083d1f91d4ae5 NeedsCompilation: no Title: Sample Size and Power Calculation in Micorarray Studies Description: This package has been prepared to assist users in computing either a sample size or power value for a microarray experimental study. The user is referred to the cited references for technical background on the methodology underpinning these calculations. This package provides support for five types of sample size and power calculations. These five types can be adapted in various ways to encompass many of the standard designs encountered in practice. biocViews: Microarray Author: Weiliang Qiu and Mei-Ling Ting Lee and George Alex Whitmore Maintainer: Weiliang Qiu source.ver: src/contrib/sizepower_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sizepower_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sizepower_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sizepower_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sizepower_1.34.0.tgz vignettes: vignettes/sizepower/inst/doc/sizepower.pdf vignetteTitles: package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sizepower/inst/doc/sizepower.R suggestsMe: oneChannelGUI Package: SJava Version: 0.90.0 Depends: R (>= 2.10.0), methods Imports: methods License: GPL (>= 2) MD5sum: 4d6c692d51bca0728cdcb0697faa0b2a NeedsCompilation: yes Title: The Omegahat interface for R and Java. Description: An interface from R to Java to create and call Java objects and methods. biocViews: Infrastructure Author: Duncan Temple Lang, John Chambers Maintainer: Martin Morgan source.ver: src/contrib/SJava_0.90.0.tar.gz hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: RWebServices importsMe: RWebServices Package: SLGI Version: 1.24.0 Depends: R (>= 2.10), ScISI, lattice Imports: AnnotationDbi, Biobase, GO.db, ScISI, graphics, lattice, methods, stats, BiocGenerics Suggests: GO.db, org.Sc.sgd.db License: Artistic-2.0 MD5sum: f669f937af67c7d97ef13f0dca2c82d3 NeedsCompilation: no Title: Synthetic Lethal Genetic Interaction Description: A variety of data files and functions for the analysis of genetic interactions biocViews: GraphAndNetwork, Proteomics, Genetics, Network Author: Nolwenn LeMeur, Zhen Jiang, Ting-Yuan Liu, Jess Mar and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/SLGI_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SLGI_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SLGI_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SLGI_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SLGI_1.24.0.tgz vignettes: vignettes/SLGI/inst/doc/SLGI.pdf vignetteTitles: SLGI Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SLGI/inst/doc/SLGI.R dependsOnMe: PCpheno Package: SLqPCR Version: 1.30.0 Depends: R(>= 2.4.0) Imports: stats Suggests: RColorBrewer License: GPL (>= 2) MD5sum: ae8eb1d37984e10e8cc18377903c2f58 NeedsCompilation: no Title: Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH Description: Functions for analysis of real-time quantitative PCR data at SIRS-Lab GmbH biocViews: MicrotitrePlateAssay, qPCR Author: Matthias Kohl Maintainer: Matthias Kohl source.ver: src/contrib/SLqPCR_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SLqPCR_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SLqPCR_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SLqPCR_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SLqPCR_1.30.0.tgz vignettes: vignettes/SLqPCR/inst/doc/SLqPCR.pdf vignetteTitles: SLqPCR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SLqPCR/inst/doc/SLqPCR.R suggestsMe: EasyqpcR Package: SMAP Version: 1.28.0 Depends: R (>= 2.10), methods License: GPL-2 Archs: i386, x64 MD5sum: 117d4779f6031b58a4c7c707f7055a3d NeedsCompilation: yes Title: A Segmental Maximum A Posteriori Approach to Array-CGH Copy Number Profiling Description: Functions and classes for DNA copy number profiling of array-CGH data biocViews: Microarray, TwoChannel, CopyNumberVariation Author: Robin Andersson Maintainer: Robin Andersson source.ver: src/contrib/SMAP_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SMAP_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SMAP_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SMAP_1.28.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SMAP_1.28.0.tgz vignettes: vignettes/SMAP/inst/doc/SMAP.pdf vignetteTitles: SMAP hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SMAP/inst/doc/SMAP.R Package: SNAGEE Version: 1.4.0 Depends: R (>= 2.6.0), SNAGEEdata Suggests: ALL, hgu95av2.db Enhances: parallel License: Artistic-2.0 MD5sum: ed62d2d19c147ff2fbdfb13a208c0cc9 NeedsCompilation: no Title: Signal-to-Noise applied to Gene Expression Experiments Description: Signal-to-Noise applied to Gene Expression Experiments. Signal-to-noise ratios can be used as a proxy for quality of gene expression studies and samples. The SNRs can be calculated on any gene expression data set as long as gene IDs are available, no access to the raw data files is necessary. This allows to flag problematic studies and samples in any public data set. biocViews: Microarray, OneChannel, TwoChannel, QualityControl Author: David Venet Maintainer: David Venet URL: http://bioconductor.org/ source.ver: src/contrib/SNAGEE_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SNAGEE_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SNAGEE_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SNAGEE_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SNAGEE_1.4.0.tgz vignettes: vignettes/SNAGEE/inst/doc/SNAGEE.pdf vignetteTitles: SNAGEE Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SNAGEE/inst/doc/SNAGEE.R Package: snapCGH Version: 1.34.0 Depends: limma, DNAcopy, methods Imports: aCGH, cluster, DNAcopy, GLAD, graphics, grDevices, limma, methods, stats, tilingArray, utils License: GPL Archs: i386, x64 MD5sum: 9b23375405904e772648f346629e368c NeedsCompilation: yes Title: Segmentation, normalisation and processing of aCGH data. Description: Methods for segmenting, normalising and processing aCGH data; including plotting functions for visualising raw and segmented data for individual and multiple arrays. biocViews: Microarray, CopyNumberVariation, TwoChannel, Preprocessing Author: Mike L. Smith, John C. Marioni, Steven McKinney, Thomas Hardcastle, Natalie P. Thorne Maintainer: John Marioni source.ver: src/contrib/snapCGH_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/snapCGH_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.1/snapCGH_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.1/snapCGH_1.34.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/snapCGH_1.34.0.tgz vignettes: vignettes/snapCGH/inst/doc/snapCGHguide.pdf vignetteTitles: Segmentation Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snapCGH/inst/doc/snapCGHguide.R importsMe: ADaCGH2 suggestsMe: beadarraySNP Package: snm Version: 1.12.0 Depends: R (>= 2.12.0) Imports: corpcor, lme4 (>= 1.0), splines License: LGPL MD5sum: 5401972d8019fd227e340672b2eb805c NeedsCompilation: no Title: Supervised Normalization of Microarrays Description: SNM is a modeling strategy especially designed for normalizing high-throughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as study-specific variables. These variables are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest. biocViews: Microarray, OneChannel, TwoChannel, MultiChannel, DifferentialExpression, ExonArray, GeneExpression, Transcription, MultipleComparison, Preprocessing, QualityControl Author: Brig Mecham and John D. Storey Maintainer: John D. Storey source.ver: src/contrib/snm_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/snm_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/snm_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/snm_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/snm_1.12.0.tgz vignettes: vignettes/snm/inst/doc/snm.pdf vignetteTitles: snm Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snm/inst/doc/snm.R Package: SNPchip Version: 2.10.0 Depends: R (>= 2.14.0) Imports: graphics, lattice, grid, foreach, utils, methods, oligoClasses (>= 1.21.12), Biobase, GenomicRanges Suggests: crlmm (>= 1.17.14), IRanges, RUnit Enhances: doSNOW, VanillaICE (>= 1.21.24), RColorBrewer License: LGPL (>= 2) MD5sum: c580d8948e7803c32fe4852599b2d8a3 NeedsCompilation: no Title: Visualizations for copy number alterations Description: This package defines methods for visualizing high-throughput genomic data biocViews: CopyNumberVariation, SNP, GeneticVariability, Visualization Author: Robert Scharpf and Ingo Ruczinski Maintainer: Robert Scharpf URL: http://www.biostat.jhsph.edu/~iruczins/software/snpchip.html source.ver: src/contrib/SNPchip_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SNPchip_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SNPchip_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SNPchip_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SNPchip_2.10.0.tgz vignettes: vignettes/SNPchip/inst/doc/PlottingIdiograms.pdf vignetteTitles: Plotting Idiograms hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SNPchip/inst/doc/PlottingIdiograms.R dependsOnMe: mBPCR importsMe: crlmm, phenoTest suggestsMe: Category, MinimumDistance, oligoClasses, VanillaICE Package: snpStats Version: 1.14.0 Depends: R(>= 2.10.0), survival, Matrix, methods Imports: graphics, grDevices, stats, utils, BiocGenerics Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: 78a46750b09d13b4b1a56c734b9d3741 NeedsCompilation: yes Title: SnpMatrix and XSnpMatrix classes and methods Description: Classes and statistical methods for large SNP association studies, extending the snpMatrix package (now removed) biocViews: Microarray, SNP, GeneticVariability Author: David Clayton Maintainer: David Clayton source.ver: src/contrib/snpStats_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/snpStats_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/snpStats_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/snpStats_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/snpStats_1.14.0.tgz vignettes: vignettes/snpStats/inst/doc/data-input-vignette.pdf, vignettes/snpStats/inst/doc/differences.pdf, vignettes/snpStats/inst/doc/Fst-vignette.pdf, vignettes/snpStats/inst/doc/imputation-vignette.pdf, vignettes/snpStats/inst/doc/ld-vignette.pdf, vignettes/snpStats/inst/doc/pca-vignette.pdf, vignettes/snpStats/inst/doc/snpStats-vignette.pdf, vignettes/snpStats/inst/doc/tdt-vignette.pdf vignetteTitles: Data input, snpMatrix-differences, Fst, Imputation and meta-analysis, LD statistics, Principal components analysis, snpStats introduction, TDT tests hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/snpStats/inst/doc/data-input-vignette.R, vignettes/snpStats/inst/doc/differences.R, vignettes/snpStats/inst/doc/Fst-vignette.R, vignettes/snpStats/inst/doc/imputation-vignette.R, vignettes/snpStats/inst/doc/ld-vignette.R, vignettes/snpStats/inst/doc/pca-vignette.R, vignettes/snpStats/inst/doc/snpStats-vignette.R, vignettes/snpStats/inst/doc/tdt-vignette.R dependsOnMe: GGBase importsMe: FunciSNP, GGtools, gwascat suggestsMe: crlmm, GWASTools, VariantAnnotation Package: SomatiCA Version: 1.6.0 Depends: R (>= 2.14.0), lars, DNAcopy, foreach, methods, rebmix, GenomicRanges, IRanges, doParallel Imports: foreach, lars, sn, DNAcopy, methods, rebmix, GenomicRanges, IRanges Enhances: sn, SomatiCAData License: GPL (>=2) MD5sum: 9eba439906dde84af468685a38015e18 NeedsCompilation: no Title: SomatiCA: identifying, characterizing, and quantifying somatic copy number aberrations from cancer genome sequencing Description: SomatiCA is a software suite that is capable of identifying, characterizing, and quantifying somatic CNAs from cancer genome sequencing. First, it uses read depths and lesser allele frequencies (LAF) from mapped short sequence reads to segment the genome and identify candidate CNAs. Second, SomatiCA estimates the admixture rate from the relative copy-number profile of tumor-normal pair by a Bayesian finite mixture model. Third, SomatiCA quantifies absolute somatic copy-number and subclonality for each genomic segment to guide its characterization. Results from SomatiCA can be further integrated with single nucleotide variations (SNVs) to get a better understanding of the tumor evolution. biocViews: Sequencing, CopyNumberVariation Author: Mengjie Chen , Hongyu Zhao Maintainer: Mengjie Chen source.ver: src/contrib/SomatiCA_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SomatiCA_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SomatiCA_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SomatiCA_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SomatiCA_1.6.0.tgz vignettes: vignettes/SomatiCA/inst/doc/SomatiCA.pdf, vignettes/SomatiCA/inst/doc/SomatiCAUserGuide.pdf vignetteTitles: SomatiCA Vignette, SomatiCAUserGuide.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SomatiCA/inst/doc/SomatiCA.R Package: SomaticSignatures Version: 1.0.1 Depends: R (>= 3.0.2) Imports: GenomeInfoDb, GenomicRanges, IRanges, VariantAnnotation, Biostrings, ggplot2, ggbio, stringr, reshape2, NMF, methods, pcaMethods, gtools Suggests: testthat, knitr, BiocStyle, parallel, BSgenome.Hsapiens.UCSC.hg19, SomaticCancerAlterations, h5vc, h5vcData, fastICA License: GPL-3 MD5sum: 5dafae55c15ab463e91c70cd94f5ab7e NeedsCompilation: no Title: Somatic Signatures Description: The SomaticSignatures package identifies mutational signatures of single nucleotide variants (SNVs). biocViews: Sequencing, SomaticMutation, Visualization, Clustering, HighThroughputSequencingData, Cancer, PrinicpalComponent, GenomicVariation, StatisticalMethod Author: Julian Gehring, with contribution of Bernd Fischer (EMBL Heidelberg) Maintainer: Julian Gehring URL: http://bioconductor.org/packages/release/bioc/html/SomaticSignatures.html, https://github.com/julian-gehring/SomaticSignatures VignetteBuilder: knitr source.ver: src/contrib/SomaticSignatures_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/SomaticSignatures_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.1/SomaticSignatures_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.1/SomaticSignatures_1.0.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SomaticSignatures_1.0.1.tgz vignettes: vignettes/SomaticSignatures/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SomaticSignatures/inst/doc/SomaticSignatures-vignette.R htmlDocs: vignettes/SomaticSignatures/inst/doc/SomaticSignatures-vignette.html htmlTitles: "SomaticSignatures - HTML" importsMe: Rariant Package: SpacePAC Version: 1.2.0 Depends: R(>= 2.15),iPAC Suggests: RUnit, BiocGenerics, rgl License: GPL-2 MD5sum: 70ecf3b63760bf70f1e925b50ddb799a NeedsCompilation: no Title: Identification of Mutational Clusters in 3D Protein Space via Simulation. Description: Identifies clustering of somatic mutations in proteins via a simulation approach while considering the protein's tertiary structure. biocViews: Clustering, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/SpacePAC_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SpacePAC_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SpacePAC_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SpacePAC_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SpacePAC_1.2.0.tgz vignettes: vignettes/SpacePAC/inst/doc/SpacePAC.pdf vignetteTitles: SpacePAC: Identifying mutational clusters in 3D protein space using simulation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SpacePAC/inst/doc/SpacePAC.R Package: spade Version: 1.12.2 Depends: R (>= 2.11), igraph, Rclusterpp Imports: Biobase, flowCore Suggests: flowViz License: GPL-2 Archs: i386, x64 MD5sum: 29dcc0e64445e44ea25ffa4677a9aad7 NeedsCompilation: yes Title: SPADE -- An analysis and visualization tool for Flow Cytometry Description: SPADE, or Spanning tree Progression of Density normalized Events, is an analysis and visualization tool for high dimensional flow cytometry data that organizes cells into hierarchies of related phenotypes. biocViews: FlowCytometry, GraphAndNetwork, GUI, Visualization, Clustering Author: M. Linderman, P. Qiu, E. Simonds, Z. Bjornson Maintainer: Zach Bjornson URL: http://cytospade.org source.ver: src/contrib/spade_1.12.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/spade_1.12.2.zip win64.binary.ver: bin/windows64/contrib/3.1/spade_1.12.2.zip mac.binary.ver: bin/macosx/contrib/3.1/spade_1.12.2.tgz vignettes: vignettes/spade/inst/doc/SPADE.pdf vignetteTitles: spade package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/spade/inst/doc/SPADE.R Package: SpeCond Version: 1.18.0 Depends: R (>= 2.10.0), mclust (>= 3.3.1), Biobase (>= 1.15.13), fields, hwriter (>= 1.1), RColorBrewer, methods License: LGPL (>=2) MD5sum: f6e79eb1bcc5920d5d5ad6810c45a827 NeedsCompilation: no Title: Condition specific detection from expression data Description: This package performs a gene expression data analysis to detect condition-specific genes. Such genes are significantly up- or down-regulated in a small number of conditions. It does so by fitting a mixture of normal distributions to the expression values. Conditions can be environmental conditions, different tissues, organs or any other sources that you wish to compare in terms of gene expression. biocViews: Microarray, DifferentialExpression, MultipleComparison, Clustering, ReportWriting Author: Florence Cavalli Maintainer: Florence Cavalli source.ver: src/contrib/SpeCond_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SpeCond_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SpeCond_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SpeCond_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SpeCond_1.18.0.tgz vignettes: vignettes/SpeCond/inst/doc/SpeCond.pdf vignetteTitles: SpeCond hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SpeCond/inst/doc/SpeCond.R Package: SPEM Version: 1.4.0 Depends: R (>= 2.15.1), Rsolnp, Biobase, methods License: GPL-2 MD5sum: e6fb8d80a3fc3182e3af6034337e6667 NeedsCompilation: no Title: S-system parameter estimation method Description: This package can optimize the parameter in S-system models given time series data biocViews: Network, NetworkInference, Software Author: Xinyi YANG Developer, Jennifer E. DENT Developer and Christine NARDINI Supervisor Maintainer: Xinyi YANG source.ver: src/contrib/SPEM_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SPEM_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SPEM_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SPEM_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SPEM_1.4.0.tgz vignettes: vignettes/SPEM/inst/doc/SPEM-package.pdf vignetteTitles: Vignette for SPEM hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SPEM/inst/doc/SPEM-package.R Package: SPIA Version: 2.16.0 Depends: R (>= 2.14.0), graphics, KEGGgraph Imports: graphics Suggests: graph, Rgraphviz, hgu133plus2.db License: GPL (>= 2) MD5sum: f4277df77b85734b43e2e968f81f0f87 NeedsCompilation: no Title: Signaling Pathway Impact Analysis (SPIA) using combined evidence of pathway over-representation and unusual signaling perturbations Description: This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study. biocViews: Microarray, GraphAndNetwork Author: Adi Laurentiu Tarca , Purvesh Kathri and Sorin Draghici Maintainer: Adi Laurentiu Tarca URL: http://bioinformatics.oxfordjournals.org/cgi/reprint/btn577v1 source.ver: src/contrib/SPIA_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SPIA_2.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SPIA_2.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SPIA_2.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SPIA_2.16.0.tgz vignettes: vignettes/SPIA/inst/doc/SPIA.pdf vignetteTitles: SPIA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SPIA/inst/doc/SPIA.R suggestsMe: graphite, KEGGgraph Package: spikeLI Version: 2.24.0 Imports: graphics, grDevices, stats, utils License: GPL-2 MD5sum: 9618f8f0c36917684c484a8636c285ce NeedsCompilation: no Title: Affymetrix Spike-in Langmuir Isotherm Data Analysis Tool Description: SpikeLI is a package that performs the analysis of the Affymetrix spike-in data using the Langmuir Isotherm. The aim of this package is to show the advantages of a physical-chemistry based analysis of the Affymetrix microarray data compared to the traditional methods. The spike-in (or Latin square) data for the HGU95 and HGU133 chipsets have been downloaded from the Affymetrix web site. The model used in the spikeLI package is described in details in E. Carlon and T. Heim, Physica A 362, 433 (2006). biocViews: Microarray, QualityControl Author: Delphine Baillon, Paul Leclercq , Sarah Ternisien, Thomas Heim, Enrico Carlon Maintainer: Enrico Carlon source.ver: src/contrib/spikeLI_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/spikeLI_2.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/spikeLI_2.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/spikeLI_2.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/spikeLI_2.24.0.tgz vignettes: vignettes/spikeLI/inst/doc/spikeLI.pdf vignetteTitles: spikeLI hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spikeLI/inst/doc/spikeLI.R Package: spkTools Version: 1.20.0 Depends: R (>= 2.7.0), Biobase (>= 2.5.5) Imports: Biobase (>= 2.5.5), graphics, grDevices, gtools, methods, RColorBrewer, stats, utils Suggests: xtable License: GPL (>= 2) MD5sum: 9bf3fb6080c5a06c88d412be8a8c00f7 NeedsCompilation: no Title: Methods for Spike-in Arrays Description: The package contains functions that can be used to compare expression measures on different array platforms. biocViews: Software, Technology, Microarray Author: Matthew N McCall , Rafael A Irizarry Maintainer: Matthew N McCall URL: http://bioconductor.org source.ver: src/contrib/spkTools_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/spkTools_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/spkTools_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/spkTools_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/spkTools_1.20.0.tgz vignettes: vignettes/spkTools/inst/doc/spkDoc.pdf vignetteTitles: spkTools: Spike-in Data Analysis and Visualization hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spkTools/inst/doc/spkDoc.R Package: splicegear Version: 1.36.0 Depends: R (>= 2.6.0), methods, Biobase(>= 2.5.5) Imports: annotate, Biobase, graphics, grDevices, grid, methods, utils, XML License: LGPL MD5sum: f0d8bc46167fa0906172f96a91f1b814 NeedsCompilation: no Title: splicegear Description: A set of tools to work with alternative splicing biocViews: Infrastructure, Transcription Author: Laurent Gautier Maintainer: Laurent Gautier source.ver: src/contrib/splicegear_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/splicegear_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/splicegear_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/splicegear_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/splicegear_1.36.0.tgz vignettes: vignettes/splicegear/inst/doc/splicegear.pdf vignetteTitles: splicegear Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/splicegear/inst/doc/splicegear.R Package: spliceR Version: 1.6.2 Depends: R (>= 2.15.0), methods, cummeRbund, rtracklayer, VennDiagram, RColorBrewer, plyr Imports: GenomicRanges, IRanges Suggests: BSgenome.Hsapiens.UCSC.hg19, BSgenome License: GPL (>=2) Archs: i386, x64 MD5sum: 2204a5b10fde1ff44701ce732807d71d NeedsCompilation: yes Title: Classification of alternative splicing and prediction of coding potential from RNA-seq data. Description: An R package for classification of alternative splicing and prediction of coding potential from RNA-seq data. biocViews: GeneExpression, Transcription, AlternativeSplicing, DifferentialExpression, DifferentialSplicing, Sequencing, Visualization Author: Johannes Waage , Kristoffer Vitting-Seerup Maintainer: Johannes Waage , Kristoffer Vitting-Seerup source.ver: src/contrib/spliceR_1.6.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/spliceR_1.6.2.zip win64.binary.ver: bin/windows64/contrib/3.1/spliceR_1.6.2.zip mac.binary.ver: bin/macosx/contrib/3.1/spliceR_1.6.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/spliceR_1.6.2.tgz vignettes: vignettes/spliceR/inst/doc/spliceR.pdf vignetteTitles: spliceR Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spliceR/inst/doc/spliceR.R Package: spliceSites Version: 1.2.0 Depends: methods,rbamtools,refGenome (>= 1.1.2),doBy,Biobase,Biostrings (>= 2.28.0),seqLogo Imports: BiocGenerics License: GPL-2 Archs: i386, x64 MD5sum: 4c88ad7d64199233690ccf3f975c2f00 NeedsCompilation: yes Title: Manages align gap positions from RNA-seq data Description: Align gap positions from RNA-seq data biocViews: RNASeq, GeneExpression, DifferentialExpression, Proteomics Author: Wolfgang Kaisers Maintainer: Wolfgang Kaisers source.ver: src/contrib/spliceSites_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/spliceSites_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/spliceSites_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/spliceSites_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/spliceSites_1.2.0.tgz vignettes: vignettes/spliceSites/inst/doc/spliceSites.pdf vignetteTitles: RNA-seq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spliceSites/inst/doc/spliceSites.R Package: SplicingGraphs Version: 1.4.1 Depends: BiocGenerics, IRanges (>= 1.17.43), GenomicRanges (>= 1.15.12), GenomicFeatures, GenomicAlignments (>= 1.0.3), Rgraphviz (>= 2.3.7) Imports: methods, utils, igraph, BiocGenerics, IRanges, GenomicRanges, GenomicFeatures, GenomicAlignments, graph, Rgraphviz Suggests: igraph, Gviz, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene, RNAseqData.HNRNPC.bam.chr14, RUnit License: Artistic-2.0 MD5sum: 6fef06690619db1f13c1847da986c84b NeedsCompilation: no Title: Create, manipulate, visualize splicing graphs, and assign RNA-seq reads to them Description: This package allows the user to create, manipulate, and visualize splicing graphs and their bubbles based on a gene model for a given organism. Additionally it allows the user to assign RNA-seq reads to the edges of a set of splicing graphs, and to summarize them in different ways. biocViews: Genetics, Annotation, DataRepresentation, Visualization, Sequencing, RNASeq, GeneExpression Author: D. Bindreither, M. Carlson, M. Morgan, H. Pages Maintainer: H. Pages source.ver: src/contrib/SplicingGraphs_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/SplicingGraphs_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/SplicingGraphs_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/SplicingGraphs_1.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SplicingGraphs_1.4.1.tgz vignettes: vignettes/SplicingGraphs/inst/doc/SplicingGraphs.pdf vignetteTitles: Splicing graphs and RNA-seq data hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SplicingGraphs/inst/doc/SplicingGraphs.R Package: splots Version: 1.30.0 Imports: grid, RColorBrewer License: LGPL MD5sum: 836c8e9d2a78bbb43b95acc11c8b1cc0 NeedsCompilation: no Title: Visualization of high-throughput assays in microtitre plate or slide format Description: The splots package provides the plotScreen function for visualising data in microtitre plate or slide format. biocViews: Visualization, Sequencing, MicrotitrePlateAssay Author: Wolfgang Huber, Oleg Sklyar Maintainer: Wolfgang Huber source.ver: src/contrib/splots_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/splots_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/splots_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/splots_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/splots_1.30.0.tgz vignettes: vignettes/splots/inst/doc/splotsHOWTO.pdf vignetteTitles: Visualization of data from assays in microtitre plate or slide format hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/splots/inst/doc/splotsHOWTO.R dependsOnMe: cellHTS2 importsMe: RNAinteract, RNAither Package: spotSegmentation Version: 1.38.0 Depends: R (>= 2.10), mclust License: GPL (>= 2) MD5sum: 732c5054444684acc2d83ecad6c06299 NeedsCompilation: no Title: Microarray Spot Segmentation and Gridding for Blocks of Microarray Spots Description: Spot segmentation via model-based clustering and gridding for blocks within microarray slides, as described in Li et al, Robust Model-Based Segmentation of Microarray Images, Technical Report no. 473, Department of Statistics, University of Washington. biocViews: Microarray, TwoChannel, QualityControl, Preprocessing Author: Qunhua Li, Chris Fraley, Adrian Raftery Department of Statistics, University of Washington Maintainer: Chris Fraley URL: http://www.stat.washington.edu/fraley source.ver: src/contrib/spotSegmentation_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/spotSegmentation_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/spotSegmentation_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/spotSegmentation_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/spotSegmentation_1.38.0.tgz vignettes: vignettes/spotSegmentation/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: SQUADD Version: 1.14.0 Depends: R (>= 2.11.0) Imports: graphics, grDevices, methods, RColorBrewer, stats, utils License: GPL (>=2) MD5sum: 987cde7ac4239a97b0a16eb140a2d5be NeedsCompilation: no Title: Add-on of the SQUAD Software Description: This package SQUADD is a SQUAD add-on. It permits to generate SQUAD simulation matrix, prediction Heat-Map and Correlation Circle from PCA analysis. biocViews: GraphAndNetwork, Network, Visualization Author: Martial Sankar, supervised by Christian Hardtke and Ioannis Xenarios Maintainer: Martial Sankar URL: http://www.unil.ch/dbmv/page21142_en.html source.ver: src/contrib/SQUADD_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SQUADD_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SQUADD_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SQUADD_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SQUADD_1.14.0.tgz vignettes: vignettes/SQUADD/inst/doc/SQUADD_ERK.pdf, vignettes/SQUADD/inst/doc/SQUADD.pdf vignetteTitles: SQUADD package, SQUADD package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SQUADD/inst/doc/SQUADD_ERK.R, vignettes/SQUADD/inst/doc/SQUADD.R Package: SRAdb Version: 1.18.0 Depends: RSQLite (>= 0.8-4) , graph, RCurl Imports: GEOquery Suggests: Rgraphviz License: Artistic-2.0 MD5sum: 25f4ae585b8fcb95d3faf0e07437fb1c NeedsCompilation: no Title: A compilation of metadata from NCBI SRA and tools Description: The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, and others. However, finding data of interest can be challenging using current tools. SRAdb is an attempt to make access to the metadata associated with submission, study, sample, experiment and run much more feasible. This is accomplished by parsing all the NCBI SRA metadata into a SQLite database that can be stored and queried locally. Fulltext search in the package make querying metadata very flexible and powerful. fastq and sra files can be downloaded for doing alignment locally. Beside ftp protocol, the SRAdb has funcitons supporting fastp protocol (ascp from Aspera Connect) for faster downloading large data files over long distance. The SQLite database is updated regularly as new data is added to SRA and can be downloaded at will for the most up-to-date metadata. biocViews: Infrastructure, Sequencing, DataImport Author: Jack Zhu and Sean Davis Maintainer: Jack Zhu URL: http://gbnci.abcc.ncifcrf.gov/sra/ source.ver: src/contrib/SRAdb_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SRAdb_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SRAdb_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SRAdb_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SRAdb_1.18.0.tgz vignettes: vignettes/SRAdb/inst/doc/SRAdb.pdf vignetteTitles: Using SRAdb to Query the Sequence Read Archive hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SRAdb/inst/doc/SRAdb.R Package: sRAP Version: 1.4.2 Depends: WriteXLS Imports: gplots, pls, ROCR, qvalue License: GPL-3 MD5sum: da87fc6df5ae7e295e466b3664b0a2f2 NeedsCompilation: no Title: Simplified RNA-Seq Analysis Pipeline Description: This package provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data. biocViews: GeneExpression, RNAseq, Microarray, Preprocessing, QualityControl, Statistics, DifferentialExpression, Visualization, GeneSetEnrichment, GO Author: Charles Warden Maintainer: Charles Warden source.ver: src/contrib/sRAP_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/sRAP_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/sRAP_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/sRAP_1.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sRAP_1.4.2.tgz vignettes: vignettes/sRAP/inst/doc/sRAP.pdf vignetteTitles: sRAP Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sRAP/inst/doc/sRAP.R Package: sscore Version: 1.36.0 Depends: R (>= 1.8.0), affy, affyio Suggests: affydata License: GPL (>= 2) MD5sum: 6dc0e952ebe683f8802bd84d74a1927d NeedsCompilation: no Title: S-Score Algorithm for Affymetrix Oligonucleotide Microarrays Description: This package contains an implementation of the S-Score algorithm as described by Zhang et al (2002). biocViews: DifferentialExpression Author: Richard Kennedy , based on C++ code from Li Zhang and Borland Delphi code from Robnet Kerns . Maintainer: Richard Kennedy URL: http://home.att.net/~richard-kennedy/professional.html source.ver: src/contrib/sscore_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sscore_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sscore_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sscore_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sscore_1.36.0.tgz vignettes: vignettes/sscore/inst/doc/sscore.pdf vignetteTitles: SScore primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sscore/inst/doc/sscore.R Package: sSeq Version: 1.2.0 Depends: R (>= 3.0), caTools, RColorBrewer License: GPL (>= 3) MD5sum: d8f76ad896e9b2aa14a3c8618f262447 NeedsCompilation: no Title: Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size Description: The purpose of this package is to discover the genes that are differentially expressed between two conditions in RNA-seq experiments. Gene expression is measured in counts of transcripts and modeled with the Negative Binomial (NB) distribution using a shrinkage approach for dispersion estimation. The method of moment (MM) estimates for dispersion are shrunk towards an estimated target, which minimizes the average squared difference between the shrinkage estimates and the initial estimates. The exact per-gene probability under the NB model is calculated, and used to test the hypothesis that the expected expression of a gene in two conditions identically follow a NB distribution. biocViews: RNASeq Author: Danni Yu , Wolfgang Huber and Olga Vitek Maintainer: Danni Yu source.ver: src/contrib/sSeq_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sSeq_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sSeq_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sSeq_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sSeq_1.2.0.tgz vignettes: vignettes/sSeq/inst/doc/sSeq.pdf vignetteTitles: sSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sSeq/inst/doc/sSeq.R Package: ssize Version: 1.38.0 Depends: gdata, xtable License: LGPL MD5sum: 9b05cd974d7edf7eef28c02b608f2a9f NeedsCompilation: no Title: Estimate Microarray Sample Size Description: Functions for computing and displaying sample size information for gene expression arrays. biocViews: Microarray, DifferentialExpression Author: Gregory R. Warnes, Peng Liu, and Fasheng Li Maintainer: Gregory R. Warnes source.ver: src/contrib/ssize_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ssize_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ssize_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ssize_1.38.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ssize_1.38.0.tgz vignettes: vignettes/ssize/inst/doc/ssize.pdf vignetteTitles: package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ssize/inst/doc/ssize.R suggestsMe: oneChannelGUI Package: SSPA Version: 2.4.0 Depends: R (>= 2.12), methods, qvalue, lattice, limma Imports: graphics, stats Suggests: BiocStyle, genefilter, edgeR, DESeq License: GPL (>= 2) Archs: i386, x64 MD5sum: 8253a9b489e650e35915ce50f9d403fb NeedsCompilation: yes Title: General Sample Size and Power Analysis for Microarray and Next-Generation Sequencing Data Description: General Sample size and power analysis for microarray and next-generation sequencing data. biocViews: Microarray, StatisticalMethod Author: Maarten van Iterson Maintainer: Maarten van Iterson URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html source.ver: src/contrib/SSPA_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SSPA_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SSPA_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SSPA_2.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SSPA_2.4.0.tgz vignettes: vignettes/SSPA/inst/doc/SSPA.pdf vignetteTitles: SSPA Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SSPA/inst/doc/SSPA.R Package: staRank Version: 1.6.0 Depends: methods, cellHTS2, R (>= 2.10) License: GPL MD5sum: aa0ac20e85793eb0fa937a0648b5a304 NeedsCompilation: no Title: Stability Ranking Description: Detecting all relevant variables from a data set is challenging, especially when only few samples are available and data is noisy. Stability ranking provides improved variable rankings of increased robustness using resampling or subsampling. biocViews: MultipleComparison, CellBiology, CellBasedAssays, MicrotitrePlateAssay Author: Juliane Siebourg, Niko Beerenwinkel Maintainer: Juliane Siebourg source.ver: src/contrib/staRank_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/staRank_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/staRank_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/staRank_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/staRank_1.6.0.tgz vignettes: vignettes/staRank/inst/doc/staRank.pdf vignetteTitles: Using staRank hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/staRank/inst/doc/staRank.R Package: Starr Version: 1.20.0 Depends: Ringo, affy, affxparser Imports: pspline, MASS, zlibbioc License: Artistic-2.0 Archs: i386, x64 MD5sum: 04a8f87bfe3472d8d6e18c2f7f67d9ec NeedsCompilation: yes Title: Simple tiling array analysis of Affymetrix ChIP-chip data Description: Starr facilitates the analysis of ChIP-chip data, in particular that of Affymetrix tiling arrays. The package provides functions for data import, quality assessment, data visualization and exploration. Furthermore, it includes high-level analysis features like association of ChIP signals with annotated features, correlation analysis of ChIP signals and other genomic data (e.g. gene expression), peak-finding with the CMARRT algorithm and comparative display of multiple clusters of ChIP-profiles. It uses the basic Bioconductor classes ExpressionSet and probeAnno for maximum compatibility with other software on Bioconductor. All functions from Starr can be used to investigate preprocessed data from the Ringo package, and vice versa. An important novel tool is the the automated generation of correct, up-to-date microarray probe annotation (bpmap) files, which relies on an efficient mapping of short sequences (e.g. the probe sequences on a microarray) to an arbitrary genome. biocViews: Microarray,OneChannel,DataImport,QualityControl,Preprocessing,ChIPchip Author: Benedikt Zacher, Johannes Soeding, Pei Fen Kuan, Matthias Siebert, Achim Tresch Maintainer: Benedikt Zacher source.ver: src/contrib/Starr_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Starr_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Starr_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Starr_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Starr_1.20.0.tgz vignettes: vignettes/Starr/inst/doc/Starr.pdf vignetteTitles: Simple tiling array analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Starr/inst/doc/Starr.R Package: stepNorm Version: 1.36.0 Depends: R (>= 1.8.0), marray, methods Imports: marray, MASS, methods, stats License: LGPL MD5sum: 38485d4e8ecd0c4d3411eb4c013560b4 NeedsCompilation: no Title: Stepwise normalization functions for cDNA microarrays Description: Stepwise normalization functions for cDNA microarray data. biocViews: Microarray, TwoChannel, Preprocessing Author: Yuanyuan Xiao , Yee Hwa (Jean) Yang Maintainer: Yuanyuan Xiao URL: http://www.biostat.ucsf.edu/jean/ source.ver: src/contrib/stepNorm_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/stepNorm_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/stepNorm_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/stepNorm_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/stepNorm_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: stepwiseCM Version: 1.10.0 Depends: R (>= 2.14), randomForest, MAclinical, tspair, pamr, snowfall, glmpath, penalized, e1071, Biobase License: GPL (>2) MD5sum: ebe854cf34af3b07a1e42885cf518e78 NeedsCompilation: no Title: Stepwise Classification of Cancer Samples using High-dimensional Data Sets Description: Stepwise classification of cancer samples using multiple data sets. This package implements the classification strategy using two heterogeneous data sets without actually combining them. Package uses the data type for which full measurements are available at the first stage, and the data type for which only partial measurements are available at the second stage. For incoming new samples package quantifies how much improvement will be obtained if covariates of new samples for the data types at the second stage are measured. This packages suits for the application where study goal is not only obtain high classification accuracy, but also requires economically cheap classifier. biocViews: Classification, Microarray, Integration Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/stepwiseCM_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/stepwiseCM_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/stepwiseCM_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/stepwiseCM_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/stepwiseCM_1.10.0.tgz vignettes: vignettes/stepwiseCM/inst/doc/stepwiseCM.pdf vignetteTitles: stepwiseCM hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/stepwiseCM/inst/doc/stepwiseCM.R Package: Streamer Version: 1.10.0 Imports: methods, graph, RBGL, parallel, BiocGenerics Suggests: RUnit, Rsamtools (>= 1.5.53), GenomicAlignments, Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: 66de8a98c8e8c47f57e9067832790b01 NeedsCompilation: yes Title: Enabling stream processing of large files Description: Large data files can be difficult to work with in R, where data generally resides in memory. This package encourages a style of programming where data is 'streamed' from disk into R via a `producer' and through a series of `consumers' that, typically reduce the original data to a manageable size. The package provides useful Producer and Consumer stream components for operations such as data input, sampling, indexing, and transformation; see package?Streamer for details. biocViews: Infrastructure, DataImport Author: Martin Morgan, Nishant Gopalakrishnan Maintainer: Martin Morgan source.ver: src/contrib/Streamer_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Streamer_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Streamer_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Streamer_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Streamer_1.10.0.tgz vignettes: vignettes/Streamer/inst/doc/Streamer.pdf vignetteTitles: Streamer: A simple example hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Streamer/inst/doc/Streamer.R importsMe: plethy Package: STRINGdb Version: 1.3.2 Depends: R (>= 2.14.0), png, sqldf, plyr, igraph, RCurl, plotrix, methods Suggests: RUnit, BiocGenerics License: GPL-2 MD5sum: dfad3e5fdd47f370501a54c9d08da139 NeedsCompilation: no Title: STRINGdb (Search Tool for the Retrieval of Interacting proteins database) Description: The STRINGdb package provides a user-friendly interface to the STRING protein-protein interactions database ( http://www.string-db.org ). biocViews: Network Author: Andrea Franceschini Maintainer: Andrea Franceschini , Alexander Roth , Christian Von Mering , Michael Kuhn , Lars J Jensen source.ver: src/contrib/STRINGdb_1.3.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/STRINGdb_1.3.2.zip win64.binary.ver: bin/windows64/contrib/3.1/STRINGdb_1.3.2.zip mac.binary.ver: bin/macosx/contrib/3.1/STRINGdb_1.3.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/STRINGdb_1.3.2.tgz vignettes: vignettes/STRINGdb/inst/doc/STRINGdb.pdf vignetteTitles: STRINGdb Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/STRINGdb/inst/doc/STRINGdb.R dependsOnMe: scsR Package: supraHex Version: 1.2.0 Depends: R (>= 3.0.2), hexbin Imports: ape, MASS License: GPL-2 MD5sum: f8b848d2374190d367bc502eedc6a9ba NeedsCompilation: no Title: A supra-hexagonal map for analysing tabular omics data Description: A supra-hexagonal map is a giant hexagon on a 2-dimensional grid seamlessly consisting of smaller hexagons. It is supposed to train, analyse and visualise a high-dimensional omics input data. The supraHex is able to carry out gene clustering/meta-clustering and sample correlation, plus intuitive visualisations to facilitate exploratory analysis. More importantly, it allows for overlaying additional data onto the trained map to explore relations between input and additional data. So with supraHex, it is also possible to carry out multilayer omics data comparisons. Newly added utilities are advanced heatmap visualisation and tree-based analysis of sample relationships. Uniquely to this package, users can ultrafastly understand any tabular omics data, both scientifically and artistically, especially in a sample-specific fashion but without loss of information on large genes (see http://www.ncbi.nlm.nih.gov/pubmed/24309102). biocViews: Bioinformatics, Clustering, Visualization, GeneExpression Author: Hai Fang and Julian Gough Maintainer: Hai Fang URL: http://supfam.org/supraHex source.ver: src/contrib/supraHex_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/supraHex_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/supraHex_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/supraHex_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/supraHex_1.2.0.tgz vignettes: vignettes/supraHex/inst/doc/supraHex_vignettes.pdf vignetteTitles: supraHex User Manual hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/supraHex/inst/doc/supraHex_vignettes.R Package: survcomp Version: 1.14.0 Depends: R (>= 2.10), survival, prodlim Imports: ipred, SuppDists, KernSmooth, survivalROC, bootstrap, grid, rmeta Suggests: Hmisc, CPE, clinfun, survJamda, Biobase, xtable License: Artistic-2.0 Archs: i386, x64 MD5sum: dc816580fb2c8adc3c51a981c5ea8913 NeedsCompilation: yes Title: Performance Assessment and Comparison for Survival Analysis Description: R package providing functions to assess and to compare the performance of risk prediction (survival) models. biocViews: GeneExpression, DifferentialExpression, Visualization Author: Benjamin Haibe-Kains, Markus Schroeder, Catharina Olsen, Christos Sotiriou, Gianluca Bontempi, John Quackenbush Maintainer: Benjamin Haibe-Kains , Markus Schroeder , Catharina Olsen URL: http://compbio.dfci.harvard.edu source.ver: src/contrib/survcomp_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/survcomp_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/survcomp_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/survcomp_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/survcomp_1.14.0.tgz vignettes: vignettes/survcomp/inst/doc/survcomp.pdf vignetteTitles: SurvComp: a package for performance assessment and comparison for survival analysis hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/survcomp/inst/doc/survcomp.R dependsOnMe: genefu suggestsMe: metaseqR Package: Sushi Version: 1.0.0 Depends: R (>= 2.10), zoo,biomaRt Imports: graphics, grDevices License: GPL (>= 2) MD5sum: 7e83e9be9a7b84a4ed5ffa3fa2a09cf1 NeedsCompilation: no Title: Tools for visualizing genomics data Description: Flexible, quantitative, and integrative genomic visualizations for publication-quality multi-panel figures biocViews: DataRepresentation, Visualization, Genetics, Sequencing, Infrastructure, Author: Douglas H Phanstiel Maintainer: Douglas H Phanstiel source.ver: src/contrib/Sushi_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Sushi_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Sushi_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Sushi_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Sushi_1.0.0.tgz vignettes: vignettes/Sushi/inst/doc/Sushi.pdf vignetteTitles: Sushi hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Sushi/inst/doc/Sushi.R Package: sva Version: 3.10.0 Depends: R (>= 2.8), corpcor, mgcv Imports: graphics, stats Suggests: limma,pamr,bladderbatch License: Artistic-2.0 Archs: i386, x64 MD5sum: 11bf3e771369fc49964e20df9bf3961a NeedsCompilation: yes Title: Surrogate Variable Analysis Description: The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensional data sets. Surrogate variables are covariates constructed directly from high-dimensional data (like gene expression/RNA sequencing/methylation/brain imaging data) that can be used in subsequent analyses to adjust for unknown, unmodeled, or latent sources of noise. The sva package can be used to remove artifacts in two ways: (1) identifying and estimating surrogate variables for unknown sources of variation in high-throughput experiments (Leek and Storey 2007 PLoS Genetics,2008 PNAS) and (2) directly removing known batch effects using ComBat (Johnson et al. 2007 Biostatistics). Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008 PNAS or Leek et al. 2011 Nat. Reviews Genetics). Surrogate variable analysis and ComBat were developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved. biocViews: Microarray, StatisticalMethod, Preprocessing, MultipleComparison Author: Jeffrey T. Leek , W. Evan Johnson , Hilary S. Parker , Andrew E. Jaffe , John D. Storey , Maintainer: Jeffrey T. Leek source.ver: src/contrib/sva_3.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/sva_3.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/sva_3.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/sva_3.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/sva_3.10.0.tgz vignettes: vignettes/sva/inst/doc/sva.pdf vignetteTitles: bladderbatchTutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sva/inst/doc/sva.R dependsOnMe: SCAN.UPC importsMe: ChAMP, charm, trigger Package: SwimR Version: 1.2.0 Depends: R (>= 3.0.0), methods, gplots (>= 2.10.1), heatmap.plus (>= 1.3), signal (>= 0.7), R2HTML (>= 2.2.1) Imports: methods License: LGPL-2 MD5sum: 6b5d9ddc0e607f5ea7f491d4b3ee9c88 NeedsCompilation: no Title: SwimR: A Suite of Analytical Tools for Quantification of C. elegans Swimming Behavior Description: SwimR is an R-based suite that calculates, analyses, and plots the frequency of C. elegans swimming behavior over time. It places a particular emphasis on identifying paralysis and quantifying the kinetic elements of paralysis during swimming. Data is input to SwipR from a custom built program that fits a 5 point morphometric spine to videos of single worms swimming in a buffer called Worm Tracker. biocViews: Visualization Author: Jing Wang , Andrew Hardaway and Bing Zhang Maintainer: Randy Blakely source.ver: src/contrib/SwimR_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/SwimR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/SwimR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/SwimR_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/SwimR_1.2.0.tgz vignettes: vignettes/SwimR/inst/doc/SwimR.pdf vignetteTitles: SwimR hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SwimR/inst/doc/SwimR.R Package: synapter Version: 1.6.0 Depends: R (>= 2.15), methods, MSnbase Imports: hwriter, tcltk, tcltk2, RColorBrewer, lattice, qvalue, multtest, utils, Biobase, knitr, Biostrings, cleaver, BiocParallel Suggests: synapterdata, xtable License: GPL-2 MD5sum: 4a81ce20ceb066d7215b9146e909005b NeedsCompilation: no Title: Label-free data analysis pipeline for optimal identification and quantitation Description: The synapter package provides functionality to reanalyse label-free proteomics data acquired on a Synapt G2 mass spectrometer. One or several runs, possibly processed with additional ion mobility separation to increase identification accuracy can be combined to other quantitation files to maximise identification and quantitation accuracy. biocViews: MassSpectrometry, Proteomics, GUI Author: Laurent Gatto, Nick J. Bond and Pavel V. Shliaha with contributions from Sebastian Gibb. Maintainer: Laurent Gatto URL: http://lgatto.github.com/synapter/ VignetteBuilder: knitr source.ver: src/contrib/synapter_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/synapter_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/synapter_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/synapter_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/synapter_1.6.0.tgz vignettes: vignettes/synapter/inst/doc/synapter.pdf vignetteTitles: Combining HDMSe/MSe data using 'synapter' to optimise identification and quantitation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/synapter/inst/doc/synapter.R suggestsMe: pRoloc Package: TargetScore Version: 1.2.0 Depends: pracma, Matrix Suggests: TargetScoreData, gplots, Biobase, GEOquery License: GPL-2 MD5sum: abaf217cb7043376dfb451a522344689 NeedsCompilation: no Title: TargetScore: Infer microRNA targets using microRNA-overexpression data and sequence information Description: Infer the posterior distributions of microRNA targets by probabilistically modelling the likelihood microRNA-overexpression fold-changes and sequence-based scores. Variaitonal Bayesian Gaussian mixture model (VB-GMM) is applied to log fold-changes and sequence scores to obtain the posteriors of latent variable being the miRNA targets. The final targetScore is computed as the sigmoid-transformed fold-change weighted by the averaged posteriors of target components over all of the features. biocViews: miRNA Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/software.html source.ver: src/contrib/TargetScore_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TargetScore_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TargetScore_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TargetScore_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TargetScore_1.2.0.tgz vignettes: vignettes/TargetScore/inst/doc/TargetScore.pdf vignetteTitles: TargetScore: Infer microRNA targets using microRNA-overexpression data and sequence information hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TargetScore/inst/doc/TargetScore.R Package: TargetSearch Version: 1.20.0 Depends: R (>= 2.7.0), mzR Imports: graphics, grDevices, methods, stats, tcltk, utils Suggests: TargetSearchData License: GPL (>= 2) Archs: i386, x64 MD5sum: 2236d72c8fe72ca19724709f0dc408de NeedsCompilation: yes Title: A package for the analysis of GC-MS metabolite profiling data. Description: This packages provides a targeted pre-processing method for GC-MS data. biocViews: MassSpectrometry,Preprocessing Author: Alvaro Cuadros-Inostroza , Jan Lisec , Henning Redestig , Matt Hannah Maintainer: Alvaro Cuadros-Inostroza source.ver: src/contrib/TargetSearch_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TargetSearch_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TargetSearch_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TargetSearch_1.20.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TargetSearch_1.20.0.tgz vignettes: vignettes/TargetSearch/inst/doc/RICorrection.pdf, vignettes/TargetSearch/inst/doc/TargetSearch.pdf vignetteTitles: RI correction, The TargetSearch Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TargetSearch/inst/doc/RICorrection.R, vignettes/TargetSearch/inst/doc/TargetSearch.R Package: TCC Version: 1.4.0 Depends: R (>= 2.15), methods, DESeq, DESeq2, edgeR, baySeq, ROC Imports: samr Suggests: RUnit, BiocGenerics Enhances: snow License: GPL-2 MD5sum: f55cfdfc3efdb088f35fd0899834c897 NeedsCompilation: no Title: TCC: Differential expression analysis for tag count data with robust normalization strategies Description: This package provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in depended packages. biocViews: Sequencing, DifferentialExpression, RNASeq Author: Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer: Jianqiang Sun , Tomoaki Nishiyama source.ver: src/contrib/TCC_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TCC_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TCC_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TCC_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TCC_1.4.0.tgz vignettes: vignettes/TCC/inst/doc/TCC.pdf vignetteTitles: TCC hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TCC/inst/doc/TCC.R suggestsMe: compcodeR Package: TDARACNE Version: 1.14.0 Depends: GenKern, Rgraphviz, Biobase License: GPL-2 MD5sum: 673f6fc29eb54f9a04610244844aa307 NeedsCompilation: no Title: Network reverse engineering from time course data. Description: To infer gene networks from time-series measurements is a current challenge into bioinformatics research area. In order to detect dependencies between genes at different time delays, we propose an approach to infer gene regulatory networks from time-series measurements starting from a well known algorithm based on information theory. The proposed algorithm is expected to be useful in reconstruction of small biological directed networks from time course data. biocViews: Microarray, TimeCourse Author: Zoppoli P.,Morganella S., Ceccarelli M. Maintainer: Zoppoli Pietro source.ver: src/contrib/TDARACNE_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TDARACNE_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TDARACNE_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TDARACNE_1.14.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TDARACNE_1.14.0.tgz vignettes: vignettes/TDARACNE/inst/doc/TDARACNE.pdf vignetteTitles: TDARACNE hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TDARACNE/inst/doc/TDARACNE.R Package: TEQC Version: 3.4.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.5), Rsamtools, hwriter Imports: Biobase (>= 2.15.1) License: GPL (>= 2) MD5sum: f1385a0a3d41d9f2e88f57d8647efbd0 NeedsCompilation: no Title: Quality control for target capture experiments Description: Target capture experiments combine hybridization-based (in solution or on microarrays) capture and enrichment of genomic regions of interest (e.g. the exome) with high throughput sequencing of the captured DNA fragments. This package provides functionalities for assessing and visualizing the quality of the target enrichment process, like specificity and sensitivity of the capture, per-target read coverage and so on. biocViews: QualityControl, Microarray, Sequencing, Genetics Author: M. Hummel, S. Bonnin, E. Lowy, G. Roma Maintainer: Manuela Hummel source.ver: src/contrib/TEQC_3.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TEQC_3.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TEQC_3.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TEQC_3.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TEQC_3.4.0.tgz vignettes: vignettes/TEQC/inst/doc/TEQC.pdf vignetteTitles: TEQC hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TEQC/inst/doc/TEQC.R Package: ternarynet Version: 1.8.0 Depends: R (>= 2.10.0), methods Imports: utils, igraph License: GPL (>= 2) Archs: i386, x64 MD5sum: 90da0c88dd2fa9bca9d6c02897e5e04e NeedsCompilation: yes Title: Ternary Network Estimation Description: A computational Bayesian approach to ternary gene regulatory network estimation from gene perturbation experiments. biocViews: Software, CellBiology, GraphAndNetwork Author: Matthew N. McCall , Anthony Almudevar Maintainer: Matthew N. McCall source.ver: src/contrib/ternarynet_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/ternarynet_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/ternarynet_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/ternarynet_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/ternarynet_1.8.0.tgz vignettes: vignettes/ternarynet/inst/doc/ternarynet.pdf vignetteTitles: ternarynet: A Computational Bayesian Approach to Ternary Network Estimation hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ternarynet/inst/doc/ternarynet.R Package: TFBSTools Version: 1.2.0 Depends: R (>= 3.0.1) Imports: Biostrings(>= 2.29.19), RSQLite(>= 0.11.4), seqLogo, GenomicRanges(>= 1.13.50), caTools(>= 1.14), XVector(>= 0.2.0), rtracklayer(>= 1.22.0), BSgenome(>= 1.30.0), IRanges(>= 1.19.38), methods, gtools(>= 3.0.0), CNEr(>= 0.99.8), BiocParallel(>= 0.5.6), DirichletMultinomial(>= 1.5.1) Suggests: JASPAR2014(>= 0.99.3), RUnit, BiocGenerics License: GPL-2 Archs: i386, x64 MD5sum: 71c5d3ded26380665a9aeb98f93ee452 NeedsCompilation: yes Title: Software package for transcription factor binding site (TFBS) analysis Description: TFBSTools is a package for the analysis and manipulation of transcription factor binding sites and transcription factor profile matrices. biocViews: MotifAnnotation, GeneRegulation, MotifDiscovery Author: Ge Tan Maintainer: Ge Tan URL: http://jaspar.genereg.net/ SystemRequirements: meme source.ver: src/contrib/TFBSTools_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TFBSTools_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TFBSTools_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TFBSTools_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TFBSTools_1.2.0.tgz vignettes: vignettes/TFBSTools/inst/doc/TFBSTools.pdf vignetteTitles: TFBSTools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TFBSTools/inst/doc/TFBSTools.R Package: tigre Version: 1.18.0 Depends: R (>= 2.11.0), BiocGenerics, Biobase Imports: methods, AnnotationDbi, gplots, graphics, puma, stats, utils, annotate, DBI, RSQLite Suggests: drosgenome1.db, lumi License: AGPL-3 Archs: i386, x64 MD5sum: e274751a465dbacb3a008a92e7c8cd90 NeedsCompilation: yes Title: Transcription factor Inference through Gaussian process Reconstruction of Expression Description: The tigre package implements our methodology of Gaussian process differential equation models for analysis of gene expression time series from single input motif networks. The package can be used for inferring unobserved transcription factor (TF) protein concentrations from expression measurements of known target genes, or for ranking candidate targets of a TF. biocViews: Microarray, TimeCourse, GeneExpression, Transcription, GeneRegulation, NetworkInference, Bayesian Author: Antti Honkela, Pei Gao, Jonatan Ropponen, Miika-Petteri Matikainen, Magnus Rattray, Neil D. Lawrence Maintainer: Antti Honkela URL: http://www.bioinf.manchester.ac.uk/resources/tiger/ source.ver: src/contrib/tigre_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tigre_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tigre_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tigre_1.18.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tigre_1.18.0.tgz vignettes: vignettes/tigre/inst/doc/tigre.pdf, vignettes/tigre/inst/doc/tigre_quick.pdf vignetteTitles: tigre User Guide, tigre Quick Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tigre/inst/doc/tigre_quick.R, vignettes/tigre/inst/doc/tigre.R Package: tilingArray Version: 1.42.0 Depends: R (>= 2.11.0), Biobase, methods, pixmap Imports: strucchange, affy, vsn, genefilter, RColorBrewer, grid, stats4 License: Artistic-2.0 Archs: i386, x64 MD5sum: 81a5cfcc3e88857ddd8fd397176f9447 NeedsCompilation: yes Title: Transcript mapping with high-density oligonucleotide tiling arrays Description: The package provides functionality that can be useful for the analysis of high-density tiling microarray data (such as from Affymetrix genechips) for measuring transcript abundance and architecture. The main functionalities of the package are: 1. the class 'segmentation' for representing partitionings of a linear series of data; 2. the function 'segment' for fitting piecewise constant models using a dynamic programming algorithm that is both fast and exact; 3. the function 'confint' for calculating confidence intervals using the strucchange package; 4. the function 'plotAlongChrom' for generating pretty plots; 5. the function 'normalizeByReference' for probe-sequence dependent response adjustment from a (set of) reference hybridizations. biocViews: Microarray, OneChannel, Preprocessing, Visualization Author: Wolfgang Huber, Zhenyu Xu, Joern Toedling with contributions from Matt Ritchie Maintainer: Zhenyu Xu source.ver: src/contrib/tilingArray_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tilingArray_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tilingArray_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tilingArray_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tilingArray_1.42.0.tgz vignettes: vignettes/tilingArray/inst/doc/assessNorm.pdf, vignettes/tilingArray/inst/doc/costMatrix.pdf, vignettes/tilingArray/inst/doc/findsegments.pdf, vignettes/tilingArray/inst/doc/plotAlongChrom.pdf, vignettes/tilingArray/inst/doc/segmentation.pdf vignetteTitles: Normalisation with the normalizeByReference function in the tilingArray package, Supplement. Calculation of the cost matrix, Introduction to using the segment function to fit a piecewise constant curve, Introduction to the plotAlongChrom function, Segmentation demo hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tilingArray/inst/doc/assessNorm.R, vignettes/tilingArray/inst/doc/costMatrix.R, vignettes/tilingArray/inst/doc/findsegments.R, vignettes/tilingArray/inst/doc/plotAlongChrom.R, vignettes/tilingArray/inst/doc/segmentation.R importsMe: ADaCGH2, snapCGH Package: timecourse Version: 1.36.0 Depends: R (>= 2.1.1), MASS, methods Imports: Biobase, graphics, limma (>= 1.8.6), MASS, marray, methods, stats License: LGPL MD5sum: 411753756e56d054647dbb6e8d4cb36d NeedsCompilation: no Title: Statistical Analysis for Developmental Microarray Time Course Data Description: Functions for data analysis and graphical displays for developmental microarray time course data. biocViews: Microarray, TimeCourse, DifferentialExpression Author: Yu Chuan Tai Maintainer: Yu Chuan Tai URL: http://www.bioconductor.org source.ver: src/contrib/timecourse_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/timecourse_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/timecourse_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/timecourse_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/timecourse_1.36.0.tgz vignettes: vignettes/timecourse/inst/doc/timecourse.pdf vignetteTitles: timecourse manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/timecourse/inst/doc/timecourse.R Package: TitanCNA Version: 1.0.0 Depends: R (>= 3.0.1), foreach (>= 1.4.0), HMMcopy (>= 1.2.0) License: file LICENSE Archs: i386, x64 MD5sum: aac773f2dc265302601c485ca1f5db99 NeedsCompilation: yes Title: Subclonal copy number and LOH prediction whole genome sequencing of tumours Description: Hidden Markov model to segment and predict regions of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH), and estimate cellular prevalenece of clonal clusters in tumour whole genome sequencing data. biocViews: Sequencing, WholeGenome, DNASeq, ExomeSeq, StatisticalMethod, CopyNumberVariation, HiddenMarkovModel, Genetics, GenomicVariation Author: Gavin Ha, Sohrab P Shah Maintainer: Gavin Ha , Sohrab P Shah source.ver: src/contrib/TitanCNA_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TitanCNA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TitanCNA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TitanCNA_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TitanCNA_1.0.0.tgz vignettes: vignettes/TitanCNA/inst/doc/TitanCNA.pdf vignetteTitles: TitanCNA hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/TitanCNA/inst/doc/TitanCNA.R Package: tkWidgets Version: 1.42.0 Depends: R (>= 2.0.0), methods, widgetTools (>= 1.1.7), DynDoc (>= 1.3.0), tools Suggests: Biobase, hgu95av2 License: Artistic-2.0 MD5sum: 291747843fa5466ae8f4e635b907f40f NeedsCompilation: no Title: R based tk widgets Description: Widgets to provide user interfaces. tcltk should have been installed for the widgets to run. biocViews: Infrastructure Author: J. Zhang Maintainer: J. Zhang source.ver: src/contrib/tkWidgets_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tkWidgets_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tkWidgets_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tkWidgets_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tkWidgets_1.42.0.tgz vignettes: vignettes/tkWidgets/inst/doc/importWizard.pdf, vignettes/tkWidgets/inst/doc/tkWidgets.pdf vignetteTitles: tkWidgets importWizard, tkWidgets contents hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tkWidgets/inst/doc/importWizard.R, vignettes/tkWidgets/inst/doc/tkWidgets.R dependsOnMe: oneChannelGUI importsMe: Mfuzz, OLINgui suggestsMe: affy, affyQCReport, annotate, Biobase, genefilter, marray Package: topGO Version: 2.16.0 Depends: R (>= 2.10.0), methods, graph (>= 1.14.0), Biobase (>= 2.0.0), GO.db (>= 2.3.0), AnnotationDbi (>= 1.7.19), SparseM (>= 0.73) Imports: methods, graph, Biobase, SparseM, AnnotationDbi, lattice Suggests: ALL, hgu95av2.db, hgu133a.db, genefilter, xtable, multtest, Rgraphviz, globaltest License: LGPL MD5sum: 6cbf5c7d02f32cc48ffe18e542a1644c NeedsCompilation: no Title: topGO: Enrichment analysis for Gene Ontology Description: topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied. biocViews: Microarray, Visualization Author: Adrian Alexa, Jorg Rahnenfuhrer Maintainer: Adrian Alexa source.ver: src/contrib/topGO_2.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/topGO_2.16.0.zip win64.binary.ver: bin/windows64/contrib/3.1/topGO_2.16.0.zip mac.binary.ver: bin/macosx/contrib/3.1/topGO_2.16.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/topGO_2.16.0.tgz vignettes: vignettes/topGO/inst/doc/topGO.pdf vignetteTitles: topGO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/topGO/inst/doc/topGO.R dependsOnMe: RNAither, tRanslatome importsMe: GOSim suggestsMe: Ringo Package: trackViewer Version: 1.0.2 Depends: R (>= 3.1.0), methods, GenomicRanges, grid, gWidgetstcltk Imports: GenomicAlignments, GenomicFeatures, Gviz, pbapply, Rsamtools, rtracklayer, scales Suggests: biomaRt, TxDb.Hsapiens.UCSC.hg19.knownGene, RUnit, BiocGenerics, BiocStyle License: GPL (>= 2) MD5sum: cad96a9ff1f7ddd9bd8357c8454f56f9 NeedsCompilation: no Title: light package to plot elegant track layers Description: visualize mapped reads along with annotation as track layers for NGS dataset such as ChIP-seq, RNA-seq, miRNA-seq, DNA-seq. biocViews: GenomicsSequence, Visualization Author: Jianhong Ou, Yong-Xu Wang, Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/trackViewer_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/trackViewer_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.1/trackViewer_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.1/trackViewer_1.0.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/trackViewer_1.0.2.tgz vignettes: vignettes/trackViewer/inst/doc/trackViewer.pdf vignetteTitles: trackViewer Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/trackViewer/inst/doc/trackViewer.R Package: tRanslatome Version: 1.2.0 Depends: R (>= 2.15.0), methods, limma, sigPathway, samr, anota, DESeq, edgeR, RankProd, topGO, org.Hs.eg.db, GOSemSim, Heatplus, gplots, plotrix License: LGPL MD5sum: f6c19f53c260c6b0ed5f7303cac37548 NeedsCompilation: no Title: Comparison between multiple levels of gene expression. Description: Detection of differentially expressed genes (DEGs) from the comparison of two biological conditions (treated vs. untreated, diseased vs. normal, mutant vs. wild-type) among different levels of gene expression (transcriptome ,translatome, proteome), using several statistical methods: Rank Product, Translational Efficiency, t-test, SAM, Limma, ANOTA, DESeq, edgeR. Possibility to plot the results with scatterplots, histograms, MA plots, standard deviation (SD) plots, coefficient of variation (CV) plots. Detection of significantly enriched post-transcriptional regulatory factors (RBPs, miRNAs, etc) and Gene Ontology terms in the lists of DEGs previously identified for the two expression levels. Comparison of GO terms enriched only in one of the levels or in both. Calculation of the semantic similarity score between the lists of enriched GO terms coming from the two expression levels. Visual examination and comparison of the enriched terms with heatmaps, radar plots and barplots. biocViews: CellBiology, GeneRegulation, GeneExpression, DifferentialExpression, Microarray, Sequencing, QualityControl, GO, MultipleComparison Author: Toma Tebaldi, Erik Dassi, Galena Kostoska Maintainer: Toma Tebaldi , Erik Dassi source.ver: src/contrib/tRanslatome_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tRanslatome_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tRanslatome_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tRanslatome_1.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tRanslatome_1.2.0.tgz vignettes: vignettes/tRanslatome/inst/doc/tRanslatome_package.pdf vignetteTitles: tRanslatome hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tRanslatome/inst/doc/tRanslatome_package.R Package: TransView Version: 1.8.0 Depends: methods,GenomicRanges Imports: Rsamtools,zlibbioc,gplots,IRanges LinkingTo: Rsamtools Suggests: RUnit,pasillaBamSubset License: GPL-3 Archs: i386, x64 MD5sum: 9249064e50d53e846f6618850c32cec3 NeedsCompilation: yes Title: Read density map construction and accession. Visualization of ChIPSeq and RNASeq data sets. Description: This package provides efficient tools to generate, access and display read densities of sequencing based data sets such as from RNA-Seq and ChIP-Seq. biocViews: DNAMethylation, GeneExpression, Transcription, Microarray, Sequencing, Sequencing, ChIPSeq, RNASeq, MethylSeq, DataImport, Visualization, Clustering, MultipleComparison Author: Julius Muller Maintainer: Julius Muller URL: http://bioconductor.org/packages/release/bioc/html/TransView.html source.ver: src/contrib/TransView_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TransView_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TransView_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TransView_1.8.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TransView_1.8.0.tgz vignettes: vignettes/TransView/inst/doc/TransView.pdf vignetteTitles: An introduction to TransView hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TransView/inst/doc/TransView.R Package: triform Version: 1.6.0 Depends: R (>= 2.11.0), IRanges, yaml Imports: IRanges, yaml, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: c1f1e3ee56a73d3407ff4a80f48a0cfe NeedsCompilation: no Title: Triform finds enriched regions (peaks) in transcription factor ChIP-sequencing data Description: The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics. biocViews: Sequencing, ChIPSeq Author: Karl Kornacker Developer [aut], Tony Handstad Developer [aut, cre] Maintainer: Tony Handstad Developer source.ver: src/contrib/triform_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/triform_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/triform_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/triform_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/triform_1.6.0.tgz vignettes: vignettes/triform/inst/doc/triform.pdf vignetteTitles: Triform users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/triform/inst/doc/triform.R Package: trigger Version: 1.10.0 Depends: R (>= 2.14.0), corpcor, qtl Imports: qvalue, methods, graphics, sva License: GPL-3 Archs: i386, x64 MD5sum: 907154436e8ba6badeae7bc712d12d38 NeedsCompilation: yes Title: Transcriptional Regulatory Inference from Genetics of Gene ExpRession Description: This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest. biocViews: GeneExpression, SNP, GeneticVariability, Microarray, Genetics Author: Lin S. Chen , Dipen P. Sangurdekar and John D. Storey Maintainer: John D. Storey source.ver: src/contrib/trigger_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/trigger_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/trigger_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/trigger_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/trigger_1.10.0.tgz vignettes: vignettes/trigger/inst/doc/trigger.pdf vignetteTitles: Trigger Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/trigger/inst/doc/trigger.R Package: trio Version: 3.2.1 Depends: R (>= 3.0.1) Suggests: survival, haplo.stats, mcbiopi, siggenes, splines, LogicReg (>= 1.5.3), logicFS (>= 1.28.1), KernSmooth, VariantAnnotation License: LGPL-2 MD5sum: 640120d20d4b596e2279ac5cd628d188 NeedsCompilation: no Title: Testing of SNPs and SNP Interactions in Case-Parent Trio Studies Description: Testing SNPs and SNP interactions with a genotypic TDT. This package furthermore contains functions for computing pairwise values of LD measures and for identifying LD blocks, as well as functions for setting up matched case pseudo-control genotype data for case-parent trios in order to run trio logic regression, for imputing missing genotypes in trios, for simulating case-parent trios with disease risk dependent on SNP interaction, and for power and sample size calculation in trio data. biocViews: SNP, GeneticVariability, Microarray, Genetics Author: Holger Schwender, Qing Li, Christoph Neumann, Philipp Berger, Margaret Taub, Ingo Ruczinski Maintainer: Holger Schwender source.ver: src/contrib/trio_3.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/trio_3.2.1.zip win64.binary.ver: bin/windows64/contrib/3.1/trio_3.2.1.zip mac.binary.ver: bin/macosx/contrib/3.1/trio_3.2.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/trio_3.2.1.tgz vignettes: vignettes/trio/inst/doc/trio.pdf vignetteTitles: Trio Logic Regression and genotypic TDT hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/trio/inst/doc/trio.R Package: triplex Version: 1.4.0 Depends: R (>= 2.15.0), IRanges (>= 1.21.10), XVector (>= 0.3.2), Biostrings (>= 2.31.3) Imports: methods, grid, GenomicRanges LinkingTo: IRanges, XVector, Biostrings Suggests: rgl (>= 0.93.932), BSgenome.Celegans.UCSC.ce10, rtracklayer, GenomeGraphs License: BSD_2_clause + file LICENSE Archs: i386, x64 MD5sum: 1e922e463a2fc4f7db7f41d55d66dff8 NeedsCompilation: yes Title: Search and visualize intramolecular triplex-forming sequences in DNA Description: This package provides functions for identification and visualization of potential intramolecular triplex patterns in DNA sequence. The main functionality is to detect the positions of subsequences capable of folding into an intramolecular triplex (H-DNA) in a much larger sequence. The potential H-DNA (triplexes) should be made of as many cannonical nucleotide triplets as possible. The package includes visualization showing the exact base-pairing in 1D, 2D or 3D. biocViews: SequenceMatching, GeneRegulation Author: Jiri Hon, Matej Lexa, Tomas Martinek and Kamil Rajdl with contributions from Daniel Kopecek Maintainer: Jiri Hon URL: http://www.fi.muni.cz/~lexa/triplex/ source.ver: src/contrib/triplex_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/triplex_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/triplex_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/triplex_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/triplex_1.4.0.tgz vignettes: vignettes/triplex/inst/doc/triplex.pdf vignetteTitles: Triplex User Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/triplex/inst/doc/triplex.R Package: tspair Version: 1.22.0 Depends: R (>= 2.10), Biobase (>= 2.4.0) License: GPL-2 Archs: i386, x64 MD5sum: 8a231a0133fc6181702bf628e74065c9 NeedsCompilation: yes Title: Top Scoring Pairs for Microarray Classification Description: These functions calculate the pair of genes that show the maximum difference in ranking between two user specified groups. This "top scoring pair" maximizes the average of sensitivity and specificity over all rank based classifiers using a pair of genes in the data set. The advantage of classifying samples based on only the relative rank of a pair of genes is (a) the classifiers are much simpler and often more interpretable than more complicated classification schemes and (b) if arrays can be classified using only a pair of genes, PCR based tests could be used for classification of samples. See the references for the tspcalc() function for references regarding TSP classifiers. biocViews: Microarray Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/tspair_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tspair_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tspair_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tspair_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tspair_1.22.0.tgz vignettes: vignettes/tspair/inst/doc/tsp.pdf vignetteTitles: tspTutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tspair/inst/doc/tsp.R dependsOnMe: stepwiseCM Package: TSSi Version: 1.10.0 Depends: R (>= 2.13.2), BiocGenerics (>= 0.3.2) Imports: BiocGenerics, methods, Hmisc, minqa, stats, Biobase (>= 0.3.2), plyr, IRanges Suggests: rtracklayer Enhances: parallel License: GPL-3 Archs: i386, x64 MD5sum: 3e63b4ab888959e90b33a255a139f144 NeedsCompilation: yes Title: Transcription Start Site Identification Description: Identify and normalize transcription start sites in high-throughput sequencing data. biocViews: Sequencing, RNASeq, Genetics, Preprocessing Author: Clemens Kreutz, Julian Gehring Maintainer: Julian Gehring URL: http://julian-gehring.github.com/TSSi/ source.ver: src/contrib/TSSi_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TSSi_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TSSi_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TSSi_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TSSi_1.10.0.tgz vignettes: vignettes/TSSi/inst/doc/TSSi.pdf vignetteTitles: Introduction to the TSSi package: Identification of Transcription Start Sites hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TSSi/inst/doc/TSSi.R Package: TurboNorm Version: 1.12.0 Depends: R (>= 2.12.0), convert, limma (>= 1.7.0), marray Imports: stats, grDevices, affy, lattice Suggests: BiocStyle, affydata License: LGPL Archs: i386, x64 MD5sum: e7ca4df119b0fe1e58dc8d88704ad5f4 NeedsCompilation: yes Title: A fast scatterplot smoother suitable for microarray normalization Description: A fast scatterplot smoother based on B-splines with second-order difference penalty. Functions for microarray normalization of single-colour data i.e. Affymetrix/Illumina and two-colour data supplied as marray MarrayRaw-objects or limma RGList-objects are available. biocViews: Microarray, OneChannel, TwoChannel, Preprocessing, DNAMethylation, CpGIsland Author: Maarten van Iterson and Chantal van Leeuwen Maintainer: Maarten van Iterson URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html source.ver: src/contrib/TurboNorm_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TurboNorm_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TurboNorm_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TurboNorm_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TurboNorm_1.12.0.tgz vignettes: vignettes/TurboNorm/inst/doc/turbonorm.pdf vignetteTitles: TurboNorm Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TurboNorm/inst/doc/turbonorm.R Package: tweeDEseq Version: 1.10.0 Depends: R (>= 2.12.0) Imports: MASS, limma, edgeR, parallel, cqn Suggests: tweeDEseqCountData, xtable License: GPL (>= 2) Archs: i386, x64 MD5sum: 167f06313dd9325c74f8b030a8d31f61 NeedsCompilation: yes Title: RNA-seq data analysis using the Poisson-Tweedie family of distributions Description: Differential expression analysis of RNA-seq using the Poisson-Tweedie family of distributions. biocViews: StatisticalMethod, DifferentialExpression, Sequencing, RNASeq Author: Juan R Gonzalez and Mikel Esnaola (with contributions from Robert Castelo ) Maintainer: Juan R Gonzalez URL: http://www.creal.cat/jrgonzalez/software.htm source.ver: src/contrib/tweeDEseq_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/tweeDEseq_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/tweeDEseq_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/tweeDEseq_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/tweeDEseq_1.10.0.tgz vignettes: vignettes/tweeDEseq/inst/doc/tweeDEseq.pdf vignetteTitles: tweeDEseq: analysis of RNA-seq data using the Poisson-Tweedie family of distributions hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tweeDEseq/inst/doc/tweeDEseq.R Package: twilight Version: 1.40.0 Depends: R (>= 2.10), splines (>= 2.2.0), stats (>= 2.2.0), Biobase(>= 1.12.0) Imports: Biobase, graphics, grDevices, stats Suggests: golubEsets (>= 1.4.2), vsn (>= 1.7.2) License: GPL (>= 2) Archs: i386, x64 MD5sum: 8a8dae8f845b838d75a5a1f11a22defa NeedsCompilation: yes Title: Estimation of local false discovery rate Description: In a typical microarray setting with gene expression data observed under two conditions, the local false discovery rate describes the probability that a gene is not differentially expressed between the two conditions given its corrresponding observed score or p-value level. The resulting curve of p-values versus local false discovery rate offers an insight into the twilight zone between clear differential and clear non-differential gene expression. Package 'twilight' contains two main functions: Function twilight.pval performs a two-condition test on differences in means for a given input matrix or expression set and computes permutation based p-values. Function twilight performs a stochastic downhill search to estimate local false discovery rates and effect size distributions. The package further provides means to filter for permutations that describe the null distribution correctly. Using filtered permutations, the influence of hidden confounders could be diminished. biocViews: Microarray, DifferentialExpression, MultipleComparison Author: Stefanie Scheid Maintainer: Stefanie Scheid URL: http://compdiag.molgen.mpg.de/software/twilight.shtml source.ver: src/contrib/twilight_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/twilight_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/twilight_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/twilight_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/twilight_1.40.0.tgz vignettes: vignettes/twilight/inst/doc/tr_2004_01.pdf vignetteTitles: Estimation of Local False Discovery Rates hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/twilight/inst/doc/tr_2004_01.R dependsOnMe: OrderedList importsMe: OrderedList Package: TypeInfo Version: 1.30.0 Depends: methods Suggests: Biobase License: BSD MD5sum: 04ee5ce02eb092bda9b03566db050298 NeedsCompilation: no Title: Optional Type Specification Prototype Description: A prototype for a mechanism for specifying the types of parameters and the return value for an R function. This is meta-information that can be used to generate stubs for servers and various interfaces to these functions. Additionally, the arguments in a call to a typed function can be validated using the type specifications. We allow types to be specified as either i) by class name using either inheritance - is(x, className), or strict instance of - class(x) %in% className, or ii) a dynamic test given as an R expression which is evaluated at run-time. More precise information and interesting tests can be done via ii), but it is harder to use this information as meta-data as it requires more effort to interpret it and it is of course run-time information. It is typically more meaningful. biocViews: Infrastructure Author: Duncan Temple Lang Robert Gentleman () Maintainer: Duncan Temple Lang source.ver: src/contrib/TypeInfo_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/TypeInfo_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/TypeInfo_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/TypeInfo_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/TypeInfo_1.30.0.tgz vignettes: vignettes/TypeInfo/inst/doc/TypeInfoNews.pdf vignetteTitles: TypeInfo R News hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/TypeInfo/inst/doc/TypeInfoNews.R htmlDocs: vignettes/TypeInfo/inst/doc/outline.html htmlTitles: "outline.html" dependsOnMe: RWebServices Package: UNDO Version: 1.0.0 Depends: R (>= 2.15.2), methods, BiocGenerics, Biobase Imports: MASS, boot, nnls, stats, utils License: GPL-2 MD5sum: f9977e9938d1b77c2b19f3370101cd91 NeedsCompilation: no Title: Unsupervised Deconvolution of Tumor-Stromal Mixed Expressions Description: UNDO is an R package for unsupervised deconvolution of tumor and stromal mixed expression data. It detects marker genes and deconvolutes the mixing expression data without any prior knowledge. biocViews: Software Author: Niya Wang Maintainer: Niya Wang source.ver: src/contrib/UNDO_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/UNDO_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/UNDO_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/UNDO_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/UNDO_1.0.0.tgz vignettes: vignettes/UNDO/inst/doc/UNDO-vignette.pdf vignetteTitles: DeconRNASeq Demo hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/UNDO/inst/doc/UNDO-vignette.R Package: unifiedWMWqPCR Version: 1.0.0 Depends: methods Imports: BiocGenerics, stats, graphics, HTqPCR License: GPL (>=2) MD5sum: 8e8382a834d1d282a4c8555e2de8cf35 NeedsCompilation: no Title: Unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data Description: This packages implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data. biocViews: DifferentialExpression, GeneExpression, MicrotitrePlateAssay, MultipleComparison, QualityControl, Software, Visualization, qPCR Author: Jan R. De Neve & Joris Meys Maintainer: Joris Meys source.ver: src/contrib/unifiedWMWqPCR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/unifiedWMWqPCR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/unifiedWMWqPCR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/unifiedWMWqPCR_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/unifiedWMWqPCR_1.0.0.tgz vignettes: vignettes/unifiedWMWqPCR/inst/doc/unifiedWMWqPCR.pdf vignetteTitles: unifiedWMWqPCR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/unifiedWMWqPCR/inst/doc/unifiedWMWqPCR.R Package: UniProt.ws Version: 2.4.2 Depends: RSQLite, RCurl, methods, utils Imports: BiocGenerics, AnnotationDbi Suggests: RUnit License: Artistic License 2.0 MD5sum: 54757295b744d6801727af254f7e7d9a NeedsCompilation: no Title: R Interface to UniProt Web Services Description: A collection of functions for retrieving, processing and repackaging the Uniprot web services. biocViews: Annotation, Infrastructure Author: Marc Carlson Maintainer: Marc Carlson source.ver: src/contrib/UniProt.ws_2.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.1/UniProt.ws_2.4.2.zip win64.binary.ver: bin/windows64/contrib/3.1/UniProt.ws_2.4.2.zip mac.binary.ver: bin/macosx/contrib/3.1/UniProt.ws_2.4.2.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/UniProt.ws_2.4.2.tgz vignettes: vignettes/UniProt.ws/inst/doc/UniProt.ws.pdf vignetteTitles: UniProt.ws: A package for retrieving data from the UniProt web service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/UniProt.ws/inst/doc/UniProt.ws.R suggestsMe: cleaver, dagLogo Package: VanillaICE Version: 1.26.1 Depends: R (>= 3.0.0) Imports: stats, utils, methods, Biobase, oligoClasses (>= 1.21.12),lattice, IRanges (>= 1.13.22), grid, msm, iterators, foreach, GenomicRanges, matrixStats Suggests: genomewidesnp6Crlmm (>= 1.0.7), hapmapsnp6, RColorBrewer, genefilter, RSQLite, foreach, RUnit, pd.mapping50k.hind240, SNPchip (>= 2.5.7), doSNOW Enhances: DNAcopy, crlmm (>= 1.17.14) License: LGPL-2 Archs: i386, x64 MD5sum: 643fab25e414cbda9e58217cefe4426f NeedsCompilation: yes Title: A Hidden Markov Model for high throughput genotyping arrays Description: Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays biocViews: CopyNumberVariants Author: Robert Scharpf , Kevin Scharpf, and Ingo Ruczinski Maintainer: Robert Scharpf source.ver: src/contrib/VanillaICE_1.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/VanillaICE_1.26.1.zip win64.binary.ver: bin/windows64/contrib/3.1/VanillaICE_1.26.1.zip mac.binary.ver: bin/macosx/contrib/3.1/VanillaICE_1.26.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/VanillaICE_1.26.1.tgz vignettes: vignettes/VanillaICE/inst/doc/crlmmDownstream.pdf, vignettes/VanillaICE/inst/doc/VanillaICE.pdf vignetteTitles: crlmmDownstream, VanillaICE Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VanillaICE/inst/doc/crlmmDownstream.R, vignettes/VanillaICE/inst/doc/VanillaICE.R importsMe: MinimumDistance suggestsMe: oligoClasses Package: VariantAnnotation Version: 1.10.5 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.7.7), GenomicRanges (>= 1.13.51), Rsamtools (>= 1.15.5) Imports: IRanges (>= 1.21.43), XVector, Biostrings (>= 2.31.19), Biobase, AnnotationDbi (>= 1.17.11), zlibbioc, BSgenome, GenomicFeatures (>= 1.15.15), DBI, utils, rtracklayer LinkingTo: IRanges, XVector, Biostrings, Rsamtools Suggests: RUnit, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, SNPlocs.Hsapiens.dbSNP.20110815, SNPlocs.Hsapiens.dbSNP.20101109, SIFT.Hsapiens.dbSNP132, PolyPhen.Hsapiens.dbSNP131, snpStats, ggplot2, BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: 96c8dea7917fd57839fec31f54963f30 NeedsCompilation: yes Title: Annotation of Genetic Variants Description: Annotate variants, compute amino acid coding changes, predict coding outcomes biocViews: DataImport, Sequencing, SNP, Annotation, Genetics, Homo_sapiens Author: Valerie Obenchain, Martin Morgan, Michael Lawrence with contributions from Stephanie Gogarten. Maintainer: Valerie Obenchain source.ver: src/contrib/VariantAnnotation_1.10.5.tar.gz win.binary.ver: bin/windows/contrib/3.1/VariantAnnotation_1.10.5.zip win64.binary.ver: bin/windows64/contrib/3.1/VariantAnnotation_1.10.5.zip mac.binary.ver: bin/macosx/contrib/3.1/VariantAnnotation_1.10.5.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/VariantAnnotation_1.10.5.tgz vignettes: vignettes/VariantAnnotation/inst/doc/filterVcf.pdf, vignettes/VariantAnnotation/inst/doc/VariantAnnotation.pdf vignetteTitles: filterVcf Overview, Introduction to VariantAnnotation hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VariantAnnotation/inst/doc/filterVcf.R, vignettes/VariantAnnotation/inst/doc/VariantAnnotation.R dependsOnMe: CNVrd2, deepSNV, ensemblVEP, HTSeqGenie, VariantTools importsMe: biovizBase, customProDB, FunciSNP, ggbio, GGtools, gmapR, R453Plus1Toolbox, Rariant, SeqArray, SomaticSignatures, VariantFiltering suggestsMe: GenomicRanges, GWASTools, trio, vtpnet Package: VariantFiltering Version: 1.0.4 Depends: R (>= 3.0.0), methods, BiocGenerics (>= 0.9.1) Imports: DBI, RSQLite (>= 0.8-1), Biobase, IRanges (>= 1.21.13), AnnotationDbi, BiocParallel, Biostrings (>= 2.29.19), GenomicRanges, Rsamtools, BSgenome, BSgenome.Hsapiens.UCSC.hg19, VariantAnnotation, shiny LinkingTo: IRanges, XVector, Biostrings Suggests: BiocStyle, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, SNPlocs.Hsapiens.dbSNP.20120608, MafDb.ALL.wgs.phase1.release.v3.20101123, MafDb.ESP6500SI.V2.SSA137.dbSNP138, phastCons100way.UCSC.hg19, PolyPhen.Hsapiens.dbSNP131, SIFT.Hsapiens.dbSNP137 License: Artistic-2.0 Archs: i386, x64 MD5sum: 85b0ff8dd34ced359a999987a53dc076 NeedsCompilation: yes Title: Filtering of coding and non-coding genetic variants Description: Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minimum allele frequencies across human populations, splice site strength, conservation, etc. biocViews: Genetics, Homo_sapiens, Annotation, SNP, Sequencing, HighThroughputSequencing Author: Dei M. Elurbe, Robert Castelo Maintainer: Robert Castelo source.ver: src/contrib/VariantFiltering_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/3.1/VariantFiltering_1.0.4.zip win64.binary.ver: bin/windows64/contrib/3.1/VariantFiltering_1.0.4.zip mac.binary.ver: bin/macosx/contrib/3.1/VariantFiltering_1.0.4.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/VariantFiltering_1.0.4.tgz vignettes: vignettes/VariantFiltering/inst/doc/usingVariantFiltering.pdf vignetteTitles: VariantFiltering: filter coding and non-coding genetic variants hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: VariantTools Version: 1.6.1 Depends: IRanges (>= 1.19.34), GenomicRanges (>= 1.13.43), VariantAnnotation (>= 1.7.35), methods Imports: Rsamtools (>= 1.11.10), BiocGenerics, Biostrings, parallel, gmapR (>= 1.5.15), GenomicFeatures, Matrix, rtracklayer, BiocParallel, GenomeInfoDb Suggests: RUnit, LungCancerLines (>= 0.0.6), RBGL, graph License: Artistic-2.0 MD5sum: eaa3c14f0a7e65691461a4b35a95d6b1 NeedsCompilation: no Title: Tools for Working with Genetic Variants Description: Tools for detecting, filtering, calling, comparing and plotting variants. biocViews: Genetics, GeneticVariability, Sequencing Author: Michael Lawrence, Jeremiah Degenhardt, Robert Gentleman Maintainer: Michael Lawrence source.ver: src/contrib/VariantTools_1.6.1.tar.gz vignettes: vignettes/VariantTools/inst/doc/VariantTools.pdf vignetteTitles: Introduction to VariantTools hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VariantTools/inst/doc/VariantTools.R importsMe: HTSeqGenie Package: vbmp Version: 1.32.0 Depends: R (>= 2.10) Suggests: Biobase (>= 2.5.5), statmod License: GPL (>= 2) MD5sum: 5844b6aa7d281647fa8b12fa16ca255b NeedsCompilation: no Title: Variational Bayesian Multinomial Probit Regression Description: Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination. biocViews: Classification Author: Nicola Lama , Mark Girolami Maintainer: Nicola Lama URL: http://bioinformatics.oxfordjournals.org/cgi/content/short/btm535v1 source.ver: src/contrib/vbmp_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/vbmp_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/vbmp_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/vbmp_1.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/vbmp_1.32.0.tgz vignettes: vignettes/vbmp/inst/doc/vbmp.pdf vignetteTitles: vbmp Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/vbmp/inst/doc/vbmp.R Package: Vega Version: 1.12.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: d75fd44d9eeb08a30dc95636a878036e NeedsCompilation: yes Title: An R package for copy number data segmentation Description: Vega (Variational Estimator for Genomic Aberrations) is an algorithm that adapts a very popular variational model (Mumford and Shah) used in image segmentation so that chromosomal aberrant regions can be efficiently detected. biocViews: aCGH, CopyNumberVariation Author: Sandro Morganella Maintainer: Sandro Morganella source.ver: src/contrib/Vega_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/Vega_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.1/Vega_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.1/Vega_1.12.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/Vega_1.12.0.tgz vignettes: vignettes/Vega/inst/doc/Vega.pdf vignetteTitles: Vega hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Vega/inst/doc/Vega.R Package: VegaMC Version: 3.2.0 Depends: R (>= 2.10.0), biomaRt, Biobase, genoset Imports: methods License: GPL-2 Archs: i386, x64 MD5sum: e0e608a20025630a9abf71eda868f81a NeedsCompilation: yes Title: VegaMC: A Package Implementing a Variational Piecewise Smooth Model for Identification of Driver Chromosomal Imbalances in Cancer Description: This package enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. VegaMC performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, VegaMC produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported. biocViews: aCGH, CopyNumberVariation Author: S. Morganella and M. Ceccarelli Maintainer: Sandro Morganella source.ver: src/contrib/VegaMC_3.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/VegaMC_3.2.0.zip win64.binary.ver: bin/windows64/contrib/3.1/VegaMC_3.2.0.zip mac.binary.ver: bin/macosx/contrib/3.1/VegaMC_3.2.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/VegaMC_3.2.0.tgz vignettes: vignettes/VegaMC/inst/doc/VegaMC.pdf vignetteTitles: VegaMC hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/VegaMC/inst/doc/VegaMC.R Package: viper Version: 1.0.0 Depends: R (>= 2.14.0), Biobase, methods Imports: mixtools, stats Suggests: bcellViper License: GPL (>=2) MD5sum: d1b0013e02df96da1bf6845e51d713b3 NeedsCompilation: no Title: Virtual Inference of Protein-activity by Enriched Regulon analysis Description: Inference of protein activity from gene expression data, including the VIPER and msVIPER algorithms biocViews: SystemsBiology, NetworkEnrichment, GeneExpression, FunctionalPrediction, GeneRegulation Author: Mariano J Alvarez Maintainer: Mariano J Alvarez source.ver: src/contrib/viper_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/viper_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.1/viper_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.1/viper_1.0.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/viper_1.0.0.tgz vignettes: vignettes/viper/inst/doc/viper.pdf vignetteTitles: Using VIPER hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/viper/inst/doc/viper.R Package: virtualArray Version: 1.8.0 Depends: R (>= 2.15.0), BiocGenerics, methods, plyr, preprocessCore Imports: affy, affyPLM, AnnotationDbi, Biobase, gcrma, GEOquery, graphics, methods, reshape2, stats, utils, tseries, outliers Suggests: affydata, plier, limma, lumi, org.Hs.eg.db Enhances: multicore,BiocParallel License: GPL-3 MD5sum: 177f2e4928c77243e254e3d29cd7292e NeedsCompilation: no Title: Build virtual array from different microarray platforms Description: This package permits the user to combine raw data of different microarray platforms into one virtual array. It consists of several functions that act subsequently in a semi-automatic way. Doing as much of the data combination and letting the user concentrate on analysing the resulting virtual array. biocViews: Microarray, OneChannel, DataImport, Preprocessing, MultipleComparison Author: Andreas Heider Maintainer: Andreas Heider source.ver: src/contrib/virtualArray_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/virtualArray_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.1/virtualArray_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.1/virtualArray_1.8.0.tgz vignettes: vignettes/virtualArray/inst/doc/virtualArray.pdf vignetteTitles: virtualArray Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/virtualArray/inst/doc/virtualArray.R Package: vsn Version: 3.32.0 Depends: R (>= 2.10), Biobase (>= 2.5.5) Imports: methods, affy (>= 1.23.4), limma, lattice Suggests: affydata, hgu95av2cdf License: Artistic-2.0 Archs: i386, x64 MD5sum: 616aa7372e5ec6cce50127919689cf68 NeedsCompilation: yes Title: Variance stabilization and calibration for microarray data Description: The package implements a method for normalising microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references (see vignette). The model incorporates data calibration (a.k.a. normalization), a model for the dependence of the variance on the mean intensity, and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription. biocViews: Microarray, OneChannel, TwoChannel, Preprocessing Author: Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth. Maintainer: Wolfgang Huber URL: http://www.r-project.org, http://www.ebi.ac.uk/huber source.ver: src/contrib/vsn_3.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/vsn_3.32.0.zip win64.binary.ver: bin/windows64/contrib/3.1/vsn_3.32.0.zip mac.binary.ver: bin/macosx/contrib/3.1/vsn_3.32.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/vsn_3.32.0.tgz vignettes: vignettes/vsn/inst/doc/convergence2.pdf, vignettes/vsn/inst/doc/likelihoodcomputations.pdf, vignettes/vsn/inst/doc/vsn.pdf vignetteTitles: Verifying and assessing the performance with simulated data, Likelihood Calculations for vsn, Introduction to vsn hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/vsn/inst/doc/convergence2.R, vignettes/vsn/inst/doc/likelihoodcomputations.R, vignettes/vsn/inst/doc/vsn.R dependsOnMe: affyPara, cellHTS2, MmPalateMiRNA, webbioc importsMe: arrayQualityMetrics, imageHTS, LVSmiRNA, metaseqR, MSnbase, pvca, Ringo, tilingArray suggestsMe: adSplit, beadarray, BiocCaseStudies, cellHTS, DESeq, DESeq2, ggbio, GlobalAncova, globaltest, limma, lumi, twilight Package: vtpnet Version: 0.4.1 Depends: R (>= 3.0.0), graph, GenomicRanges Suggests: MotifDb, VariantAnnotation, Rgraphviz, gwascat License: Artistic-2.0 MD5sum: 03bfc87cfb84f8863e6632339c0cb348 NeedsCompilation: no Title: variant-transcription factor-phenotype networks Description: variant-transcription factor-phenotype networks, inspired by Maurano et al., Science (2012), PMID 22955828 biocViews: Network Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/vtpnet_0.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/vtpnet_0.4.1.zip win64.binary.ver: bin/windows64/contrib/3.1/vtpnet_0.4.1.zip mac.binary.ver: bin/macosx/contrib/3.1/vtpnet_0.4.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/vtpnet_0.4.1.tgz vignettes: vignettes/vtpnet/inst/doc/vtpnet.pdf vignetteTitles: vtpnet: variant-transcription factor-network tools hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/vtpnet/inst/doc/vtpnet.R Package: wateRmelon Version: 1.4.0 Depends: R (>= 2.10), limma, methods, matrixStats, methylumi, lumi, IlluminaHumanMethylation450k.db, ROC Suggests: RPMM Enhances: minfi, methylumi, IMA License: GPL-3 MD5sum: 0eb6266592fec7512a05ad8b4c9cbc3b NeedsCompilation: no Title: Illumina 450 methylation array normalization and metrics Description: 15 flavours of betas and three performance metrics, with methods for objects produced by methylumi, minfi and IMA packages. biocViews: DNAMethylation, Microarray, TwoChannel, Preprocessing, QualityControl Author: Leonard C Schalkwyk, Ruth Pidsley, Chloe CY Wong, with functions contributed by Nizar Touleimat, Matthieu Defrance, Andrew Teschendorff, Jovana Maksimovic Maintainer: Leo source.ver: src/contrib/wateRmelon_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/wateRmelon_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/wateRmelon_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/wateRmelon_1.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/wateRmelon_1.4.0.tgz vignettes: vignettes/wateRmelon/inst/doc/wateRmelon.pdf vignetteTitles: Package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/wateRmelon/inst/doc/wateRmelon.R importsMe: ChAMP Package: waveTiling Version: 1.6.0 Depends: oligo, oligoClasses, Biobase, Biostrings, GenomeGraphs Imports: methods, affy, preprocessCore, GenomicRanges, waveslim, IRanges Suggests: BSgenome, BSgenome.Athaliana.TAIR.TAIR9, waveTilingData, pd.atdschip.tiling, TxDb.Athaliana.BioMart.plantsmart12 License: GPL (>=2) Archs: i386, x64 MD5sum: a037c8b10d8310a87eb13b795a5c4e46 NeedsCompilation: yes Title: Wavelet-Based Models for Tiling Array Transcriptome Analysis Description: This package is designed to conduct transcriptome analysis for tiling arrays based on fast wavelet-based functional models. biocViews: Microarray, DifferentialExpression, TimeCourse, GeneExpression Author: Kristof De Beuf , Peter Pipelers and Lieven Clement Maintainer: Kristof De Beuf URL: https://r-forge.r-project.org/projects/wavetiling/ source.ver: src/contrib/waveTiling_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/waveTiling_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.1/waveTiling_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.1/waveTiling_1.6.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/waveTiling_1.6.0.tgz vignettes: vignettes/waveTiling/inst/doc/waveTiling-vignette.pdf vignetteTitles: The waveTiling package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/waveTiling/inst/doc/waveTiling-vignette.R Package: weaver Version: 1.30.0 Depends: R (>= 2.5.0), digest, tools, utils, codetools Suggests: codetools License: GPL-2 MD5sum: 32bd56e8162a7b1b15aa9c59a6ea0d30 NeedsCompilation: no Title: Tools and extensions for processing Sweave documents Description: This package provides enhancements on the Sweave() function in the base package. In particular a facility for caching code chunk results is included. biocViews: Infrastructure Author: Seth Falcon Maintainer: Seth Falcon source.ver: src/contrib/weaver_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/weaver_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.1/weaver_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.1/weaver_1.30.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/weaver_1.30.0.tgz vignettes: vignettes/weaver/inst/doc/weaver_howTo.pdf vignetteTitles: Using weaver to process Sweave documents hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/weaver/inst/doc/weaver_howTo.R suggestsMe: BiocCaseStudies Package: webbioc Version: 1.36.0 Depends: R (>= 1.8.0), Biobase, affy, multtest, annaffy, vsn, gcrma, qvalue Imports: multtest, qvalue, stats, utils, BiocInstaller License: GPL (>= 2) MD5sum: f0be6ec646756ee44fd2987c1c7f18b4 NeedsCompilation: no Title: Bioconductor Web Interface Description: An integrated web interface for doing microarray analysis using several of the Bioconductor packages. It is intended to be deployed as a centralized bioinformatics resource for use by many users. (Currently only Affymetrix oligonucleotide analysis is supported.) biocViews: Infrastructure, Microarray, OneChannel, DifferentialExpression Author: Colin A. Smith Maintainer: Colin A. Smith URL: http://www.bioconductor.org/ SystemRequirements: Unix, Perl (>= 5.6.0), Netpbm source.ver: src/contrib/webbioc_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/webbioc_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.1/webbioc_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.1/webbioc_1.36.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/webbioc_1.36.0.tgz vignettes: vignettes/webbioc/inst/doc/demoscript.pdf, vignettes/webbioc/inst/doc/webbioc.pdf vignetteTitles: webbioc Demo Script, webbioc Overview hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/webbioc/inst/doc/demoscript.R, vignettes/webbioc/inst/doc/webbioc.R Package: widgetTools Version: 1.42.0 Depends: R (>= 2.4.0), methods, utils, tcltk Suggests: Biobase License: LGPL MD5sum: a51dbb312d23917767fad4829c47fc5a NeedsCompilation: no Title: Creates an interactive tcltk widget Description: This packages contains tools to support the construction of tcltk widgets biocViews: Infrastructure Author: Jianhua Zhang Maintainer: Jianhua Zhang source.ver: src/contrib/widgetTools_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/widgetTools_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.1/widgetTools_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.1/widgetTools_1.42.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/widgetTools_1.42.0.tgz vignettes: vignettes/widgetTools/inst/doc/widgetTools.pdf vignetteTitles: widgetTools Introduction hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/widgetTools/inst/doc/widgetTools.R dependsOnMe: tkWidgets importsMe: OLINgui suggestsMe: affy Package: xcms Version: 1.40.0 Depends: R (>= 2.14.0), methods, mzR (>= 1.1.6), BiocGenerics, Biobase Suggests: faahKO, msdata, ncdf, multtest, rgl, MassSpecWavelet (>= 1.5.2), RANN, RUnit Enhances: Rgraphviz, Rmpi, XML License: GPL (>= 2) + file LICENSE Archs: i386, x64 MD5sum: 24eefb97a2059dc89835dd595f45017f NeedsCompilation: yes Title: LC/MS and GC/MS Data Analysis Description: Framework for processing and visualization of chromatographically separated and single-spectra mass spectral data. Imports from AIA/ANDI NetCDF, mzXML, mzData and mzML files. Preprocesses data for high-throughput, untargeted analyte profiling. biocViews: MassSpectrometry, Metabolomics Author: Colin A. Smith , Ralf Tautenhahn , Steffen Neumann , Paul Benton , Christopher Conley Maintainer: Ralf Tautenhahn URL: http://metlin.scripps.edu/download/ and https://github.com/sneumann/xcms source.ver: src/contrib/xcms_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/xcms_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.1/xcms_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.1/xcms_1.40.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/xcms_1.40.0.tgz vignettes: vignettes/xcms/inst/doc/xcmsDirect.pdf, vignettes/xcms/inst/doc/xcmsInstall.pdf, vignettes/xcms/inst/doc/xcmsMSn.pdf, vignettes/xcms/inst/doc/xcmsPreprocess.pdf vignetteTitles: Grouping FTICR-MS data with xcms, Installation Instructions for xcms, Processing Tandem-MS and MS$^n$ data with xcms, LC/MS Preprocessing and Analysis with xcms hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/xcms/inst/doc/xcmsDirect.R, vignettes/xcms/inst/doc/xcmsInstall.R, vignettes/xcms/inst/doc/xcmsMSn.R, vignettes/xcms/inst/doc/xcmsPreprocess.R dependsOnMe: CAMERA, flagme, metaMS importsMe: CAMERA, Risa suggestsMe: MassSpecWavelet, RMassBank Package: XDE Version: 2.10.0 Depends: R (>= 2.10.0), Biobase (>= 2.5.5), methods, graphics Imports: Biobase, BiocGenerics, genefilter, graphics, grDevices, gtools, MergeMaid, methods, stats, utils, mvtnorm Suggests: siggenes, genefilter, MASS, RColorBrewer, GeneMeta, RUnit Enhances: coda License: LGPL-2 Archs: i386, x64 MD5sum: c9481e679300257aeff6f9ae24499dd2 NeedsCompilation: yes Title: XDE: a Bayesian hierarchical model for cross-study analysis of differential gene expression Description: Multi-level model for cross-study detection of differential gene expression. biocViews: Microarray, DifferentialExpression Author: R.B. Scharpf, G. Parmigiani, A.B. Nobel, and H. Tjelmeland Maintainer: Robert Scharpf source.ver: src/contrib/XDE_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/XDE_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/XDE_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/XDE_2.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/XDE_2.10.0.tgz vignettes: vignettes/XDE/inst/doc/XdeParameterClass.pdf, vignettes/XDE/inst/doc/XDE.pdf vignetteTitles: XdeParameterClass Vignette, XDE Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/XDE/inst/doc/XdeParameterClass.R, vignettes/XDE/inst/doc/XDE.R Package: xmapbridge Version: 1.22.0 Depends: R (>= 2.0), methods Suggests: RUnit, RColorBrewer License: LGPL-3 MD5sum: d8399dc21608e9e6c05eb3cc3d215336 NeedsCompilation: no Title: Export plotting files to the xmapBridge for visualisation in X:Map Description: xmapBridge can plot graphs in the X:Map genome browser. This package exports plotting files in a suitable format. biocViews: Annotation, ReportWriting, Visualization Author: Tim Yates and Crispin J Miller Maintainer: Tim Yates URL: http://xmap.picr.man.ac.uk, http://www.bioconductor.org source.ver: src/contrib/xmapbridge_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/xmapbridge_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.1/xmapbridge_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.1/xmapbridge_1.22.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/xmapbridge_1.22.0.tgz vignettes: vignettes/xmapbridge/inst/doc/xmapbridge.pdf vignetteTitles: xmapbridge primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xmapbridge/inst/doc/xmapbridge.R Package: xps Version: 1.24.1 Depends: R (>= 2.6.0), methods, utils Suggests: tools License: GPL (>= 2.0) Archs: i386 MD5sum: de7bb04d94476ebd7b0608cfadfecc70 NeedsCompilation: yes Title: Processing and Analysis of Affymetrix Oligonucleotide Arrays including Exon Arrays, Whole Genome Arrays and Plate Arrays Description: The package handles pre-processing, normalization, filtering and analysis of Affymetrix GeneChip expression arrays, including exon arrays (Exon 1.0 ST: core, extended, full probesets), gene arrays (Gene 1.0 ST) and plate arrays on computers with 1 GB RAM only. It imports Affymetrix .CDF, .CLF, .PGF and .CEL as well as annotation files, and computes e.g. RMA, MAS5, FARMS, DFW, FIRMA, tRMA, MAS5-calls, DABG-calls, I/NI-calls. It is an R wrapper to XPS (eXpression Profiling System), which is based on ROOT, an object-oriented framework developed at CERN. Thus, the prior installation of ROOT is a prerequisite for the usage of this package, however, no knowledge of ROOT is required. ROOT is licensed under LGPL and can be downloaded from http://root.cern.ch. biocViews: ExonArray, GeneExpression, Microarray, OneChannel, DataImport, Preprocessing, Transcription, DifferentialExpression Author: Christian Stratowa, Vienna, Austria Maintainer: Christian Stratowa SystemRequirements: root_v5.34.05 - See README file for installation instructions. source.ver: src/contrib/xps_1.24.1.tar.gz win.binary.ver: bin/windows/contrib/3.1/xps_1.24.1.zip win64.binary.ver: bin/windows64/contrib/3.1/xps_1.24.1.zip mac.binary.ver: bin/macosx/contrib/3.1/xps_1.24.1.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/xps_1.24.1.tgz vignettes: vignettes/xps/inst/doc/APTvsXPS.pdf, vignettes/xps/inst/doc/xpsClasses.pdf, vignettes/xps/inst/doc/xps.pdf, vignettes/xps/inst/doc/xpsPreprocess.pdf vignetteTitles: 3. XPS Vignette: Comparison APT vs XPS, 2. XPS Vignette: Classes, 1. XPS Vignette: Overview, 4. XPS Vignette: Function express() hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xps/inst/doc/APTvsXPS.R, vignettes/xps/inst/doc/xpsClasses.R, vignettes/xps/inst/doc/xpsPreprocess.R, vignettes/xps/inst/doc/xps.R Package: XVector Version: 0.4.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.7.2), IRanges (>= 1.21.25) Imports: methods, BiocGenerics, IRanges LinkingTo: IRanges Suggests: Biostrings, drosophila2probe, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: 4fa3e58a5251357478b4282d1d08e3e5 NeedsCompilation: yes Title: Representation and manpulation of external sequences Description: Memory efficient S4 classes for storing sequences "externally" (behind an R external pointer, or on disk). biocViews: Infrastructure, DataRepresentation Author: H. Pages and P. Aboyoun Maintainer: H. Pages source.ver: src/contrib/XVector_0.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/XVector_0.4.0.zip win64.binary.ver: bin/windows64/contrib/3.1/XVector_0.4.0.zip mac.binary.ver: bin/macosx/contrib/3.1/XVector_0.4.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/XVector_0.4.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: Biostrings, motifRG, Rsamtools, rSFFreader, triplex importsMe: Biostrings, BSgenome, ChIPsim, CNEr, DECIPHER, gcrma, GenomicRanges, Gviz, R453Plus1Toolbox, rSFFreader, rtracklayer, TFBSTools, VariantAnnotation suggestsMe: IRanges Package: yaqcaffy Version: 1.24.0 Depends: simpleaffy (>= 2.19.3), methods Imports: stats4 Suggests: MAQCsubsetAFX, affydata, xtable, tcltk2, tcltk License: Artistic-2.0 MD5sum: aaa84506702f94f98b620b8602225fb7 NeedsCompilation: no Title: Affymetrix expression data quality control and reproducibility analysis Description: Quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets. biocViews: Microarray,OneChannel,QualityControl,ReportWriting Author: Laurent Gatto Maintainer: Laurent Gatto source.ver: src/contrib/yaqcaffy_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/yaqcaffy_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.1/yaqcaffy_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.1/yaqcaffy_1.24.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/yaqcaffy_1.24.0.tgz vignettes: vignettes/yaqcaffy/inst/doc/yaqcaffy.pdf vignetteTitles: yaqcaffy: Affymetrix quality control and MAQC reproducibility hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/yaqcaffy/inst/doc/yaqcaffy.R suggestsMe: qcmetrics Package: zlibbioc Version: 1.10.0 License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: 88e9c6b8aa87ab12c8d01932e447aa2f NeedsCompilation: yes Title: An R packaged zlib-1.2.5 Description: This package uses the source code of zlib-1.2.5 to create libraries for systems that do not have these available via other means (most Linux and Mac users should have system-level access to zlib, and no direct need for this package). See the vignette for instructions on use. biocViews: Infrastructure Author: Martin Morgan Maintainer: Bioconductor Package Maintainer URL: http://bioconductor.org/packages/release/bioc/html/Zlibbioc.html source.ver: src/contrib/zlibbioc_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.1/zlibbioc_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.1/zlibbioc_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.1/zlibbioc_1.10.0.tgz mac.binary.mavericks.ver: bin/macosx/mavericks/contrib/3.1/zlibbioc_1.10.0.tgz vignettes: vignettes/zlibbioc/inst/doc/UsingZlibbioc.pdf vignetteTitles: Using zlibbioc C libraries hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/zlibbioc/inst/doc/UsingZlibbioc.R dependsOnMe: BitSeq importsMe: affy, affyio, affyPLM, Biostrings, ChemmineOB, DiffBind, makecdfenv, oligo, QuasR, rhdf5, Rsamtools, rtracklayer, seqbias, ShortRead, Starr, VariantAnnotation