Package: a4 Version: 1.10.0 Depends: a4Base, a4Preproc, a4Classif, a4Core, a4Reporting Suggests: MLP, nlcv, ALL, Cairo License: GPL-3 MD5sum: 8e0fe01bace928158aee2af99706c37f NeedsCompilation: no Title: Automated Affymetrix Array Analysis Umbrella Package Description: Automated Affymetrix Array Analysis Umbrella Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4_1.10.0.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: 1.10.0 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: 7e1aca3d33d425976b0f8d513f918877 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Base Package Description: Automated Affymetrix Array Analysis biocViews: Bioinformatics, 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4Base_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4Base_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4Base_1.10.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Classif Version: 1.10.0 Depends: methods, a4Core, a4Preproc, MLInterfaces, ROCR, pamr, glmnet, varSelRF Imports: a4Core Suggests: ALL License: GPL-3 MD5sum: cbbc0e46e3afa804456c60e150338dd7 NeedsCompilation: no Title: Automated Affymetrix Array Analysis Classification Package Description: Automated Affymetrix Array Analysis Classification Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Classif_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4Classif_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4Classif_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4Classif_1.10.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: a4Core Version: 1.10.0 Depends: methods, Biobase, glmnet License: GPL-3 MD5sum: c3f252531bd635542dfd02934d4d2e4e NeedsCompilation: no Title: Automated Affymetrix Array Analysis Core Package Description: Automated Affymetrix Array Analysis Core Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Core_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4Core_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4Core_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4Core_1.10.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif importsMe: a4Classif Package: a4Preproc Version: 1.10.0 Depends: methods, AnnotationDbi Suggests: ALL, hgu95av2.db License: GPL-3 MD5sum: def2defa0fd4597265f71bba17b0485e NeedsCompilation: no Title: Automated Affymetrix Array Analysis Preprocessing Package Description: Automated Affymetrix Array Analysis Preprocessing Package biocViews: Bioinformatics, Microarray Author: Willem Talloen, Tobias Verbeke Maintainer: Tobias Verbeke , Willem Ligtenberg source.ver: src/contrib/a4Preproc_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4Preproc_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4Preproc_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4Preproc_1.10.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4, a4Base, a4Classif Package: a4Reporting Version: 1.10.0 Depends: methods, annaffy Imports: xtable, utils License: GPL-3 MD5sum: c07a49c5bf2bc4f5a51a4aa6d6dfaa2e 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/a4Reporting_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/a4Reporting_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/a4Reporting_1.10.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4 Package: ABarray Version: 1.30.0 Imports: Biobase, graphics, grDevices, methods, multtest, stats, tcltk, utils Suggests: limma, LPE License: GPL MD5sum: 7a7d391abafe914f7e9d1195b39a2b53 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ABarray_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ABarray_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ABarray_1.30.0.tgz vignettes: vignettes/ABarray/inst/doc/ABarray.pdf, vignettes/ABarray/inst/doc/ABarrayGUI.pdf vignetteTitles: ABarray gene expression, ABarray gene expression GUI interface hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ABarray/inst/doc/ABarray.R, vignettes/ABarray/inst/doc/ABarrayGUI.R Package: aCGH Version: 1.40.0 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: b70eac05f243efb9674113aa27ca4de4 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: CopyNumberVariants, DataImport, Genetics Author: Jane Fridlyand , Peter Dimitrov Maintainer: Peter Dimitrov source.ver: src/contrib/aCGH_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/aCGH_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/aCGH_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/aCGH_1.40.0.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: 2.18.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), methods Imports: graphics, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: 563bd7cc8482a13febca706882259597 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: Bioinformatics Author: Sean Davis Maintainer: Sean Davis URL: http://watson.nci.nih.gov/~sdavis source.ver: src/contrib/ACME_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ACME_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ACME_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ACME_2.18.0.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: 2.2.0 Depends: R (>= 2.15.0), parallel, ff Imports: bit, ffbase, DNAcopy, snapCGH, tilingArray, aCGH, GLAD, waveslim, cluster Suggests: CGHregions, Cairo, limma Enhances: Rmpi License: GPL (>= 3) Archs: i386, x64 MD5sum: b100a5a714ec60a9e590cd8825992ab7 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, CopyNumberVariants 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_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ADaCGH2_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ADaCGH2_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ADaCGH2_2.2.0.tgz vignettes: vignettes/ADaCGH2/inst/doc/ADaCGH2-long-examples.pdf, vignettes/ADaCGH2/inst/doc/ADaCGH2.pdf vignetteTitles: ADaCGH2-long-examples.pdf, ADaCGH2 Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ADaCGH2/inst/doc/ADaCGH2-long-examples.R, vignettes/ADaCGH2/inst/doc/ADaCGH2.R Package: adSplit Version: 1.32.0 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: a7dd899b7e73d63211f2d731f60aac03 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, Bioinformatics, Clustering Author: Claudio Lottaz, Joern Toedling Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/adSplit_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/adSplit_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/adSplit_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/adSplit_1.32.0.tgz vignettes: vignettes/adSplit/inst/doc/bcb_logo.pdf, vignettes/adSplit/inst/doc/minerva_bcb.pdf, vignettes/adSplit/inst/doc/tr_2005_02.pdf vignetteTitles: bcb_logo.pdf, minerva_bcb.pdf, Annotation-Driven Clustering hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/adSplit/inst/doc/tr_2005_02.R Package: affxparser Version: 1.34.2 Depends: R (>= 2.6.0) Suggests: R.utils (>= 1.29.8), AffymetrixDataTestFiles License: LGPL (>= 2) Archs: i386, x64 MD5sum: 9eb13b1eebc33554b2a81fc40be6e048 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_1.34.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/affxparser_1.34.2.zip win64.binary.ver: bin/windows64/contrib/3.0/affxparser_1.34.2.zip mac.binary.ver: bin/macosx/contrib/3.0/affxparser_1.34.2.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: 1.40.0 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: b58ebcb0117b685130425e8840088845 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affy_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affy_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affy_1.40.0.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, ExiMiR, farms, frmaTools, gcrma, LMGene, logitT, maDB, 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, ChIPXpress, Cormotif, farms, ffpe, frma, gcrma, GEOsubmission, Harshlight, HTqPCR, lumi, makecdfenv, MSnbase, plier, plw, puma, pvac, simpleaffy, tilingArray, TurboNorm, virtualArray, vsn, waveTiling suggestsMe: AnnotationForge, beadarray, beadarraySNP, BiocCaseStudies, BiocGenerics, Biostrings, BufferedMatrixMethods, categoryCompare, ecolitk, ExpressionView, factDesign, ffpe, gCMAPWeb, GeneRegionScan, limma, made4, oneChannelGUI, piano, PREDA, qcmetrics, siggenes, TurboNorm Package: affycomp Version: 1.38.0 Depends: R (>= 2.13.0), methods, Biobase (>= 2.3.3) Suggests: splines, affycompData License: GPL (>= 2) MD5sum: 7b30327b14a45597d497bba9deb87bdf 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affycomp_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affycomp_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affycomp_1.38.0.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: 1.22.0 Depends: R (>= 2.7.0), XML (>= 2.8-1), RCurl (>= 0.8-1), methods Imports: Biostrings License: Artistic-2.0 MD5sum: 06127e1b2d708320379b6c41ca8191d9 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AffyCompatible_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AffyCompatible_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AffyCompatible_1.22.0.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: 1.20.0 Depends: R (>= 2.7.0), tools, methods, utils, Biobase, affy, affydata License: Artistic-2.0 MD5sum: 2a67c36a39ba8d8c543bfa9a53947e2b NeedsCompilation: no Title: structured corruption of affymetrix cel file data Description: structured corruption of cel file data to demonstrate QA effectiveness biocViews: Infrastructure, Bioinformatics Author: V. Carey Maintainer: V. Carey source.ver: src/contrib/affyContam_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyContam_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyContam_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyContam_1.20.0.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: 1.34.0 Depends: affy, Biobase, GO.db, KEGG.db Imports: biomaRt, limma, GOstats, annotate, annaffy, genefilter, gcrma, splines, xtable, AnnotationDbi, lattice, gplots, R2HTML, oligoClasses, ReportingTools, hwriter Suggests: affydata, hgfocuscdf, rgl License: Artistic-2.0 MD5sum: c51eb71297beb36d41f3033bfd5edae2 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 source.ver: src/contrib/affycoretools_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affycoretools_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affycoretools_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affycoretools_1.34.0.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 suggestsMe: Agi4x44PreProcess Package: AffyExpress Version: 1.28.0 Depends: R (>= 2.10), affy (>= 1.23.4), limma Suggests: simpleaffy, R2HTML, affyPLM, hgu95av2cdf, hgu95av2, test3cdf, genefilter, estrogen, annaffy, gcrma License: LGPL MD5sum: e14186e66d96022c14345ff0510efacf 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, Bioinformatics, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu , Xuejun Arthur Li Maintainer: Xuejun Arthur Li source.ver: src/contrib/AffyExpress_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AffyExpress_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AffyExpress_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AffyExpress_1.28.0.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: 1.14.0 Depends: R (>= 2.10.0), methods, gcrma Imports: affxparser (>= 1.16.0), affy, graphics, methods, Biobase Suggests: AffymetrixDataTestFiles License: GPL version 3 MD5sum: 4413daa494796e5f9437d4bbcb2296db 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyILM_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyILM_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyILM_1.14.0.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: 1.30.0 Depends: R (>= 2.6.0) Imports: zlibbioc License: LGPL (>= 2) Archs: i386, x64 MD5sum: 5a26b715296921b05ab788e6af2a3e09 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyio_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyio_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyio_1.30.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE dependsOnMe: affylmGUI, affyPara, makecdfenv, SCAN.UPC, sscore importsMe: affy, crlmm, ExiMiR, gcrma, oligo, oligoClasses suggestsMe: BufferedMatrixMethods Package: affylmGUI Version: 1.36.0 Depends: limma, tcltk, affy, BiocInstaller, affyio, affy, tkrplot, affyPLM, R2HTML, xtable, gcrma, affyPLM, AnnotationDbi License: LGPL MD5sum: d025aa403478b32454184d231e2ebf9d 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, Bioinformatics, DifferentialExpression, MultipleComparisons, 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affylmGUI_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affylmGUI_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affylmGUI_1.36.0.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: 1.22.0 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: b085e2f55b92f3732835263bb5c6947a 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyPara_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyPara_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyPara_1.22.0.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: 1.36.0 Depends: R (>= 2.13.0), affy (>= 1.5) Suggests: affydata, hgu95av2probe License: LGPL MD5sum: d9d20dc844c04dc65c02945de1ebd7d1 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affypdnn_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affypdnn_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affypdnn_1.36.0.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: 1.38.0 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: bffb6a94e493311a4cb0f9cc53b696e0 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyPLM_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyPLM_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyPLM_1.38.0.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, frmaTools, ggbio, metahdep, oneChannelGUI, piano Package: affyQCReport Version: 1.40.0 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: 16440fb7fa5920fd36319a5af83eadc7 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/affyQCReport_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/affyQCReport_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/affyQCReport_1.40.0.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: 1.8.0 Depends: R (>= 2.9.0), methods, affy Suggests: AmpAffyExample License: GPL-2 MD5sum: 98744e1e95fcdde78a698b00dc7b3f36 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, Bioinformatics Author: Mario Fasold Maintainer: Mario Fasold source.ver: src/contrib/AffyRNADegradation_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AffyRNADegradation_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AffyRNADegradation_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AffyRNADegradation_1.8.0.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: 1.20.0 Depends: R (>= 2.6) Imports: affxparser, affy (>= 1.16), stats, utils, preprocessCore License: GPL (>= 2) Archs: i386, x64 MD5sum: 5cbc7db056fbd052bb5487123ed99efb 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AffyTiling_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AffyTiling_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AffyTiling_1.20.0.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: 1.10.0 Depends: R (>= 2.10), Biobase, GSEABase Imports: stats License: GPL Version 2 or later MD5sum: 9cbf08e9f8bf0fca48ac66f46f8f25a1 NeedsCompilation: no Title: Agreement of Differential Expression Analysis Description: A tool to evaluate agreement of differential expression for cross-species genomics biocViews: Microarray, Genetics, Bioinformatics, GeneExpression Author: Stan Pounds ; Cuilan Lani Gao Maintainer: Cuilan lani Gao source.ver: src/contrib/AGDEX_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AGDEX_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AGDEX_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AGDEX_1.10.0.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: Agi4x44PreProcess Version: 1.22.0 Depends: R (>= 2.10), Biobase, limma, annotate, genefilter Suggests: vsn, affycoretools, hgug4112a.db, GO.db, marray, gplots, gtools, gdata License: GPL-3 MD5sum: b88b89f3902cb5aec94faac537d5f433 NeedsCompilation: no Title: PreProcessing of Agilent 4x44 array data Description: Preprocessing of Agilent 4x44 array data biocViews: Microarray, OneChannel, Preprocessing Author: Pedro Lopez-Romero Maintainer: Pedro Lopez-Romero source.ver: src/contrib/Agi4x44PreProcess_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Agi4x44PreProcess_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Agi4x44PreProcess_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Agi4x44PreProcess_1.22.0.tgz vignettes: vignettes/Agi4x44PreProcess/inst/doc/Agi4x44PreProcess.pdf vignetteTitles: Agi4x44PreProcess hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Agi4x44PreProcess/inst/doc/Agi4x44PreProcess.R Package: agilp Version: 3.4.0 Depends: R (>= 2.14.0) License: GPL-3 MD5sum: 5f565f7534565ab5601f0f98f25863d0 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 Author: Benny Chain Maintainer: Benny Chain source.ver: src/contrib/agilp_3.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/agilp_3.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/agilp_3.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/agilp_3.4.0.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: 2.12.0 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: 0efc7867ed3f7a69945334eb1e2a1950 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,Bioinformatics Author: Pedro Lopez-Romero Maintainer: Pedro Lopez-Romero source.ver: src/contrib/AgiMicroRna_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AgiMicroRna_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AgiMicroRna_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AgiMicroRna_2.12.0.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: 1.0.0 Depends: GenomicRanges, R (>= 3.0.0) Imports: methods, BiocGenerics, Biostrings, IRanges, GenomicFeatures, Rsamtools, AnnotationDbi Suggests: RUnit, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene,SNPlocs.Hsapiens.dbSNP.20120608 License: GPL-3 MD5sum: 0da57422c464231f6e39745cd54637f1 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, HighThroughputSequencing Author: Jesper R Gadin, Lasse Folkersen Maintainer: Jesper R Gadin source.ver: src/contrib/AllelicImbalance_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AllelicImbalance_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AllelicImbalance_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AllelicImbalance_1.0.0.tgz vignettes: vignettes/AllelicImbalance/inst/doc/AllelicImbalance.pdf vignetteTitles: AllelicImbalance hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AllelicImbalance/inst/doc/AllelicImbalance.R Package: altcdfenvs Version: 2.24.0 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: 7ca0c6dd18dc5cb9a347f9afdef36d8f 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_2.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/altcdfenvs_2.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/altcdfenvs_2.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/altcdfenvs_2.24.0.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: 1.0.0 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: 70ece150cf3f6ec43a459deb40741023 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: Bioinformatics, ReportWriting, Transcription, GeneExpression, DifferentialExpression, HighThroughputSequencing, RNAseq, Visualization Author: Alicja Szabelska ; Marek Wiewiorka ; Michal Okoniewski Maintainer: Michal Okoniewski source.ver: src/contrib/ampliQueso_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ampliQueso_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ampliQueso_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ampliQueso_1.0.0.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: 1.34.0 Depends: R (>= 2.5.0), methods, Biobase, GO.db, KEGG.db Imports: AnnotationDbi (>= 0.1.15) Suggests: hgu95av2.db, multtest, tcltk License: LGPL MD5sum: 886859ce049d7b17b5c728b8016e8f20 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/annaffy_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/annaffy_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/annaffy_1.34.0.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, maDB Package: annmap Version: 1.4.1 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: DBI, RMySQL (>= 0.6-0), digest, Biobase, grid, lattice, Rsamtools, genefilter, IRanges, BiocGenerics Suggests: RUnit, rjson License: GPL-2 MD5sum: faf01c8021d3b9cf5cbe007f1aa0745a 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, Bioinformatics, Microarray, OneChannel, ReportWriting, Transcription, Visualization Author: Tim Yates Maintainer: Tim Yates URL: http://annmap.picr.man.ac.uk source.ver: src/contrib/annmap_1.4.1.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/annmap_1.4.1.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: 1.40.1 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: d9121a4211cc5337ab052e867588f909 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_1.40.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/annotate_1.40.1.zip win64.binary.ver: bin/windows64/contrib/3.0/annotate_1.40.1.zip mac.binary.ver: bin/macosx/contrib/3.0/annotate_1.40.1.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: Agi4x44PreProcess, ChromHeatMap, GeneAnswers, geneplotter, GOSim, GSEABase, idiogram, macat, MineICA, MLInterfaces, PCpheno, phenoTest, PREDA, RpsiXML, rTRM, ScISI importsMe: affycoretools, Category, categoryCompare, ChromHeatMap, 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, puma, siggenes, tigre Package: AnnotationDbi Version: 1.24.0 Depends: R (>= 2.7.0), methods, utils, BiocGenerics (>= 0.5.4), Biobase (>= 1.17.0) 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 License: Artistic-2.0 MD5sum: a51f84efd8fff2f48579189ebc67c508 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 source.ver: src/contrib/AnnotationDbi_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AnnotationDbi_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AnnotationDbi_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AnnotationDbi_1.24.0.tgz vignettes: vignettes/AnnotationDbi/inst/doc/AnnotationDbi.pdf, vignettes/AnnotationDbi/inst/doc/databaseTypes.pdf, vignettes/AnnotationDbi/inst/doc/IntroToAnnotationPackages.pdf vignetteTitles: How to use bimaps from the ".db" annotation packages, databaseTypes.pdf, 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, BioNet, CancerMutationAnalysis, Category, categoryCompare, ChIPpeakAnno, ChromHeatMap, clusterProfiler, CoCiteStats, customProDB, domainsignatures, DOSE, ExpressionView, FunciSNP, gCMAP, gCMAPWeb, genefilter, geneplotter, GGBase, GGtools, GlobalAncova, globaltest, GOFunction, GOSemSim, goseq, GOSim, GOstats, goTools, graphite, GSEABase, Gviz, HTSanalyzeR, KEGGprofile, lumi, methyAnalysis, methylumi, MineICA, MiRaGE, OrganismDbi, PADOG, PAnnBuilder, pathview, pcaGoPromoter, PCpheno, phenoTest, qpgraph, ReactomePA, REDseq, rTRM, ScISI, SLGI, tigre, topGO, UniProt.ws, VariantAnnotation, virtualArray suggestsMe: BiocCaseStudies, BiocGenerics, GeneAnswers, GeneRegionScan, GenomicRanges, limma, MmPalateMiRNA, neaGUI, oneChannelGUI, qcmetrics, sigPathway Package: AnnotationForge Version: 1.4.4 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: 89efc9d7879b9be9f8cc35d510d5d857 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_1.4.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/AnnotationForge_1.4.4.zip win64.binary.ver: bin/windows64/contrib/3.0/AnnotationForge_1.4.4.zip mac.binary.ver: bin/macosx/contrib/3.0/AnnotationForge_1.4.4.tgz vignettes: vignettes/AnnotationForge/inst/doc/Homo_sapiens.pdf, vignettes/AnnotationForge/inst/doc/makeProbePackage.pdf, vignettes/AnnotationForge/inst/doc/MakingNewAnnotationPackages.pdf, vignettes/AnnotationForge/inst/doc/SQLForge.pdf vignetteTitles: Homo_sapiens.pdf, 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/NewSchema.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: 1.12.0 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: 465b1d45ef938f5cf33d5158198e3178 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AnnotationFuncs_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AnnotationFuncs_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AnnotationFuncs_1.12.0.tgz vignettes: vignettes/AnnotationFuncs/inst/doc/AnnotationFuncsUserguide.pdf vignetteTitles: Annotation mapping functions hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: AnnotationHub Version: 1.2.0 Depends: IRanges Imports: methods, stats, utils, rjson, BiocGenerics, BiocInstaller (>= 1.11.0), AnnotationDbi, GenomicRanges Suggests: RUnit, RCurl, Rsamtools License: Artistic-2.0 MD5sum: 6e56dec588def852037d7eba9172518b 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 Maintainer: Marc Carlson source.ver: src/contrib/AnnotationHub_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/AnnotationHub_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/AnnotationHub_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/AnnotationHub_1.2.0.tgz vignettes: vignettes/AnnotationHub/inst/doc/AnnotationHub.pdf vignetteTitles: AnnotationHub: A client package for retrieving data from the AnnotationHub web service hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/AnnotationHub/inst/doc/AnnotationHub.R suggestsMe: GenomicRanges Package: annotationTools Version: 1.36.0 Imports: Biobase, stats License: GPL MD5sum: d7788f08d7fadea94e50eed5bcbe5765 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/annotationTools_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/annotationTools_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/annotationTools_1.36.0.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: 1.10.0 Depends: qvalue Imports: multtest, qvalue License: GPL-3 MD5sum: 04c67850100fdc069a05f0332d6fed89 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, HighThroughputSequencing Author: Ola Larsson , Nahum Sonenberg , Robert Nadon Maintainer: Ola Larsson source.ver: src/contrib/anota_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/anota_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/anota_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/anota_1.10.0.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: 1.2.0 Depends: R (>= 3.0), matrixStats (>= 0.5), methods (>= 2.14), Suggests: antiProfilesData, RColorBrewer License: Artistic-2.0 MD5sum: 3fa94f4c18927d10da9dae3e9d1113bc 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/antiProfiles_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/antiProfiles_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/antiProfiles_1.2.0.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: 2.28.0 Depends: R (>= 2.10), graph, RBGL Imports: Rgraphviz, stats, org.Sc.sgd.db License: LGPL MD5sum: 8d8d43a6f30a51afe7cefd70fceb645b 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, GraphsAndNetworks Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/apComplex_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/apComplex_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/apComplex_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/apComplex_2.28.0.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: 1.32.0 Depends: R (>= 2.14.0), matrixStats (>= 0.8.12) Imports: R.methodsS3 (>= 1.5.2), R.oo (>= 1.15.1) Suggests: R.utils (>= 1.27.1), princurve (>= 1.1-12) License: GPL (>= 2) MD5sum: 85f902743bdfa2c0d2d8bb4fec253f6a 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/aroma.light_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/aroma.light_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/aroma.light_1.32.0.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: EDASeq Package: ArrayExpress Version: 1.22.0 Depends: R (>= 2.9.0), Biobase (>= 2.4.0) Imports: XML, affy, limma License: Artistic-2.0 MD5sum: 83f79d7213cd14223cdcf34a474f7443 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ArrayExpress_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ArrayExpress_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ArrayExpress_1.22.0.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: 1.12.0 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: c11106babcfe7c206f16b338e3d2e50c NeedsCompilation: yes Title: ArrayExpress High Throughput Sequencing Processing Pipeline Description: RNA-Seq processing pipeline for public ArrayExpress experiments or local datasets biocViews: RNAseq, Sequencing, HighThroughputSequencing Author: Angela Goncalves, Andrew Tikhonov Maintainer: Angela Goncalves , Andrew Tikhonov source.ver: src/contrib/ArrayExpressHTS_1.12.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/ArrayExpressHTS_1.12.0.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: 1.20.0 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: e9d4466df31eea0f34ef6b2b70caac23 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, Bioinformatics, Microarray, QualityControl Author: Z. Gao, A. Asare, R. Wang, V. Carey Maintainer: V. Carey source.ver: src/contrib/arrayMvout_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/arrayMvout_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/arrayMvout_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/arrayMvout_1.20.0.tgz vignettes: vignettes/arrayMvout/inst/doc/arrayMvout-asdad.pdf, vignettes/arrayMvout/inst/doc/arrayMvout-lkadas.pdf, vignettes/arrayMvout/inst/doc/arrayMvout-lkda.pdf, vignettes/arrayMvout/inst/doc/arrayMvout.pdf vignetteTitles: arrayMvout-asdad.pdf, arrayMvout-lkadas.pdf, arrayMvout-lkda.pdf, 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: 1.40.0 Depends: R (>= 2.2.0) Imports: graphics, grDevices, grid, gridBase, hexbin, limma, marray, methods, RColorBrewer, stats, utils Suggests: mclust, MEEBOdata, HEEBOdata License: LGPL MD5sum: e9686bbea5377e2ecb2da287a4e49cd5 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/arrayQuality_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/arrayQuality_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/arrayQuality_1.40.0.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: 3.18.0 Imports: affy, affyPLM (>= 1.27.3), beadarray, Biobase, Cairo (>= 1.4-6), genefilter, graphics, grDevices, grid, Hmisc, hwriter, lattice, latticeExtra, limma, methods, RColorBrewer, setRNG, simpleaffy, stats, SVGAnnotation (>= 0.9-0), utils, vsn (>= 3.23.3), XML Suggests: ALLMLL, CCl4 License: LGPL (>= 2) MD5sum: 63ce91940ff6b385e3b08e20011c9b77 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 source.ver: src/contrib/arrayQualityMetrics_3.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/arrayQualityMetrics_3.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/arrayQualityMetrics_3.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/arrayQualityMetrics_3.18.0.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: 1.22.0 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: 8072c494442f30d083d6a2b5feb656d1 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, Statistics, DifferentialExpression, Annotation, ReportWriting, Visualization Author: Xiwei Wu, Arthur Li Maintainer: Arthur Li source.ver: src/contrib/ArrayTools_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ArrayTools_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ArrayTools_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ArrayTools_1.22.0.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: 1.0.0 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: 9a73631bda25a10458a6a505c647aab6 NeedsCompilation: no Title: Implementation of wave correction for arrays Description: Wave correction for genotyping and copy number arrays biocViews: Bioinformatics,CopyNumberVariants Author: Eitan Halper-Stromberg Maintainer: Eitan Halper-Stromberg source.ver: src/contrib/ArrayTV_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ArrayTV_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ArrayTV_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ArrayTV_1.0.0.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: 1.2.0 Depends: R (>= 2.15.1), ARRmData License: Artistic-2.0 MD5sum: a9406e9722336fba218eac07eac86604 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ARRmNormalization_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ARRmNormalization_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ARRmNormalization_1.2.0.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: 1.6.0 Depends: R (>= 2.8.0), methods Imports: graphics, methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: 6673c4aa7d12b960a041b1f28e7093a0 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ASEB_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ASEB_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ASEB_1.6.0.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: ASSET Version: 1.0.0 Depends: MASS, msm, rmeta Suggests: RUnit, BiocGenerics License: GPL-2 + file LICENSE MD5sum: a79445ed489f7d285ba4a60402ac624e 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, Bioinformatics Author: Samsiddhi Bhattacharjee, Nilanjan Chatterjee and William Wheeler Maintainer: William Wheeler source.ver: src/contrib/ASSET_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ASSET_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ASSET_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ASSET_1.0.0.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: attract Version: 1.14.0 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: c08fe1b9295c5efc10519f3fee60d631 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: Statistics, GeneExpression Author: Jessica Mar Maintainer: Jessica Mar source.ver: src/contrib/attract_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/attract_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/attract_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/attract_1.14.0.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: 1.22.0 Depends: R (>= 2.10) License: Artistic-2.0 Archs: i386, x64 MD5sum: dbfa07a603252c831f181e9c2c4ade5f 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,Bioinformatics Author: Raphael Gottardo Maintainer: Raphael Gottardo source.ver: src/contrib/BAC_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BAC_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BAC_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BAC_1.22.0.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: 1.0.0 Suggests: pasilla (>= 0.2.10) License: GPL-2 Archs: i386, x64 MD5sum: 72ab95fbc804af05f41cb1fea0c6ccf4 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: HighThroughputSequencing, RNAseq, DifferentialExpression, Software, Bioinformatics, SAGE Author: Andreas Neudecker, Matthias Katzfuss Maintainer: Andreas Neudecker source.ver: src/contrib/BADER_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BADER_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BADER_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BADER_1.0.0.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: 2.2.0 Depends: R (>= 2.10), breastCancerVDX, Biobase License: Artistic-2.0 Archs: i386, x64 MD5sum: 16e4fbb8e688ffa54863bf09ef2dff1c 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. Author: Alejandro Quiroz-Zarate Maintainer: Alejandro Quiroz-Zarate source.ver: src/contrib/BAGS_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BAGS_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BAGS_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BAGS_2.2.0.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: 1.2.0 Depends: R (>= 2.15.0), RCurl, RJSONIO Imports: methods Suggests: RUnit License: Apache License 2.0 MD5sum: 4cd252dfb2a191f771eab32e7a41b0b0 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BaseSpaceR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BaseSpaceR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BaseSpaceR_1.2.0.tgz vignettes: vignettes/BaseSpaceR/inst/doc/BaseSpaceR-QscoreApp.pdf, vignettes/BaseSpaceR/inst/doc/BaseSpaceR.pdf vignetteTitles: BaseSpaceR-QscoreApp.pdf, BaseSpaceR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BaseSpaceR/inst/doc/BaseSpaceR.R Package: BayesPeak Version: 1.14.0 Depends: R (>= 2.14), IRanges Imports: IRanges, graphics License: GPL (>= 2) Archs: i386, x64 MD5sum: dff4f1be832052b7dd16338ba117b662 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BayesPeak_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BayesPeak_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BayesPeak_1.14.0.tgz vignettes: vignettes/BayesPeak/inst/doc/BayesPeak.pdf, vignettes/BayesPeak/inst/doc/regionOFdiag.pdf vignetteTitles: BayesPeak Vignette, regionOFdiag.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BayesPeak/inst/doc/BayesPeak.R Package: baySeq Version: 1.16.0 Depends: R (>= 2.3.0), methods, GenomicRanges Suggests: snow, edgeR License: GPL-3 MD5sum: 7cdea501c8fae9944715ab921f596bc8 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/baySeq_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/baySeq_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/baySeq_1.16.0.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: segmentSeq suggestsMe: oneChannelGUI Package: BCRANK Version: 1.24.0 Depends: methods Imports: Biostrings Suggests: seqLogo License: GPL-2 Archs: i386, x64 MD5sum: 1d0839ac8c451b4f788b0c83953765a1 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BCRANK_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BCRANK_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BCRANK_1.24.0.tgz vignettes: vignettes/BCRANK/inst/doc/BCRANK_intro_fig1.pdf, vignettes/BCRANK/inst/doc/BCRANK_intro_fig2.pdf, vignettes/BCRANK/inst/doc/BCRANK.pdf vignetteTitles: BCRANK_intro_fig1.pdf, BCRANK_intro_fig2.pdf, BCRANK hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BCRANK/inst/doc/BCRANK.R Package: beadarray Version: 2.12.0 Depends: R (>= 2.13.0), BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), methods, ggplot2 Imports: BeadDataPackR, limma, AnnotationDbi, stats4, BiocGenerics, reshape2 Suggests: lumi, vsn, affy, hwriter, beadarrayExampleData, illuminaHumanv3.db, gridExtra License: GPL-2 Archs: i386, x64 MD5sum: ac90632c43b62a917bfff988d81361a4 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 source.ver: src/contrib/beadarray_2.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/beadarray_2.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/beadarray_2.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/beadarray_2.12.0.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: 1.28.0 Depends: methods, Biobase (>= 2.5.5), quantsmooth Suggests: aCGH, affy, limma, snapCGH, beadarray, DNAcopy License: GPL-2 MD5sum: 307ef166f20f50e1e1fa7beea517101f 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: CopyNumberVariants, SNP, GeneticVariability, TwoChannel, Preprocessing, DataImport Author: Jan Oosting Maintainer: Jan Oosting source.ver: src/contrib/beadarraySNP_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/beadarraySNP_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/beadarraySNP_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/beadarraySNP_1.28.0.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: 1.14.0 License: GPL-2 Archs: i386, x64 MD5sum: 5e2f32b87defbaf33c16e20ba0a5122d 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BeadDataPackR_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BeadDataPackR_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BeadDataPackR_1.14.0.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: betr Version: 1.18.0 Depends: R(>= 2.6.0) Imports: Biobase (>= 2.5.5), limma, mvtnorm, methods, stats Suggests: Biobase License: LGPL MD5sum: b6a9fb11171b9a6daa54eccb3153e6b8 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, Bioinformatics, DifferentialExpression, TimeCourse Author: Martin Aryee Maintainer: Martin Aryee source.ver: src/contrib/betr_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/betr_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/betr_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/betr_1.18.0.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: 1.24.1 Depends: made4, seqinr,ade4 License: Artistic-2.0 MD5sum: 24f169475ec098c1cc8f0f03ac775239 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: Bioinformatics,Classification Author: Iain Wallace Maintainer: Iain Wallace source.ver: src/contrib/bgafun_1.24.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/bgafun_1.24.1.zip win64.binary.ver: bin/windows64/contrib/3.0/bgafun_1.24.1.zip mac.binary.ver: bin/macosx/contrib/3.0/bgafun_1.24.1.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: 1.22.0 Depends: R (>= 2.3.1), KernSmooth License: GPL-2 MD5sum: 665394cfa3d83d69f03aea0510e21384 NeedsCompilation: yes Title: Bayesian models for differential gene expression Description: Fully Bayesian mixture models for differential gene expression biocViews: Microarray, DifferentialExpression, MultipleComparisons Author: Alex Lewin, Natalia Bochkina Maintainer: Alex Lewin source.ver: src/contrib/BGmix_1.22.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/BGmix_1.22.0.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: 1.28.0 Depends: R (>= 2.0.1), Biobase, affy (>= 1.5.0), gcrma (>= 2.4.1) Suggests: affydata, hgu95av2cdf License: GPL-2 Archs: i386, x64 MD5sum: 0eaf2459cdd4c2bc3660a7b6190844e5 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bgx_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bgx_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bgx_1.28.0.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: 1.14.0 License: GPL-3 Archs: i386, x64 MD5sum: f77f1a9fb82676cc20571436c240d2da 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BHC_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BHC_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BHC_1.14.0.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: 1.20.0 Depends: R (>= 1.8.0), Biobase (>= 2.5.5), multtest, GSEABase License: GPL-2 Archs: i386, x64 MD5sum: e8449fa668030b3bc71ac10496795f96 NeedsCompilation: yes Title: Biclustering Analysis and Results Exploration Description: Biclustering Analysis and Results Exploration biocViews: Microarray, Transcription, Bioinformatics, Clustering Author: Pierre Gestraud Maintainer: Pierre Gestraud URL: http://bioinfo.curie.fr source.ver: src/contrib/BicARE_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BicARE_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BicARE_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BicARE_1.20.0.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: 1.0.0 Depends: R (>= 2.14.0), rsbml, hyperdraw, LIM Imports: hypergraph License: file LICENSE MD5sum: 4fc3c900f11858b58d4fef0cc753c917 NeedsCompilation: no Title: Creates an interface to the BiGG database, provides a framework for simulation and produces flux graphs 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: NetworkAnalysis, Visualization, Metabolomics Author: Anand K. Gavai, Hannes Hettling Maintainer: Anand K. Gavai , Hannes Hettling URL: http://www.bioconductor.org/ source.ver: src/contrib/BiGGR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiGGR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BiGGR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BiGGR_1.0.0.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: 1.6.1 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: 6cd39bb82a88589b211804080a25b05f 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_1.6.1.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/bigmemoryExtras_1.6.1.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: 1.0.0 Depends: R (>= 3.0.1), DBI, RSQLite, methods Imports: XML Suggests: BiocStyle, RCurl, ape, ChemmineR License: Artistic-2.0 MD5sum: 8db90aa8246cb56cde35311345883753 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, Bioinformatics, Proteomics Author: Tyler Backman, Ronly Schlenk, Thomas Girke Maintainer: Tyler Backman source.ver: src/contrib/bioassayR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bioassayR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bioassayR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bioassayR_1.0.0.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: 2.22.0 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), utils Imports: methods, BiocGenerics Suggests: tools, tkWidgets, ALL, RUnit, golubEsets License: Artistic-2.0 Archs: i386, x64 MD5sum: 97b4dd96418b87b47d62c955d54924b7 NeedsCompilation: yes Title: Biobase: Base functions for Bioconductor Description: Functions that are needed by many other packages or which replace R functions. biocViews: Infrastructure, Bioinformatics Author: R. Gentleman, V. Carey, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Biobase_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Biobase_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Biobase_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Biobase_2.22.0.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, Agi4x44PreProcess, 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, ddCt, DESeq, DEXSeq, DFP, DSS, dyebias, easyRNASeq, EBarrays, EDASeq, eisa, epigenomix, epivizr, ExiMiR, fabia, factDesign, fastseg, flowBeads, flowClust, frma, gaga, GeneAnswers, GeneExpressionSignature, GeneMeta, geneplotter, geneRecommender, GeneRegionScan, GeneSelectMMD, GeneSelector, geNetClassifier, genoset, GEOquery, GOFunction, goProfiles, GOstats, GSEABase, GSEAlm, GWASTools, hapFabia, HCsnip, HELP, hopach, HTqPCR, htSeqTools, HTSFilter, HybridMTest, idiogram, inSilicoDb, inSilicoMerging, isobar, iterativeBMA, LMGene, lumi, macat, maDB, maSigPro, MergeMaid, metagenomeSeq, methyAnalysis, methylumi, Mfuzz, MiChip, MineICA, minfi, MiRaGE, MLInterfaces, MmPalateMiRNA, MSnbase, Mulcom, multtest, NOISeq, NormqPCR, nucleR, oligo, oneChannelGUI, OrderedList, OTUbase, OutlierD, PADOG, PAnnBuilder, panp, pcaMethods, pcot2, pdInfoBuilder, pdmclass, PGSEA, phenoTest, plgem, PLPE, plrs, prada, PREDA, PROMISE, puma, qpcrNorm, R453Plus1Toolbox, RbcBook1, rbsurv, ReadqPCR, reb, RefPlus, Resourcerer, rHVDM, Ringo, Risa, Rmagpie, rMAT, RNAinteract, rnaSeqMap, Roleswitch, RpsiXML, rqubic, RTopper, Rtreemix, safe, SCAN.UPC, SeqGSEA, sigaR, siggenes, simpleaffy, SpeCond, SPEM, spkTools, splicegear, stepwiseCM, TDARACNE, tigre, tilingArray, topGO, tspair, twilight, VegaMC, vsn, waveTiling, webbioc, xcms, XDE importsMe: ABarray, aCGH, adSplit, affyILM, affyQCReport, AgiMicroRna, annmap, annotate, AnnotationDbi, AnnotationForge, annotationTools, ArrayExpressHTS, arrayQualityMetrics, ArrayTools, attract, betr, bigmemoryExtras, biocViews, BioSeqClass, BiSeq, BrainStars, bsseq, Category, CGHnormaliter, charm, ChIPXpress, ChromHeatMap, clipper, ConsensusClusterPlus, crlmm, cycle, EBarrays, ecolitk, epigenomix, ExiMiR, farms, ffpe, flowCore, flowFlowJo, flowFP, flowMeans, flowQB, flowStats, flowType, flowUtils, flowViz, flowWorkspace, frma, frmaTools, gCMAP, gCMAPWeb, gcrma, genefilter, GeneMeta, geneRecommender, GeneRegionScan, GeneSelectMMD, genomeIntervals, GenomicFeatures, GEOsubmission, GGBase, ggbio, GGtools, girafe, globaltest, gmapR, GOFunction, GOstats, GSRI, GSVA, Gviz, Harshlight, HEM, HiTC, hopach, HTqPCR, IdMappingAnalysis, imageHTS, lapmix, LiquidAssociation, lumi, maanova, makecdfenv, maSigPro, mBPCR, MCRestimate, metaArray, methyAnalysis, methylumi, MiChip, MinimumDistance, MiPP, MmPalateMiRNA, multiscan, mzR, nucleR, oligoClasses, OrderedList, PADOG, PAnnBuilder, panp, pcaGoPromoter, PCpheno, piano, plateCore, plier, ppiStats, prada, PROMISE, puma, pvac, pvca, qcmetrics, qpgraph, QuasR, qusage, R453Plus1Toolbox, randPack, ReadqPCR, RGalaxy, Rmagpie, rMAT, rols, rqubic, rSFFreader, Rtreemix, SAGx, ShortRead, SimBindProfiles, simpleaffy, SLGI, SNPchip, spade, spkTools, splicegear, supraHex, synapter, TEQC, tigre, timecourse, topGO, TSSi, twilight, VanillaICE, VariantAnnotation, virtualArray, XDE suggestsMe: annotate, betr, BiocCaseStudies, BiocGenerics, biocViews, BSgenome, Category, DART, DESeq2, farms, genefilter, genefu, GlobalAncova, globaltest, Heatplus, les, nem, OSAT, pkgDepTools, ROC, survcomp, TargetScore, tkWidgets, TypeInfo, vbmp, widgetTools Package: BiocCaseStudies Version: 1.24.0 Depends: tools, 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: 3db901e026036f42fd2873a49baa7e9a NeedsCompilation: no Title: BiocCaseStudies: Support for the Case Studies Monograph Description: Software and data to support the case studies. biocViews: Infrastructure, Bioinformatics Author: R. Gentleman, W. Huber, F. Hahne, M. Morgan, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocCaseStudies_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiocCaseStudies_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BiocCaseStudies_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BiocCaseStudies_1.24.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: BiocGenerics Version: 0.8.0 Depends: methods, graphics, stats, parallel Imports: methods, graphics, stats, parallel Suggests: Biobase, IRanges, GenomicRanges, AnnotationDbi, oligoClasses, oligo, affyPLM, flowClust, affy, RUnit, DESeq2 License: Artistic-2.0 MD5sum: 6a6c9276b28bc1839c605ac8809a4d3a NeedsCompilation: no Title: 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_0.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiocGenerics_0.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BiocGenerics_0.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BiocGenerics_0.8.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affy, affyPLM, altcdfenvs, AnnotationDbi, AnnotationForge, beadarray, Biobase, Biostrings, BSgenome, bsseq, Category, categoryCompare, ChIPpeakAnno, chipseq, ChIPseqR, ChromHeatMap, cleanUpdTSeq, cn.mops, codelink, copynumber, cummeRbund, DESeq, dexus, EDASeq, ensemblVEP, flowQ, geneplotter, genomeIntervals, GenomicFeatures, GenomicRanges, Genominator, genoset, GSEABase, gwascat, htSeqTools, interactiveDisplay, IRanges, minfi, MinimumDistance, MotIV, MSnbase, nucleR, oligo, oligoClasses, PICS, PSICQUIC, PWMEnrich, R453Plus1Toolbox, REDseq, Repitools, rMAT, rsbml, rSFFreader, SeqGSEA, ShortRead, simpleaffy, SplicingGraphs, TEQC, tigre, TSSi, VariantAnnotation, virtualArray, xcms, XVector importsMe: affyPLM, AllelicImbalance, annmap, annotate, AnnotationDbi, AnnotationForge, AnnotationHub, ArrayExpressHTS, beadarray, bigmemoryExtras, Biobase, biocGraph, Biostrings, biovizBase, BiSeq, Category, cghMCR, ChemmineOB, ChemmineR, ChIPpeakAnno, chipseq, ChromHeatMap, cn.farms, cn.mops, crlmm, cummeRbund, DESeq2, DEXSeq, DrugVsDisease, easyRNASeq, EBImage, EDASeq, eiR, eisa, epigenomix, fastseg, ffpe, flowClust, flowCore, flowFP, flowMerge, flowQ, flowStats, flowWorkspace, frma, gCMAP, gCMAPWeb, geNetClassifier, GenomicFeatures, GenomicRanges, GGBase, ggbio, GGtools, graph, GSVA, Gviz, hopach, HTSeqGenie, intansv, IRanges, KCsmart, LVSmiRNA, methylumi, MinimumDistance, MiRaGE, MotifDb, MotIV, nucleR, oligo, oligoClasses, OrganismDbi, pcaMethods, PING, plrs, prada, ProCoNA, pRoloc, QuasR, R453Plus1Toolbox, RCytoscape, REDseq, ReportingTools, RGalaxy, Ringo, rMAT, Rsamtools, rsbml, rtracklayer, simpleaffy, SLGI, snpStats, spliceSites, SplicingGraphs, Streamer, tigre, triform, TSSi, UniProt.ws, VariantAnnotation, VariantTools, XDE, XVector suggestsMe: ArrayTV, ASSET, bigmemoryExtras, BiocInstaller, BiocParallel, BiRewire, bumphunter, CAMERA, CellNOptR, CexoR, ChIPpeakAnno, ChIPXpress, clipper, clonotypeR, CNORfeeder, CNORfuzzy, cobindR, dagLogo, DBChIP, DNaseR, ensemblVEP, FGNet, GENE.E, GeneNetworkBuilder, GOstats, GraphPAC, GWASTools, illuminaio, inSilicoMerging, KEGGREST, motifStack, NetSAM, PathNet, pathview, plethy, rBiopaxParser, Rcade, Rgraphviz, ROntoTools, RTN, rTRM, SANTA, SeqArray, SeqVarTools, SpacePAC, STRINGdb, TCC Package: biocGraph Version: 1.24.0 Depends: Rgraphviz, graph Imports: Rgraphviz, geneplotter, graph, BiocGenerics, methods Suggests: fibroEset, geneplotter, hgu95av2.db License: Artistic-2.0 MD5sum: 73a6e1db237a32256d4c1504c3f943e4 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: NetworkVisualization, GraphsAndNetworks Author: Li Long , Robert Gentleman , Seth Falcon Florian Hahne Maintainer: Florian Hahne source.ver: src/contrib/biocGraph_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/biocGraph_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/biocGraph_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/biocGraph_1.24.0.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: 1.12.1 Depends: R (>= 3.0.0) Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: 41aa32a5224689befb45cb6f478da724 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_1.12.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiocInstaller_1.12.1.zip win64.binary.ver: bin/windows64/contrib/3.0/BiocInstaller_1.12.1.zip mac.binary.ver: bin/macosx/contrib/3.0/BiocInstaller_1.12.1.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affylmGUI importsMe: affy, AnnotationHub, gcrma, oligoClasses, QuasR, webbioc suggestsMe: GOSemSim, pkgDepTools Package: BiocParallel Version: 0.4.1 Imports: methods, parallel, foreach, tools, BatchJobs, BBmisc Suggests: BiocGenerics, doParallel, RUnit License: GPL-2 | GPL-3 MD5sum: 11dfccf3754a20ebf4e5ccf9bdd6183f 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: HighThroughputSequencing, Infrastructure Author: Martin Morgan and contributions from Ryan Thompson , Michel Lang Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/BiocParallel_0.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiocParallel_0.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/BiocParallel_0.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/BiocParallel_0.4.1.tgz hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: HTSeqGenie importsMe: VariantTools suggestsMe: chimera Package: BiocStyle Version: 1.0.0 License: Artistic-2.0 MD5sum: 7589b4ccbd9c9c191ad38bbfd6973ec4 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiocStyle_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BiocStyle_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BiocStyle_1.0.0.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: AnnotationForge, bioassayR, ChemmineOB, ChemmineR, cleaver, dagLogo, DESeq2, DEXSeq, easyRNASeq, EBImage, fmcsR, GenomicRanges, illuminaio, imageHTS, motifStack, omicade4, qpgraph, QuasR, rfPred, Rsamtools, SigFuge, VariantAnnotation Package: biocViews Version: 1.30.1 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: 2c5924c42da8c191c2642c8eb5eac711 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_1.30.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/biocViews_1.30.1.zip win64.binary.ver: bin/windows64/contrib/3.0/biocViews_1.30.1.zip mac.binary.ver: bin/macosx/contrib/3.0/biocViews_1.30.1.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 Package: bioDist Version: 1.34.0 Depends: R (>= 2.0), methods, Biobase,KernSmooth Suggests: locfit License: Artistic-2.0 MD5sum: 7b44369e5bd739ca22c6c1d61e599f57 NeedsCompilation: no Title: Different distance measures Description: A collection of software tools for calculating distance measures. biocViews: Bioinformatics Author: B. Ding, R. Gentleman and Vincent Carey Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/bioDist_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bioDist_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bioDist_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bioDist_1.34.0.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: 2.18.0 Depends: methods Imports: utils, XML, RCurl Suggests: annotate License: Artistic-2.0 MD5sum: 2692dafbad92824a549ed451d5fccabc 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_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/biomaRt_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/biomaRt_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/biomaRt_2.18.0.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, easyRNASeq, genefu, GenomeGraphs, MineICA, PSICQUIC, Roleswitch, SeqGSEA, shinyTANDEM, VegaMC importsMe: affycoretools, ArrayExpressHTS, ChIPpeakAnno, cobindR, customProDB, DEXSeq, GenomicFeatures, Gviz, HTSanalyzeR, IdMappingRetrieval, MEDIPS, methyAnalysis, phenoTest, R453Plus1Toolbox, RNAither suggestsMe: BiocCaseStudies, GeneAnswers, GenomicFeatures, Genominator, Gviz, isobar, maDB, MineICA, MiRaGE, oneChannelGUI, piano, Rcade, RIPSeeker, rTANDEM, rTRM, ShortRead, SIM Package: BioMVCClass Version: 1.30.0 Depends: R (>= 2.1.0), methods, MVCClass, Biobase, graph, Rgraphviz License: LGPL MD5sum: 602bbc3699961f9d91cc759fdce173ba NeedsCompilation: no Title: Model-View-Controller (MVC) Classes That Use Biobase Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphsAndNetworks Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/BioMVCClass_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BioMVCClass_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BioMVCClass_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BioMVCClass_1.30.0.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: 1.2.0 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: cbe48661fc23c82ef6faca64a6278ad3 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, CopyNumberVariants, Microarray, HighThroughputSequencing, Sequencing, Visualization, Genetics Author: Yang Du Maintainer: Yang Du source.ver: src/contrib/biomvRCNS_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/biomvRCNS_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/biomvRCNS_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/biomvRCNS_1.2.0.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: 1.23.2 Depends: R (>= 2.10.0), Biobase, graph, RBGL Imports: igraph, AnnotationDbi Suggests: rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML License: GPL (>= 2) MD5sum: ffc69c9be7b3c656555132666a737ee1 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, GraphsAndNetworks, NetworkAnalysis, 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_1.23.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/BioNet_1.23.2.zip win64.binary.ver: bin/windows64/contrib/3.0/BioNet_1.23.2.zip mac.binary.ver: bin/macosx/contrib/3.0/BioNet_1.23.2.tgz vignettes: vignettes/BioNet/inst/doc/bum1.pdf, vignettes/BioNet/inst/doc/bum2.pdf, vignettes/BioNet/inst/doc/cytoscape.pdf, vignettes/BioNet/inst/doc/prec_recall_large.pdf, vignettes/BioNet/inst/doc/prec_recall_small.pdf, vignettes/BioNet/inst/doc/Tutorial-3dplot.pdf, vignettes/BioNet/inst/doc/Tutorial.pdf vignetteTitles: bum1.pdf, bum2.pdf, cytoscape.pdf, prec_recall_large.pdf, prec_recall_small.pdf, Tutorial-3dplot.pdf, BioNet Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioNet/inst/doc/Tutorial.R importsMe: HTSanalyzeR Package: BioSeqClass Version: 1.20.0 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: 9352fbae23c13a7241aa388973910d3b 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BioSeqClass_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BioSeqClass_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BioSeqClass_1.20.0.tgz vignettes: vignettes/BioSeqClass/inst/doc/BioSeqClass.pdf, vignettes/BioSeqClass/inst/doc/cvFFSClassify0005.pdf, vignettes/BioSeqClass/inst/doc/FeatureSets16.pdf, vignettes/BioSeqClass/inst/doc/workflow.pdf vignetteTitles: Using the BioSeqClass Package, cvFFSClassify0005.pdf, FeatureSets16.pdf, workflow.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BioSeqClass/inst/doc/BioSeqClass.R Package: Biostrings Version: 2.30.1 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.5.4), IRanges (>= 1.19.34), XVector (>= 0.1.3) Imports: graphics, methods, stats, utils, BiocGenerics, IRanges, XVector 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, affydata (>= 1.11.5), RUnit Enhances: Rmpi License: Artistic-2.0 Archs: i386, x64 MD5sum: acf4d4047855f20096e751cf5fadbf5e 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_2.30.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Biostrings_2.30.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Biostrings_2.30.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Biostrings_2.30.1.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, BRAIN, BSgenome, ChIPpeakAnno, ChIPsim, cleaver, CorMut, DASiR, DECIPHER, deepSNV, easyRNASeq, GeneRegionScan, genomes, iPAC, methVisual, minfi, MotifDb, motifRG, oligo, oneChannelGUI, qrqc, R453Plus1Toolbox, REDseq, rGADEM, Roleswitch, Rsamtools, rSFFreader, RSVSim, SCAN.UPC, seqbias, ShortRead, triplex, waveTiling importsMe: AffyCompatible, AllelicImbalance, ArrayExpressHTS, BCRANK, BioSeqClass, biovizBase, charm, ChIPpeakAnno, ChIPseqR, ChIPsim, cobindR, customProDB, dagLogo, DECIPHER, ensemblVEP, gcrma, GeneRegionScan, GenomicFeatures, girafe, gmapR, Gviz, gwascat, h5vc, HiTC, HTSeqGenie, KEGGREST, MEDIPS, MEDME, methVisual, microRNA, MotIV, oligoClasses, OTUbase, pdInfoBuilder, phyloseq, qrqc, QuasR, R453Plus1Toolbox, REDseq, Repitools, rGADEM, Rolexa, rSFFreader, rtracklayer, SeqArray, TFBSTools, VariantAnnotation, VariantTools suggestsMe: annotate, CSAR, exomeCopy, GenomicFeatures, GenomicRanges, genoset, methylumi, microRNA, MiRaGE, pcaGoPromoter, procoil, rTRM, XVector Package: biovizBase Version: 1.10.8 Depends: R (>= 2.10), methods Imports: methods, grDevices, stats, scales, Hmisc, RColorBrewer, dichromat, BiocGenerics, IRanges, GenomicRanges (>= 1.13.3), Biostrings, Rsamtools (>= 1.13.1), GenomicFeatures Suggests: BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome, rtracklayer License: Artistic-2.0 Archs: i386, x64 MD5sum: 84d1fa577594b3e92f3f86bf00a721ce 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, Bioinformatics, Preprocessing Author: Tengfei Yin, Michael Lawrence, Dianne Cook Maintainer: Tengfei Yin source.ver: src/contrib/biovizBase_1.10.8.tar.gz win.binary.ver: bin/windows/contrib/3.0/biovizBase_1.10.8.zip win64.binary.ver: bin/windows64/contrib/3.0/biovizBase_1.10.8.zip mac.binary.ver: bin/macosx/contrib/3.0/biovizBase_1.10.8.tgz vignettes: vignettes/biovizBase/inst/doc/intro-shrink-single.pdf, vignettes/biovizBase/inst/doc/intro-shrinkageFun.pdf, vignettes/biovizBase/inst/doc/intro.pdf vignetteTitles: intro-shrink-single.pdf, intro-shrinkageFun.pdf, An Introduction to biovizBase hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/biovizBase/inst/doc/intro.R dependsOnMe: qrqc importsMe: ggbio, Gviz, qrqc Package: BiRewire Version: 1.2.2 Depends: igraph Suggests: RUnit, BiocGenerics License: GPL-3 Archs: i386, x64 MD5sum: 40309f383af4d5d69c46179d431a44a9 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. 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_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiRewire_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/BiRewire_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/BiRewire_1.2.2.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: 1.6.0 Depends: limma, MASS, R(>= 2.10), Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 51ffd86e934ac4c576428950de879607 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, Bioinformatics, GraphsAndNetworks Author: Benedikt Zacher, Khalid Abnaof, Stephan Gade, Erfan Younesi, Achim Tresch, Holger Froehlich Maintainer: Benedikt Zacher , Holger Froehlich source.ver: src/contrib/birta_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/birta_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/birta_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/birta_1.6.0.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: 1.2.5 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: 9aff1970f699a2811f7fa70c9874dc64 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, HighThroughputSequencing, Methylseq, DNAMethylation Author: Katja Hebestreit, Hans-Ulrich Klein Maintainer: Katja Hebestreit source.ver: src/contrib/BiSeq_1.2.5.tar.gz win.binary.ver: bin/windows/contrib/3.0/BiSeq_1.2.5.zip win64.binary.ver: bin/windows64/contrib/3.0/BiSeq_1.2.5.zip mac.binary.ver: bin/macosx/contrib/3.0/BiSeq_1.2.5.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: 1.6.1 Depends: Rsamtools, zlibbioc Imports: IRanges LinkingTo: Rsamtools, zlibbioc Suggests: edgeR, DESeq License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: a40900434d3c3d234682a29fbe532f8f 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, HighThroughputSequencing, RNAseq Author: Peter Glaus, Antti Honkela and Magnus Rattray Maintainer: Peter Glaus source.ver: src/contrib/BitSeq_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/BitSeq_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.0/BitSeq_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.0/BitSeq_1.6.1.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: 1.8.0 Depends: R (>= 2.8.1), PolynomF, Biostrings, lattice License: GPL-2 MD5sum: 8d90eb93569f446145972496d5450970 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: Bioinformatics, MassSpectrometry, Proteomics Author: Piotr Dittwald, with contributions of Dirk Valkenborg and Jurgen Claesen Maintainer: Piotr Dittwald source.ver: src/contrib/BRAIN_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BRAIN_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BRAIN_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BRAIN_1.8.0.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: 1.6.0 Depends: RCurl, Biobase, methods Imports: RJSONIO, Biobase License: Artistic-2.0 MD5sum: 648da8c4f092fc9aa08fad90e3da2f91 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BrainStars_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BrainStars_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BrainStars_1.6.0.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: 1.26.0 Depends: R (>= 1.9.0), rama License: GPL (>= 2) Archs: i386, x64 MD5sum: 3307670492a5852c61ec41da3d162573 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bridge_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bridge_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bridge_1.26.0.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: 1.30.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.1.2), IRanges (>= 1.13.6), GenomicRanges (>= 1.11.46), Biostrings (>= 2.23.3) Suggests: RUnit, BSgenome.Celegans.UCSC.ce2 (>= 1.3.11), BSgenome.Hsapiens.UCSC.hg19 (>= 1.3.11), SNPlocs.Hsapiens.dbSNP.20100427, hgu95av2probe, Biobase License: Artistic-2.0 MD5sum: 6ae0eaf797f1b64fc72f0be329fd3a0c 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BSgenome_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BSgenome_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BSgenome_1.30.0.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, ChIPpeakAnno, chipseq, cleanUpdTSeq, htSeqTools, MEDIPS, motifRG, REDseq, rGADEM importsMe: charm, ChIPpeakAnno, chipseq, cobindR, ggbio, girafe, gmapR, Gviz, MEDIPS, MethylSeekR, PING, QuasR, R453Plus1Toolbox, Repitools, rtracklayer, VariantAnnotation suggestsMe: Biostrings, biovizBase, easyRNASeq, GeneRegionScan, GenomicFeatures, GenomicRanges, genoset, MEDIPS, MiRaGE, oneChannelGUI, spliceR, waveTiling Package: bsseq Version: 0.10.0 Depends: R (>= 2.15), methods, BiocGenerics, IRanges, GenomicRanges, parallel, matrixStats Imports: scales, stats, graphics, Biobase, locfit Suggests: RUnit, bsseqData License: Artistic-2.0 MD5sum: bdbff8058544100d2a87b49673d1cf1a 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 Maintainer: Kasper Daniel Hansen source.ver: src/contrib/bsseq_0.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bsseq_0.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bsseq_0.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bsseq_0.10.0.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: 1.26.0 Depends: R (>= 2.6.0), methods License: LGPL (>= 2) Archs: i386, x64 MD5sum: 0c940a510f96f364413280e77d080298 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BufferedMatrix_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BufferedMatrix_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BufferedMatrix_1.26.0.tgz vignettes: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture1.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture2.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture3.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture4.pdf, vignettes/BufferedMatrix/inst/doc/BufferedMatrixPicture5.pdf vignetteTitles: BufferedMatrix: Introduction, BufferedMatrixPicture1.pdf, BufferedMatrixPicture2.pdf, BufferedMatrixPicture3.pdf, BufferedMatrixPicture4.pdf, BufferedMatrixPicture5.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/BufferedMatrix/inst/doc/BufferedMatrix.R dependsOnMe: BufferedMatrixMethods Package: BufferedMatrixMethods Version: 1.26.0 Depends: R (>= 2.6.0), BufferedMatrix (>= 1.3.0), methods LinkingTo: BufferedMatrix Suggests: affyio, affy License: GPL (>= 2) Archs: i386, x64 MD5sum: 7af6cd3667a779dd049db9926c90177c 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BufferedMatrixMethods_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BufferedMatrixMethods_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BufferedMatrixMethods_1.26.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: bumphunter Version: 1.2.0 Depends: R (>= 2.10), IRanges, GenomicRanges, foreach, iterators, methods, parallel, locfit Imports: matrixStats, limma, itertools, doRNG Suggests: RUnit, BiocGenerics, doParallel, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene License: Artistic-2.0 MD5sum: e4abf997b3a877753860a719b69cdd7e NeedsCompilation: no Title: Bump Hunter Description: Tools for finding bumps in genomic data biocViews: DNAMethylation, Epigenetics, Infrastructure, MultipleComparisons Author: Rafael A. Irizarry, Martin Aryee, Hector Corrada Bravo, Kasper D. Hansen, Harris A. Jaffee Maintainer: Rafael A. Irizarry source.ver: src/contrib/bumphunter_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/bumphunter_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/bumphunter_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/bumphunter_1.2.0.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: 1.18.0 Depends: R (>= 2.3.0), minet Imports: stats License: GPL-3 Archs: i386, x64 MD5sum: bbbed27bfcd89ab5df3eccb53cadf824 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/BUS_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/BUS_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/BUS_1.18.0.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: CAGEr Version: 1.4.1 Depends: methods, R (>= 2.15.0), BSgenome, BSgenome.Mmusculus.UCSC.mm9 Imports: Rsamtools, GenomicRanges, IRanges, data.table, beanplot, rtracklayer, som, VGAM Suggests: BSgenome.Drerio.UCSC.danRer7, BSgenome.Hsapiens.UCSC.hg18, FANTOM3and4CAGE Enhances: parallel License: GPL-3 MD5sum: 6785df5778e0b633acbea8011f874807 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_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/CAGEr_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/CAGEr_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/CAGEr_1.4.1.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: 1.28.0 Depends: R (>= 2.10), limma, methods Imports: limma, methods, graphics, stats, utils License: LGPL Archs: i386, x64 MD5sum: 59f5921138731bd8510ac0b075c8aed9 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CALIB_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CALIB_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CALIB_1.28.0.tgz vignettes: vignettes/CALIB/inst/doc/quickstart.pdf, vignettes/CALIB/inst/doc/readme.pdf vignetteTitles: CALIB Overview, readme.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CALIB/inst/doc/quickstart.R Package: CAMERA Version: 1.18.0 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: f78029f0b0c4de88ec234bbc67b0acf3 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CAMERA_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CAMERA_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CAMERA_1.18.0.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 suggestsMe: RMassBank Package: cancerclass Version: 1.6.0 Depends: R (>= 2.14.0), Biobase, binom, methods, stats License: GPL 3 Archs: i386, x64 MD5sum: d6c10065f6673b5c049cac5fae85f44a 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cancerclass_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cancerclass_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cancerclass_1.6.0.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: 1.6.0 Depends: R (>= 2.10.0), qvalue Imports: AnnotationDbi, limma, methods, stats Suggests: KEGG.db License: GPL (>= 2) + file LICENSE Archs: i386, x64 MD5sum: 0937a66c58d7bb48a4165d2cd463e527 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, Bioinformatics, Software Author: Giovanni Parmigiani, Simina M. Boca Maintainer: Simina M. Boca source.ver: src/contrib/CancerMutationAnalysis_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CancerMutationAnalysis_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CancerMutationAnalysis_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CancerMutationAnalysis_1.6.0.tgz vignettes: vignettes/CancerMutationAnalysis/inst/doc/CancerMutationAnalysis.pdf vignetteTitles: CancerMutationAnalysisTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Package: casper Version: 1.4.0 Depends: R (>= 2.14.1), Biobase, IRanges, methods, gtools, GenomicRanges, Rsamtools, plyr, gaga Imports: VGAM, mgcv, GenomicFeatures, survival, sqldf Enhances: parallel License: GPL (>=2) Archs: i386, x64 MD5sum: a820e172f60067cdc1aa9cc2fc81bff9 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: Bioinformatics, GeneExpression, DifferentialExpression, Transcription, RNASeq, HighThroughputSequencing Author: David Rossell, Camille Stephan-Otto, Manuel Kroiss, Miranda Stobbe Maintainer: David Rossell source.ver: src/contrib/casper_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/casper_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/casper_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/casper_1.4.0.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: 2.28.0 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: df3a4c6b3719932e0cbff905c4f3a8fc 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_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Category_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Category_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Category_2.28.0.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, PCpheno, RDAVIDWebService importsMe: categoryCompare, cellHTS2, eisa, gCMAP, GOstats, PCpheno, phenoTest, ppiStats suggestsMe: BiocCaseStudies, cellHTS, MmPalateMiRNA Package: categoryCompare Version: 1.6.0 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: aacd154c87262be23b26e79763e5491c 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: Bioinformatics, Annotation, GO, MultipleComparisons, 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/categoryCompare_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/categoryCompare_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/categoryCompare_1.6.0.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: cellGrowth Version: 1.6.0 Depends: R (>= 2.12.0), locfit (>= 1.5-4) Imports: lattice License: Artistic-2.0 MD5sum: 30428c9e015c0dbe790c408e1fa348ee 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cellGrowth_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cellGrowth_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cellGrowth_1.6.0.tgz vignettes: vignettes/cellGrowth/inst/doc/cellGrowth-platePlotex.pdf, vignettes/cellGrowth/inst/doc/cellGrowth-plotex.pdf, vignettes/cellGrowth/inst/doc/cellGrowth-welldatex.pdf, vignettes/cellGrowth/inst/doc/cellGrowth.pdf vignetteTitles: cellGrowth-platePlotex.pdf, cellGrowth-plotex.pdf, cellGrowth-welldatex.pdf, Overview of the cellGrowth package. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/cellGrowth/inst/doc/cellGrowth.R Package: cellHTS Version: 1.32.0 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: b1f6c895ed0c4d5012db68277ff61e18 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cellHTS_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cellHTS_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cellHTS_1.32.0.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: 2.26.0 Depends: R (>= 2.10), RColorBrewer, Biobase, methods, genefilter, splots, vsn, hwriter, locfit, grid Imports: prada, GSEABase, Category, stats4 License: Artistic-2.0 MD5sum: 7ad26c35ef99ad04d84ed12d81ac6088 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_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cellHTS2_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cellHTS2_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cellHTS2_2.26.0.tgz vignettes: vignettes/cellHTS2/inst/doc/cellhts2.pdf, vignettes/cellHTS2/inst/doc/cellhts2Complete.pdf, vignettes/cellHTS2/inst/doc/twoChannels.pdf, vignettes/cellHTS2/inst/doc/twoWay.pdf vignetteTitles: Main vignette: End-to-end analysis of cell-based screens, Main vignette (complete version): 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/cellhts2.R, vignettes/cellHTS2/inst/doc/cellhts2Complete.R, vignettes/cellHTS2/inst/doc/twoChannels.R, vignettes/cellHTS2/inst/doc/twoWay.R dependsOnMe: coRNAi, imageHTS, staRank importsMe: HTSanalyzeR, RNAinteract Package: CellNOptR Version: 1.8.0 Depends: R (>= 2.15.0), RBGL, graph, methods, hash, ggplot2, RCurl, Rgraphviz, XML Suggests: RUnit, BiocGenerics, igraph License: GPL-3 Archs: i386, x64 MD5sum: 508490b35cc5323edd10f582b69d52f8 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CellNOptR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CellNOptR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CellNOptR_1.8.0.tgz vignettes: vignettes/CellNOptR/inst/doc/CellNOptR-vignette.pdf, vignettes/CellNOptR/inst/doc/CellNOptR0_1flowchart.pdf, vignettes/CellNOptR/inst/doc/Fig2.pdf, vignettes/CellNOptR/inst/doc/Fig3.pdf, vignettes/CellNOptR/inst/doc/Fig4.pdf, vignettes/CellNOptR/inst/doc/Fig6.pdf, vignettes/CellNOptR/inst/doc/Fig7.pdf, vignettes/CellNOptR/inst/doc/Fig8.pdf vignetteTitles: Main vignette:Playing with networks using CellNOptR, CellNOptR0_1flowchart.pdf, Fig2.pdf, Fig3.pdf, Fig4.pdf, Fig6.pdf, Fig7.pdf, Fig8.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CellNOptR/inst/doc/CellNOptR-vignette.R dependsOnMe: CNORdt, CNORfeeder, CNORfuzzy, CNORode Package: CexoR Version: 1.0.0 Depends: R (>= 2.10.0), IRanges Imports: Rsamtools, GenomicRanges, rtracklayer, idr Suggests: RUnit, BiocGenerics License: Artistic-2.0 | GPL-2 + file LICENSE MD5sum: 0098eb5b8172778d48a20186cd136903 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 Author: Pedro Madrigal Maintainer: Pedro Madrigal source.ver: src/contrib/CexoR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CexoR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CexoR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CexoR_1.0.0.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: 2.4.0 Depends: R (>= 2.10.1), survival Suggests: cluster License: GPL-2 + file LICENSE Archs: i386, x64 MD5sum: e79aa5dbb3d6aa9a11cceba56cb595a3 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, MultipleComparisons, Clustering Author: Samsiddhi Bhattacharjee, Nilanjan Chatterjee, Summer Han and William Wheeler Maintainer: William Wheeler source.ver: src/contrib/CGEN_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CGEN_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CGEN_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CGEN_2.4.0.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: 1.22.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), marray License: GPL MD5sum: db7faf4abdc629090f7bb2e35cb8d080 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, CopyNumberVariants Author: Sjoerd Vosse, Mark van de Wiel Maintainer: Mark van de Wiel source.ver: src/contrib/CGHbase_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CGHbase_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CGHbase_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CGHbase_1.22.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: CGHcall, CGHnormaliter, CGHregions, sigaR importsMe: CGHnormaliter, plrs Package: CGHcall Version: 2.22.0 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: 6c9412fc740312bf360d7975bd5d9be8 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_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CGHcall_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CGHcall_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CGHcall_2.22.0.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 Package: cghMCR Version: 1.20.0 Depends: methods, DNAcopy, CNTools, limma Imports: BiocGenerics (>= 0.1.6), stats4 License: LGPL MD5sum: bec51b25c5cc27a3dfca639437ed242e 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, CopyNumberVariants Author: J. Zhang and B. Feng Maintainer: J. Zhang source.ver: src/contrib/cghMCR_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cghMCR_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cghMCR_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cghMCR_1.20.0.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: 1.16.0 Depends: CGHcall (>= 2.17.0), CGHbase (>= 1.15.0) Imports: Biobase, CGHbase, CGHcall, methods, stats, utils License: GPL (>= 3) MD5sum: c9fe41c5d791c757b74fd378b7c28d88 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CGHnormaliter_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CGHnormaliter_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CGHnormaliter_1.16.0.tgz vignettes: vignettes/CGHnormaliter/inst/doc/CGHnormaliter-method.pdf, vignettes/CGHnormaliter/inst/doc/CGHnormaliter.pdf vignetteTitles: CGHnormaliter-method.pdf, CGHnormaliter hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CGHnormaliter/inst/doc/CGHnormaliter.R Package: CGHregions Version: 1.20.0 Depends: R (>= 2.0.0), methods, Biobase, CGHbase License: GPL (http://www.gnu.org/copyleft/gpl.html) MD5sum: 2a723b2977234d5aadc747e087d2dbb4 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,CopyNumberVariants,Visualization Author: Sjoerd Vosse & Mark van de Wiel Maintainer: Sjoerd Vosse source.ver: src/contrib/CGHregions_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CGHregions_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CGHregions_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CGHregions_1.20.0.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: 1.0.7 Depends: R (>= 3.0.1), minfi, ChAMPdata, Illumina450ProbeVariants.db Imports: sva, IlluminaHumanMethylation450kmanifest, limma, RPMM, DNAcopy, preprocessCore, impute, marray, wateRmelon License: GPL-3 MD5sum: 13bb4725607cdb66e6cd956ee1994f3d 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: Bioinformatics, DNAmethylation, DataImport, IlluminaChip, Preprocessing, QualityControl, Software, DifferentialMethylation, SNP, CopyNumberVariants Author: Tiffany Morris, Lee Butcher, Andy Feber, Andrew Teschendorff, Ankur Chakravarthy and Stephan Beck Maintainer: Tiffany Morris source.ver: src/contrib/ChAMP_1.0.7.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChAMP_1.0.7.zip win64.binary.ver: bin/windows64/contrib/3.0/ChAMP_1.0.7.zip mac.binary.ver: bin/macosx/contrib/3.0/ChAMP_1.0.7.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: 2.8.0 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: 78752f10cf3f961418345d1a2140c566 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, Bioinformatics, DNAMethylation Author: Martin Aryee, Peter Murakami, Harris Jaffee, Rafael Irizarry Maintainer: Peter Murakami source.ver: src/contrib/charm_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/charm_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/charm_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/charm_2.8.0.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: 1.0.1 Depends: R (>= 2.15.1) Imports: BiocGenerics, zlibbioc Suggests: ChemmineR, BiocStyle Enhances: ChemmineR (>= 2.13.0) License: file LICENSE Archs: i386, x64 MD5sum: ae4e10765734a1e55dae63f39de74662 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. Author: Kevin Horan, Thomas Girke Maintainer: Kevin Horan URL: http://manuals.bioinformatics.ucr.edu/home/chemminer source.ver: src/contrib/ChemmineOB_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChemmineOB_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.0/ChemmineOB_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.0/ChemmineOB_1.0.1.tgz vignettes: vignettes/ChemmineOB/inst/doc/ChemmineOB.pdf vignetteTitles: ChemmineOB Vignette hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/ChemmineOB/inst/doc/ChemmineOB.R Package: ChemmineR Version: 2.14.3 Depends: R (>= 2.10.0), methods Imports: graphics, methods, stats, RCurl, DBI, digest, BiocGenerics Suggests: RSQLite, scatterplot3d, gplots, fmcsR,snow, RPostgreSQL, BiocStyle Enhances: ChemmineOB License: Artistic-2.0 Archs: i386, x64 MD5sum: b3f0bcc6a050744cb1615ce780a1e59b 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 source.ver: src/contrib/ChemmineR_2.14.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChemmineR_2.14.3.zip win64.binary.ver: bin/windows64/contrib/3.0/ChemmineR_2.14.3.zip mac.binary.ver: bin/macosx/contrib/3.0/ChemmineR_2.14.3.tgz vignettes: vignettes/ChemmineR/inst/doc/ChemmineR.pdf vignetteTitles: ChemmineR Tutorial hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ChemmineR/inst/doc/ChemmineR.R dependsOnMe: eiR, fmcsR, Rchemcpp suggestsMe: bioassayR, ChemmineOB Package: chimera Version: 1.4.6 Depends: Biobase, GenomicRanges (>= 1.13.3), Rsamtools (>= 1.13.1), methods, org.Hs.eg.db, org.Mm.eg.db, AnnotationDbi, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene Suggests: BSgenome.Mmusculus.UCSC.mm9, TxDb.Mmusculus.UCSC.mm9.knownGene, BiocParallel Enhances: Rsubread License: Artistic-2.0 MD5sum: 7aa91b7bd68e31ad522e057ca00d0b34 NeedsCompilation: no Title: A package for detection and 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. biocViews: Infrastructure Author: Raffaele A Calogero, Matteo Carrara, Marco Beccuti, Francesca Cordero Maintainer: Raffaele A Calogero SystemRequirements: STAR, TopHat, bowtie and samtools are required for some functionalities source.ver: src/contrib/chimera_1.4.6.tar.gz win.binary.ver: bin/windows/contrib/3.0/chimera_1.4.6.zip win64.binary.ver: bin/windows64/contrib/3.0/chimera_1.4.6.zip mac.binary.ver: bin/macosx/contrib/3.0/chimera_1.4.6.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: 1.0.0 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: 8ca365ed263023cdb929d33c42f3254b 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, Bioinformatics, Enrichment, 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/chipenrich_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/chipenrich_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/chipenrich_1.0.0.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: 2.10.0 Depends: R (>= 2.10), grid,VennDiagram, BiocGenerics (>= 0.1.0), biomaRt, multtest, IRanges, Biostrings, BSgenome, BSgenome.Ecoli.NCBI.20080805, GO.db, org.Hs.eg.db, limma, GenomicFeatures Imports: gplots, BiocGenerics, biomaRt, multtest, IRanges, Biostrings, BSgenome, GO.db, limma, AnnotationDbi, GenomicFeatures Suggests: reactome.db, RUnit, BiocGenerics License: GPL (>= 2) MD5sum: 8baba85d080b26b380d5d4bc0f3c0871 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, Simon Lin, David Lapointe and Michael Green Maintainer: Lihua Julie Zhu source.ver: src/contrib/ChIPpeakAnno_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChIPpeakAnno_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ChIPpeakAnno_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ChIPpeakAnno_2.10.0.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: chipseq Version: 1.12.0 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, BSgenome.Mmusculus.UCSC.mm9, TxDb.Mmusculus.UCSC.mm9.knownGene License: Artistic-2.0 Archs: i386, x64 MD5sum: 555fa98560c3611b84a4559c5107e0d7 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/chipseq_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/chipseq_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/chipseq_1.12.0.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: HTSeqGenie suggestsMe: ggbio, oneChannelGUI Package: ChIPseqR Version: 1.16.0 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: fdabf6c63c70aae4ed062dbe85557a05 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, Bioinformatics, Infrastructure Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPseqR_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChIPseqR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ChIPseqR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ChIPseqR_1.16.0.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: 1.16.0 Depends: Biostrings (>= 2.29.2) Imports: IRanges, XVector, Biostrings, ShortRead, graphics, methods, stats, utils Suggests: actuar, zoo License: GPL (>= 2) MD5sum: 6abb58243c097c0a9108f50fff0271d1 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, Bioinformatics, ChIPseq Author: Peter Humburg Maintainer: Peter Humburg source.ver: src/contrib/ChIPsim_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChIPsim_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ChIPsim_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ChIPsim_1.16.0.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: 1.4.0 Depends: R (>= 2.10), ChIPXpressData Imports: Biobase, GEOquery, frma, affy, bigmemory, biganalytics Suggests: mouse4302frmavecs, mouse4302.db, mouse4302cdf, RUnit, BiocGenerics License: GPL(>=2) MD5sum: 973fa5a2a670f8d890b09f235080eb81 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, Bioinformatics Author: George Wu Maintainer: George Wu source.ver: src/contrib/ChIPXpress_1.4.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/ChIPXpress_1.4.0.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: 1.26.1 Depends: R(>= 2.10.0), survival, methods Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: ff674f03ccb9cee326d5a01200f48955 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_1.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/chopsticks_1.26.1.zip win64.binary.ver: bin/windows64/contrib/3.0/chopsticks_1.26.1.zip mac.binary.ver: bin/macosx/contrib/3.0/chopsticks_1.26.1.tgz vignettes: vignettes/chopsticks/inst/doc/chopsticks-vignette.pdf, vignettes/chopsticks/inst/doc/practical3_snpStatsBug-diff.pdf, vignettes/chopsticks/inst/doc/practical6_snpStatsBug-diff.pdf, vignettes/chopsticks/inst/doc/practical7_snpStatsBug-diff.pdf, vignettes/chopsticks/inst/doc/snpMatrix-4d.pdf, vignettes/chopsticks/inst/doc/snpMatrix-paper-HumanHeridity2007.pdf, vignettes/chopsticks/inst/doc/snpStatsBug_1.3.6_-vignette.pdf, vignettes/chopsticks/inst/doc/snpStatsBug_1.5.4_-vignette.pdf, vignettes/chopsticks/inst/doc/snpStatsBug-vignette.pdf vignetteTitles: snpMatrix, practical3_snpStatsBug-diff.pdf, practical6_snpStatsBug-diff.pdf, practical7_snpStatsBug-diff.pdf, snpMatrix-4d.pdf, snpMatrix-paper-HumanHeridity2007.pdf, snpStatsBug_1.3.6_-vignette.pdf, snpStatsBug_1.5.4_-vignette.pdf, snpStatsBug-vignette.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/chopsticks/inst/doc/chopsticks-vignette.R Package: chroGPS Version: 1.6.1 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: a49b607af94081620aa987fc73c0814f 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_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/chroGPS_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.0/chroGPS_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.0/chroGPS_1.6.1.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: 1.16.0 Depends: R (>= 2.9.0), BiocGenerics (>= 0.3.2), annotate (>= 1.20.0), AnnotationDbi (>= 1.4.0), hgu95av2.db Imports: BiocGenerics, annotate, AnnotationDbi, Biobase (>= 2.17.8), graphics, grDevices, methods, stats, IRanges, rtracklayer Suggests: ALL License: Artistic-2.0 MD5sum: 5de46936661b80a0cc9a0966ea9a8e57 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ChromHeatMap_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ChromHeatMap_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ChromHeatMap_1.16.0.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: 1.2.7 Depends: R (>= 2.10.0) Imports: methods, utils License: GPL (>= 3) Archs: i386, x64 MD5sum: c5f376b7598b524d2421c43f00811ee9 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_1.2.7.tar.gz win.binary.ver: bin/windows/contrib/3.0/cisPath_1.2.7.zip win64.binary.ver: bin/windows64/contrib/3.0/cisPath_1.2.7.zip mac.binary.ver: bin/macosx/contrib/3.0/cisPath_1.2.7.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: 1.0.2 Depends: R (>= 2.15), BiocGenerics (>= 0.1.0), BSgenome, BSgenome.Drerio.UCSC.danRer7, GenomicRanges, seqinr, e1071 License: GPL-2 MD5sum: 96f649174affe0e727fb3af39a83396a 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: HighThroughputSequencing, 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_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/cleanUpdTSeq_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.0/cleanUpdTSeq_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.0/cleanUpdTSeq_1.0.2.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: 1.0.0 Depends: R (>= 3.0.0), methods, Biostrings (>= 1.29.8) Imports: IRanges Suggests: testthat, knitr, BiocStyle (>= 0.0.14), BRAIN, UniProt.ws (>= 2.1.4) License: GPL (>= 3) MD5sum: 41fb4100ac18d39ad0db45c457386606 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: Bioinformatics, Proteomics Author: Sebastian Gibb [aut, cre] Maintainer: Sebastian Gibb URL: https://github.com/sgibb/cleaver/ VignetteBuilder: knitr source.ver: src/contrib/cleaver_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cleaver_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cleaver_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cleaver_1.0.0.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 Package: clippda Version: 1.12.0 Depends: R (>= 2.13.1),limma, statmod, rgl, lattice, scatterplot3d, graphics, grDevices, stats, utils, Biobase, tools, methods License: GPL (>=2) MD5sum: 2bc9528bb89635450cbf894306cfe32b 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, DataPreprocessing,Bioinformatics,DifferentialExpression, MultipleComparisons, SampleSize Author: Stephen Nyangoma Maintainer: Stephen Nyangoma URL: http://www.cancerstudies.bham.ac.uk/crctu/CLIPPDA.shtml source.ver: src/contrib/clippda_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/clippda_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/clippda_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/clippda_1.12.0.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: 1.2.3 Depends: R (>= 2.15.0), Matrix, graph Imports: methods, Biobase, igraph, gRbase (>= 1.6.6), qpgraph, KEGGgraph, corpcor, RBGL, Rcpp Suggests: RUnit, BiocGenerics, RCytoscape (>= 1.6.3), graphite, ALL, hgu95av2.db License: AGPL-3 MD5sum: 04c955b826bcc08ceeb556420b86ecf8 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_1.2.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/clipper_1.2.3.zip win64.binary.ver: bin/windows64/contrib/3.0/clipper_1.2.3.zip mac.binary.ver: bin/macosx/contrib/3.0/clipper_1.2.3.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: Clonality Version: 1.10.1 Depends: R (>= 2.12.2), DNAcopy Imports: DNAcopy, grDevices, graphics, stats, utils Suggests: gdata, DNAcopy License: GPL-3 MD5sum: 3a87b568eeffb37a698bafe67e377b14 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, CopyNumberVariants, Classification, aCGH Author: Irina Ostrovnaya Maintainer: Irina Ostrovnaya source.ver: src/contrib/Clonality_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Clonality_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Clonality_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Clonality_1.10.1.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: 1.0.0 Depends: methods Suggests: BiocGenerics, edgeR, knitr, pvclust, RUnit, vegan License: file LICENSE MD5sum: 7dcd2b06b6c92bdc4a3be931478af9b9 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: Bioinformatics, HighThroughputSequencing Author: Charles Plessy Maintainer: Charles Plessy VignetteBuilder: knitr source.ver: src/contrib/clonotypeR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/clonotypeR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/clonotypeR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/clonotypeR_1.0.0.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: 1.10.0 Depends: R (>= 2.10) Imports: ROC, lattice Suggests: RUnit License: GPL-3 MD5sum: a1b78450091da6671c8c5f7db641c9db 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/clst_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/clst_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/clst_1.10.0.tgz vignettes: vignettes/clst/inst/doc/clstDemo.pdf, vignettes/clst/inst/doc/matchtypes.pdf vignetteTitles: clst, matchtypes.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clst/inst/doc/clstDemo.R dependsOnMe: clstutils Package: clstutils Version: 1.10.0 Depends: R (>= 2.10), clst, rjson, ape Imports: lattice, RSQLite Suggests: RUnit, RSVGTipsDevice License: GPL-3 MD5sum: d0a2ba1f8aa5bb774b6523deb2d0369c NeedsCompilation: no Title: Tools for performing taxonomic assignment. Description: Tools for performing taxonomic assignment based on phylogeny using pplacer and clst. biocViews: HighThroughputSequencing, Classification, Visualization, QualityControl Author: Noah Hoffman Maintainer: Noah Hoffman source.ver: src/contrib/clstutils_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/clstutils_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/clstutils_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/clstutils_1.10.0.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: 1.10.1 Depends: R (>= 2.10), ggplot2 Imports: methods, stats4, DBI, plyr, AnnotationDbi, GO.db, KEGG.db, org.Hs.eg.db, DOSE, GOSemSim Suggests: ReactomePA, pathview, knitr License: Artistic-2.0 MD5sum: 76ef4a98e839764218f08612d80e593d 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, MultipleComparisons, 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_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/clusterProfiler_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.0/clusterProfiler_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.0/clusterProfiler_1.10.1.tgz vignettes: vignettes/clusterProfiler/inst/doc/clusterProfiler_for_unsupported_organisms.pdf, vignettes/clusterProfiler/inst/doc/clusterProfiler.pdf vignetteTitles: clusterProfiler_for_unsupported_organisms.pdf, An introduction to clusterProfiler hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/clusterProfiler/inst/doc/clusterProfiler.R suggestsMe: DOSE, GOSemSim, ReactomePA Package: clusterStab Version: 1.34.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), methods Suggests: fibroEset, genefilter License: Artistic-2.0 MD5sum: 4dda7be197c0e3dc1a78fae13c4368e2 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/clusterStab_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/clusterStab_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/clusterStab_1.34.0.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: 1.20.0 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: 65c2c6c6ecb3a08a2e0b14c57deb0f8c 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CMA_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CMA_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CMA_1.20.0.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: cn.farms Version: 1.10.0 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: ad4fb8599aaaf00316603e746468ba26 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, Bioinformatics, CopyNumberVariants 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cn.farms_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cn.farms_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cn.farms_1.10.0.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: 1.8.9 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: 5cb324a2acbcd12ed0e1b5f4aec6adb4 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: HighThroughputSequencing, Sequencing, Bioinformatics, CopyNumberVariants, Homo_sapiens, CellBiology, HighTroughputSequencingData, HapMap, Genetics Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/cnmops/cnmops.html source.ver: src/contrib/cn.mops_1.8.9.tar.gz win.binary.ver: bin/windows/contrib/3.0/cn.mops_1.8.9.zip win64.binary.ver: bin/windows64/contrib/3.0/cn.mops_1.8.9.zip mac.binary.ver: bin/macosx/contrib/3.0/cn.mops_1.8.9.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: CNAnorm Version: 1.8.0 Depends: R (>= 2.10.1), DNAcopy, methods Imports: methods License: GPL-2 Archs: i386, x64 MD5sum: c91fcf88465bc816ca858da04482d340 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: Bioinformatics, HighThroughputSequencing, CopyNumberVariants, 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNAnorm_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNAnorm_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNAnorm_1.8.0.tgz vignettes: vignettes/CNAnorm/inst/doc/CNAnorm.pdf vignetteTitles: CNAnorm.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: CNORdt Version: 1.4.0 Depends: R (>= 1.8.0), CellNOptR (>= 0.99), abind License: GPL-2 Archs: i386, x64 MD5sum: 0929f5a9eb68e0327d2fe021240ee1ce 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, Bioinformatics, TimeCourse Author: A. MacNamara Maintainer: A. MacNamara source.ver: src/contrib/CNORdt_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNORdt_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNORdt_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNORdt_1.4.0.tgz vignettes: vignettes/CNORdt/inst/doc/CNORdt-vignette-plot.pdf, vignettes/CNORdt/inst/doc/CNORdt-vignette.pdf vignetteTitles: CNORdt-vignette-plot.pdf, 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: 1.2.0 Depends: R (>= 2.15.0), CellNOptR (>= 1.4.0), graph Suggests: minet, catnet, igraph, Rgraphviz, RUnit, BiocGenerics License: GPL-3 MD5sum: 89761a6c5207dff4957737798bc2080a 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, Bioinformatics, NetworkInference Author: F.Eduati Maintainer: F.Eduati source.ver: src/contrib/CNORfeeder_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNORfeeder_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNORfeeder_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNORfeeder_1.2.0.tgz vignettes: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.pdf, vignettes/CNORfeeder/inst/doc/DDN.pdf, vignettes/CNORfeeder/inst/doc/integratedModel.pdf, vignettes/CNORfeeder/inst/doc/optModel.pdf, vignettes/CNORfeeder/inst/doc/SimResultsT1_1.pdf vignetteTitles: Main vignette:Playing with networks using CNORfeeder, DDN.pdf, integratedModel.pdf, optModel.pdf, SimResultsT1_1.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfeeder/inst/doc/CNORfeeder-vignette.R Package: CNORfuzzy Version: 1.4.0 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: 77ab1a715b47182e554eb1a2159fd6d3 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). Author: M. Morris, T. Cokelaer Maintainer: T. Cokelaer source.ver: src/contrib/CNORfuzzy_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNORfuzzy_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNORfuzzy_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNORfuzzy_1.4.0.tgz vignettes: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis2.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette-FullAnalysis3.pdf, vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.pdf, vignettes/CNORfuzzy/inst/doc/tf1.pdf, vignettes/CNORfuzzy/inst/doc/tf2.pdf vignetteTitles: CNORfuzzy-vignette-FullAnalysis.pdf, CNORfuzzy-vignette-FullAnalysis2.pdf, CNORfuzzy-vignette-FullAnalysis3.pdf, Main vignette:Playing with networks using CNORfuzzyl, tf1.pdf, tf2.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORfuzzy/inst/doc/CNORfuzzy-vignette.R Package: CNORode Version: 1.4.0 Depends: CellNOptR (>= 1.5.14), genalg Enhances: MEIGOR License: GPL-3 Archs: i386, x64 MD5sum: d884581d611336598540af01b30706a9 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNORode_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNORode_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNORode_1.4.0.tgz vignettes: vignettes/CNORode/inst/doc/CNORode-vignette.pdf, vignettes/CNORode/inst/doc/data_ToyModelMMB_FeddbackAnd.pdf vignetteTitles: Main vignette:Playing with networks using CNORode, data_ToyModelMMB_FeddbackAnd.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CNORode/inst/doc/CNORode-vignette.R Package: CNTools Version: 1.18.0 Depends: R (>= 2.10), methods, tools, stats, genefilter License: LGPL Archs: i386, x64 MD5sum: d15fef70967aae074993bde5a3de4383 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, CopyNumberVariants Author: Jianhua Zhang Maintainer: J. Zhang source.ver: src/contrib/CNTools_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNTools_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNTools_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNTools_1.18.0.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: 1.6.0 Depends: methods, brglm Suggests: cnvGSAdata, org.Hs.eg.db License: LGPL MD5sum: 83834613634d54328f445a8e193559cd 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: MultipleComparisons Author: Daniele Merico ; packaged by Robert Ziman Maintainer: Robert Ziman source.ver: src/contrib/cnvGSA_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cnvGSA_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cnvGSA_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cnvGSA_1.6.0.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: 1.0.0 Depends: R (>= 3.0.0), DNAcopy, methods, Rsamtools, VariantAnnotation, parallel, rjags, ggplot2 Imports: IRanges Suggests: knitr License: GPL-2 MD5sum: 0e0c296a4b414c5783a9bd0103c2c84e 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNVrd2_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNVrd2_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNVrd2_1.0.0.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: 1.56.0 Depends: R (>= 2.10), survival License: GPL-3 Archs: i386, x64 MD5sum: 732a431e8bd9419bc694f6e4d41c533c 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_1.56.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CNVtools_1.56.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CNVtools_1.56.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CNVtools_1.56.0.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: 1.0.0 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: 68088fb9c5a284e612d419d19d3ffb14 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, MultipleComparisons, SequenceMatching Author: Manuela Benary, Stefan Kroeger, Yuehien Lee, Robert Lehmann Maintainer: Manuela Benary source.ver: src/contrib/cobindR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cobindR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cobindR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cobindR_1.0.0.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: 1.34.0 Depends: R (>= 2.0), org.Hs.eg.db Imports: AnnotationDbi License: CPL MD5sum: 212c38cd6c1a5c14b3dbc5168fe3f5b8 NeedsCompilation: no Title: Different test statistics based on co-citation. Description: A collection of software tools for dealing with co-citation data. biocViews: Bioinformatics Author: B. Ding and R. Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/CoCiteStats_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CoCiteStats_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CoCiteStats_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CoCiteStats_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: codelink Version: 1.30.9 Depends: R (>= 2.10), BiocGenerics (>= 0.3.2), methods, Biobase (>= 2.17.8), limma Imports: annotate Suggests: genefilter, parallel, knitr License: GPL-2 MD5sum: ac65661aeba7acb21783b93ef6ed76c6 NeedsCompilation: no Title: Manipulation of Codelink Bioarrays data. Description: This packages allow reading into R Codelink bioarray data exported as text from the Codelink software. Also includes functions to facilitate manipulation and pre-processing of data, such as in background correction and normalization. biocViews: Microarray, OneChannel, DataImport, Preprocessing Author: Diego Diez Maintainer: Diego Diez VignetteBuilder: knitr source.ver: src/contrib/codelink_1.30.9.tar.gz win.binary.ver: bin/windows/contrib/3.0/codelink_1.30.9.zip win64.binary.ver: bin/windows64/contrib/3.0/codelink_1.30.9.zip mac.binary.ver: bin/macosx/contrib/3.0/codelink_1.30.9.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, vignettes/codelink/inst/doc/codelink.R, vignettes/codelink/inst/doc/CodelinkSet.R Package: CoGAPS Version: 1.12.0 Depends: R (>= 2.9.0), R.utils (>= 1.2.4), gplots (>= 2.8.0) Imports: graphics, grDevices, methods, stats, utils License: GPL (== 2) MD5sum: 82a33a2cb5d4d9f28e9639152e3eeca4 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, Bioinformatics 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_1.12.0.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: 1.6.0 Depends: R (>= 2.13.0) Imports: graphics, grDevices Suggests: limma License: GPL-2 MD5sum: 3dec24a021dfb440a6f299b486afcfaf 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, Bioinformatics, DifferentialExpression Author: Yingying Wei, Michael Ochs Maintainer: Yingying Wei source.ver: src/contrib/coGPS_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/coGPS_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/coGPS_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/coGPS_1.6.0.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: ConsensusClusterPlus Version: 1.16.0 Imports: Biobase, ALL, graphics, stats, utils, cluster License: GPL version 2 MD5sum: b955760b0f298eefe5f509acd147b019 NeedsCompilation: no Title: ConsensusClusterPlus Description: algorithm for determining cluster count and membership by stability evidence in unsupervised analysis biocViews: Software, Bioinformatics, Clustering Author: Matt Wilkerson , Peter Waltman Maintainer: Matt Wilkerson source.ver: src/contrib/ConsensusClusterPlus_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ConsensusClusterPlus_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ConsensusClusterPlus_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ConsensusClusterPlus_1.16.0.tgz vignettes: vignettes/ConsensusClusterPlus/inst/doc/ConsensusClusterPlus.pdf vignetteTitles: ConsensusClusterPlus Tutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Package: convert Version: 1.38.0 Depends: R (>= 2.6.0), Biobase (>= 1.15.33), limma (>= 1.7.0), marray, utils, methods License: LGPL MD5sum: 3e067e1a4ebca369debbb6a7c89f6992 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/convert_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/convert_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/convert_1.38.0.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: 1.30.0 Depends: Biobase, methods Suggests: colonCA License: Artistic-2.0 Archs: i386, x64 MD5sum: 226d17130300b8a1cbc10c175811726e 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/copa_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/copa_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/copa_1.30.0.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: copynumber Version: 1.2.0 Depends: R (>= 2.10), BiocGenerics Imports: GenomicRanges, IRanges License: Artistic-2.0 MD5sum: 541acc4f0268cb375965e66a4275c5c8 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, CopyNumberVariants, Genetics, Visualization, Bioinformatics Author: Gro Nilsen, Knut Liestoel and Ole Christian Lingjaerde. Maintainer: Gro Nilsen source.ver: src/contrib/copynumber_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/copynumber_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/copynumber_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/copynumber_1.2.0.tgz vignettes: vignettes/copynumber/inst/doc/copynumber.pdf, vignettes/copynumber/inst/doc/overview.pdf vignetteTitles: copynumber.pdf, overview.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/copynumber/inst/doc/copynumber.R Package: Cormotif Version: 1.8.0 Depends: R (>= 2.12.0), affy, limma Imports: affy, graphics, grDevices License: GPL-2 MD5sum: fdbb0e9717f1b3c7de86e1eedeee7384 NeedsCompilation: no Title: Correlation Motif Fit Description: It fits correlation motif model to multiple studies to detect study specific differential expression patterns. biocViews: Microarray, Bioinformatics, DifferentialExpression Author: Hongkai Ji, Yingying Wei Maintainer: Yingying Wei source.ver: src/contrib/Cormotif_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Cormotif_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Cormotif_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Cormotif_1.8.0.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: 1.4.0 Depends: methods, Biostrings, seqinr,igraph License: GPL-2 MD5sum: 43d154ef278df5a7d4d6448ba20b8955 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. Two methods are provided for detecting correlated mutations ,including conditional selection pressure and mutual information. 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: Bioinformatics, Sequencing Author: Zhenpeng Li, Yang Huang, Yabo Ouyang, Yiming Shao, Liying Ma Maintainer: Zhenpeng Li source.ver: src/contrib/CorMut_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CorMut_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CorMut_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CorMut_1.4.0.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: 1.12.0 Depends: R (>= 2.10), cellHTS2, limma, locfit Imports: MASS, gplots, lattice, grDevices, graphics, stats License: Artistic-2.0 MD5sum: 32a41ddc00523ecd212bed4f271df7b1 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/coRNAi_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/coRNAi_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/coRNAi_1.12.0.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: 1.28.0 Imports: e1071, stats Suggests: cluster, MASS License: GPL (>= 2) MD5sum: e27f214cf08dadbd76da7f5eeb65837b NeedsCompilation: no Title: Multivariate Correlation Estimator and Statistical Inference Procedures. Description: Multivariate correlation estimation and statistical inference. See package vignette. biocViews: Bioinformatics, Microarray, Clustering, GraphsAndNetworks Author: Dongxiao Zhu and Youjuan Li Maintainer: Dongxiao Zhu source.ver: src/contrib/CORREP_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CORREP_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CORREP_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CORREP_1.28.0.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: cqn Version: 1.8.0 Depends: R (>= 2.10.0), mclust, nor1mix, stats, preprocessCore, splines, quantreg Imports: splines Suggests: scales, edgeR License: Artistic-2.0 MD5sum: 100f87bd3f7ec4280ea0d6f22a5b90c3 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cqn_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cqn_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cqn_1.8.0.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: 1.10.0 Depends: EBImage, DNAcopy, aCGH Imports: MASS, e1071, foreach, sgeostat License: Artistic-2.0 MD5sum: 3d591dc4784979d768b73c1f32df2c84 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CRImage_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CRImage_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CRImage_1.10.0.tgz vignettes: vignettes/CRImage/inst/doc/cellularity2.pdf, vignettes/CRImage/inst/doc/CRImage.pdf, vignettes/CRImage/inst/doc/labeledImage.pdf, vignettes/CRImage/inst/doc/segmentedImage.pdf, vignettes/CRImage/inst/doc/segmentedImageRaw.pdf vignetteTitles: cellularity2.pdf, CRImage Manual, labeledImage.pdf, segmentedImage.pdf, segmentedImageRaw.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/CRImage/inst/doc/CRImage.R Package: crlmm Version: 1.20.4 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, ellipse, RUnit, VGAM License: Artistic-2.0 Archs: i386, x64 MD5sum: 825ce80a2212d86788acc1867fdcde82 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, Bioinformatics,CopyNumberVariants 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_1.20.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/crlmm_1.20.4.zip win64.binary.ver: bin/windows64/contrib/3.0/crlmm_1.20.4.zip mac.binary.ver: bin/macosx/contrib/3.0/crlmm_1.20.4.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: 1.14.0 Depends: R (>= 2.15.0), IRanges, GenomicRanges Imports: stats, utils Suggests: ShortRead, Biostrings License: Artistic-2.0 Archs: i386, x64 MD5sum: d912c1005a8deffb75900fcbde8962b7 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/CSAR_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/CSAR_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/CSAR_1.14.0.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: 1.1.2 Imports: methods, splines, stats, utils Suggests: testthat License: GPL-2 Archs: i386, x64 MD5sum: 80b3701201e9dbac019a6a6bc6e2230a 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_1.1.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/CSSP_1.1.2.zip win64.binary.ver: bin/windows64/contrib/3.0/CSSP_1.1.2.zip mac.binary.ver: bin/macosx/contrib/3.0/CSSP_1.1.2.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: 1.36.0 Depends: amap License: GPL-2 MD5sum: b73c504189fb04abe916b2365a2c1873 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ctc_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ctc_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ctc_1.36.0.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: 2.4.1 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: ac4f657b10d5717f67e7c852df9862f9 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: HighThroughputSequencing, HighThroughputSequencingData, RNAseq, RNAseqData, GeneExpression, DifferentialExpression, Infrastructure, DataImport, DataRepresentation, Visualization, Bioinformatics, Clustering, MultipleComparisons, QualityControl Author: L. Goff, C. Trapnell, D. Kelley Maintainer: Loyal A. Goff source.ver: src/contrib/cummeRbund_2.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/cummeRbund_2.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/cummeRbund_2.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/cummeRbund_2.4.1.tgz vignettes: vignettes/cummeRbund/inst/doc/cuffData_schema.pdf, vignettes/cummeRbund/inst/doc/cummeRbund-example-workflow.pdf, vignettes/cummeRbund/inst/doc/cummeRbund-manual.pdf, vignettes/cummeRbund/inst/doc/ENCODE_SCV.pdf vignetteTitles: cuffData_schema.pdf, Sample cummeRbund workflow, CummeRbund User Guide, ENCODE_SCV.pdf 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: spliceR suggestsMe: oneChannelGUI Package: customProDB Version: 1.2.0 Depends: R (>= 3.0.1), IRanges, AnnotationDbi, biomaRt Imports: Rsamtools (>= 1.10.2), Biostrings (>= 2.26.3), IRanges, GenomicRanges (>= 1.13.18), 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: 918bbc81c3d2381d2dfc72fd510b095f 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 Author: xiaojing wang Maintainer: xiaojing wang source.ver: src/contrib/customProDB_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/customProDB_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/customProDB_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/customProDB_1.2.0.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: 1.16.0 Depends: R (>= 2.10.0), Mfuzz Imports: Biobase, stats License: GPL-2 MD5sum: 3dd200cb79f6b1c909ed92aaf219bc77 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, Bioinformatics,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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/cycle_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/cycle_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/cycle_1.16.0.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: 1.0.0 Depends: R (>= 3.0.1), methods, biomaRt, grImport, grid, motifStack Imports: XML, UniProt.ws, pheatmap, Biostrings Suggests: RUnit, BiocGenerics, BiocStyle License: GPL (>=2) MD5sum: 9d6a1904551b9c2527282c5b2a8d66aa 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, Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/dagLogo_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/dagLogo_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/dagLogo_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/dagLogo_1.0.0.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: 1.34.0 Imports: MASS, stats License: GPL (>= 2) MD5sum: e71aa26e78127b93137eb04937267ae3 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, Bioinformatics, DifferentialExpression Author: Jobst Landgrebe and Frank Bretz Maintainer: Jobst Landgrebe URL: http://www.microarrays.med.uni-goettingen.de source.ver: src/contrib/daMA_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/daMA_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/daMA_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/daMA_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: DART Version: 1.8.0 Depends: R (>= 2.10.0), igraph (>= 0.6.0) Suggests: breastCancerVDX, breastCancerMAINZ, Biobase License: GPL-2 MD5sum: ac86758fc4506466abb18ecd1969ef71 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, GraphsAndNetworks, Pathways, Bioinformatics Author: Yan Jiao, Katherine Lawler, Andrew E Teschendorff Maintainer: Katherine Lawler source.ver: src/contrib/DART_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DART_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DART_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DART_1.8.0.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: 1.2.0 Depends: IRanges, GenomicRanges, XML, Biostrings License: LGPL (>= 3) MD5sum: 5b37f574424d8358279bb87fd74dd063 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DASiR_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DASiR_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DASiR_1.2.0.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: 1.22.0 Depends: RCurl (>= 1.4.0), utils License: GPL-2 MD5sum: 937915bdc9a6cad5c7118f4e9ba3bdcd 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DAVIDQuery_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DAVIDQuery_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DAVIDQuery_1.22.0.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: 1.6.0 Depends: R (>= 2.15.0), edgeR, DESeq Suggests: ShortRead, BiocGenerics License: GPL (>= 2) MD5sum: 77be3349469e0898b4a5deaf28eb0b39 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, Bioinformatics Author: Kun Liang Maintainer: Kun Liang source.ver: src/contrib/DBChIP_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DBChIP_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DBChIP_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DBChIP_1.6.0.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: 1.16.0 Depends: R (>= 2.3.0), Biobase (>= 1.10.0), RColorBrewer (>= 0.1-3), xtable, lattice, methods Suggests: RUnit License: LGPL-3 MD5sum: b9231666f419936b8e2ffde07b5c0baf 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ddCt_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ddCt_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ddCt_1.16.0.tgz vignettes: vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.pdf, vignettes/ddCt/inst/doc/rtPCR-usage.pdf, vignettes/ddCt/inst/doc/rtPCR.pdf vignetteTitles: How to apply the ddCt method, Analyse RT-PCR data with the end-to-end script in ddCt package, Introduction to the ddCt method for qRT-PCR data analysis: background,, algorithm and example hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddCt/inst/doc/RT-PCR-Script-ddCt.R, vignettes/ddCt/inst/doc/rtPCR-usage.R, vignettes/ddCt/inst/doc/rtPCR.R Package: ddgraph Version: 1.6.3 Depends: graph, methods, Rcpp Imports: bnlearn (>= 2.8), gtools, pcalg, RColorBrewer, plotrix, MASS, Rcpp LinkingTo: Rcpp Suggests: testthat, Rgraphviz, e1071, ROCR, testthat License: GPL-3 Archs: i386, x64 MD5sum: e7b1821e0a798498a06a7556f7438cad 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: Bioinformatics, GraphsAndNetworks Author: Robert Stojnic Maintainer: Robert Stojnic source.ver: src/contrib/ddgraph_1.6.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/ddgraph_1.6.3.zip win64.binary.ver: bin/windows64/contrib/3.0/ddgraph_1.6.3.zip mac.binary.ver: bin/macosx/contrib/3.0/ddgraph_1.6.3.tgz vignettes: vignettes/ddgraph/inst/doc/ddgraph-cluster.pdf, vignettes/ddgraph/inst/doc/ddgraph-ddgraph-plot.pdf, vignettes/ddgraph/inst/doc/ddgraph.pdf vignetteTitles: ddgraph-cluster.pdf, ddgraph-ddgraph-plot.pdf, Overview of the 'ddgraph' package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ddgraph/inst/doc/ddgraph.R Package: DECIPHER Version: 1.8.0 Depends: R (>= 2.13.0), Biostrings (>= 2.29), RSQLite (>= 0.9), IRanges, stats, XVector, parallel Imports: Biostrings, parallel, RSQLite, IRanges, stats, XVector LinkingTo: Biostrings, parallel, RSQLite, IRanges, stats, XVector License: GPL-3 Archs: i386, x64 MD5sum: 604b267ba1e6bf824494c835c5a5dee0 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DECIPHER_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DECIPHER_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DECIPHER_1.8.0.tgz vignettes: 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: 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/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: 1.4.0 Depends: R (>= 2.14.0), limSolve, pcaMethods, ggplot2, grid License: GPL-2 MD5sum: 74f14d47e23ef44071cc1be1a6756537 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: Bioinformatics, ExperimentData, RNAExpressionData Author: Ting Gong Joseph D. Szustakowski Maintainer: Ting Gong source.ver: src/contrib/DeconRNASeq_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DeconRNASeq_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DeconRNASeq_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DeconRNASeq_1.4.0.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: 1.36.0 Depends: R (>= 1.7.0) License: LGPL Archs: i386, x64 MD5sum: 2baf682100dc2483ff1cecd8deaed780 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: Bioinformatics, Microarray, DifferentialExpression Author: Yuanyuan Xiao , Jean Yee Hwa Yang . Maintainer: Yuanyuan Xiao source.ver: src/contrib/DEDS_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DEDS_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DEDS_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DEDS_1.36.0.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: 1.8.0 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: f515c296225a228321b37d1ec7b507e4 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/deepSNV_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/deepSNV_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/deepSNV_1.8.0.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: h5vc Package: DEGraph Version: 1.14.0 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: 356d3c6ae6219d2193aeafadab011e8f 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, GraphsAndNetworks, NetworkAnalysis, NetworkEnrichment Author: Laurent Jacob, Pierre Neuvial and Sandrine Dudoit Maintainer: Laurent Jacob source.ver: src/contrib/DEGraph_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DEGraph_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DEGraph_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DEGraph_1.14.0.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: 1.16.0 Depends: R (>= 2.8.0), qvalue, samr, methods Imports: graphics, grDevices, methods, stats, utils License: LGPL (>=2) Archs: i386, x64 MD5sum: 4f5e34e31b1a95725dcff4a3a4c24021 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DEGseq_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DEGseq_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DEGseq_1.16.0.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: 1.2.0 Depends: R (>= 2.15.1), methods, ggplot2, changepoint, wavethresh, tseries, pvclust, fBasics, grid, reshape, scales Suggests: knitr License: GPL-2 MD5sum: 325b22060d3931ff054480119db6df86 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/deltaGseg_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/deltaGseg_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/deltaGseg_1.2.0.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: 1.14.0 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: 6df447df70a5c2e1fac6c98540f6b249 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: HighThroughputSequencing, 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DESeq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DESeq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DESeq_1.14.0.tgz vignettes: vignettes/DESeq/inst/doc/DESeq.pdf, vignettes/DESeq/inst/doc/vst.pdf vignetteTitles: Analysing RNA-Seq data with the "DESeq" package, vst.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq/inst/doc/DESeq.R dependsOnMe: DBChIP, easyRNASeq, SeqGSEA, TCC, tRanslatome importsMe: ampliQueso, ArrayExpressHTS, EDASeq, HTSFilter, rnaSeqMap suggestsMe: BitSeq, dexus, DiffBind, EDASeq, gage, gCMAP, genefilter, GenomicRanges, oneChannelGUI, SSPA Package: DESeq2 Version: 1.2.10 Depends: GenomicRanges, IRanges, Rcpp (>= 0.10.1), RcppArmadillo (>= 0.3.4.4) Imports: BiocGenerics (>= 0.7.5), methods, locfit, genefilter, RColorBrewer, lattice LinkingTo: Rcpp, RcppArmadillo Suggests: RUnit, Biobase, parathyroidSE, pasilla (>= 0.2.10), vsn, gplots, BiocStyle License: GPL (>= 3) Archs: i386, x64 MD5sum: 04766ede1ed40148818a1056bf34c812 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: HighThroughputSequencing, ChIPseq, RNAseq, SAGE, DifferentialExpression Author: Michael Love (MPIMG Berlin), Simon Anders, Wolfgang Huber (EMBL Heidelberg) Maintainer: Michael Love source.ver: src/contrib/DESeq2_1.2.10.tar.gz win.binary.ver: bin/windows/contrib/3.0/DESeq2_1.2.10.zip win64.binary.ver: bin/windows64/contrib/3.0/DESeq2_1.2.10.zip mac.binary.ver: bin/macosx/contrib/3.0/DESeq2_1.2.10.tgz vignettes: vignettes/DESeq2/inst/doc/DESeq2.pdf, vignettes/DESeq2/inst/doc/vst.pdf vignetteTitles: Analyzing RNA-Seq data with the "DESeq2" package, vst.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DESeq2/inst/doc/DESeq2.R importsMe: HTSFilter, ReportingTools suggestsMe: BiocGenerics, DiffBind, gage Package: DEXSeq Version: 1.8.0 Depends: Biobase (>= 2.13.11) Imports: BiocGenerics (>= 0.7.5), biomaRt, hwriter, methods, stringr, GenomicRanges, Rsamtools, statmod (>= 1.4.15) Suggests: GenomicFeatures (>= 1.13.29), pasilla (>= 0.2.13), parathyroidSE, BiocStyle Enhances: parallel License: GPL (>= 3) MD5sum: 5fea2268be4c83f033f8504722c11215 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: HighThroughputSequencing, RNAseq, DifferentialExpression Author: Simon Anders and Alejandro Reyes , both at EMBL Heidelberg Maintainer: Alejandro Reyes source.ver: src/contrib/DEXSeq_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DEXSeq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DEXSeq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DEXSeq_1.8.0.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: 1.2.2 Depends: R (>= 2.15), methods, BiocGenerics Suggests: parallel, statmod, stats, DESeq, RColorBrewer License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: f2854f7f57cd2adc10e8172211010e49 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: HighThroughputSequencing, Sequencing, Bioinformatics, Mus_musculus, Homo_sapiens, Zea_Mays, Macaca_mulatta, Pan_troglodytes, RNASeq, GeneExpression, DifferentialExpression, CellBiology, HighTroughputSequencingData, HapMap, RNAExpressionData, RNAseqData, Classification, QualityControl Author: Guenter Klambauer Maintainer: Guenter Klambauer source.ver: src/contrib/dexus_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/dexus_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/dexus_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/dexus_1.2.2.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: 1.20.0 Depends: methods, Biobase (>= 2.5.5) License: GPL-2 MD5sum: 3e7549f13fc95367ad2d317230ec2c78 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: Bioinformatics, Microarray, DifferentialExpression Author: R. Alvarez-Gonzalez, D. Glez-Pena, F. Diaz, F. Fdez-Riverola Maintainer: Rodrigo Alvarez-Glez source.ver: src/contrib/DFP_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DFP_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DFP_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DFP_1.20.0.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: 1.8.5 Depends: R (>= 2.15.0), GenomicRanges Imports: RColorBrewer, amap, edgeR (>= 2.3.58), gplots, grDevices, stats, utils, IRanges, zlibbioc LinkingTo: Rsamtools Suggests: DESeq, Rsamtools, DESeq2 Enhances: rgl, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: 87d7af5f7f0686a9af71bf44f3c728df 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: Bioinformatics, HighThroughputSequencing, ChIPseq Author: Rory Stark, Gordon Brown Maintainer: Rory Stark source.ver: src/contrib/DiffBind_1.8.5.tar.gz win.binary.ver: bin/windows/contrib/3.0/DiffBind_1.8.5.zip win64.binary.ver: bin/windows64/contrib/3.0/DiffBind_1.8.5.zip mac.binary.ver: bin/macosx/contrib/3.0/DiffBind_1.8.5.tgz vignettes: vignettes/DiffBind/inst/doc/DiffBind.pdf vignetteTitles: DiffBind User's Guide hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/DiffBind/inst/doc/DiffBind.R Package: diffGeneAnalysis Version: 1.44.0 Imports: graphics, grDevices, minpack.lm (>= 1.0-4), stats, utils License: GPL MD5sum: a9af143109092c78a1cf8da3fcc72e1e NeedsCompilation: no Title: Performs differential gene expression Analysis Description: Analyze microarray data biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Choudary Jagarlamudi Maintainer: Choudary Jagarlamudi source.ver: src/contrib/diffGeneAnalysis_1.44.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/diffGeneAnalysis_1.44.0.zip win64.binary.ver: bin/windows64/contrib/3.0/diffGeneAnalysis_1.44.0.zip mac.binary.ver: bin/macosx/contrib/3.0/diffGeneAnalysis_1.44.0.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: 1.4.0 Depends: IRanges Imports: stats4, methods Suggests: lattice, parallel, MASS, RColorBrewer, xtable License: LGPL-3 Archs: i386, x64 MD5sum: 28ea6486b1b621084994a935741990aa 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: HighThroughputSequencing, Clustering, Classification Author: Martin Morgan Maintainer: Martin Morgan SystemRequirements: gsl source.ver: src/contrib/DirichletMultinomial_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DirichletMultinomial_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DirichletMultinomial_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DirichletMultinomial_1.4.0.tgz vignettes: vignettes/DirichletMultinomial/inst/doc/DirichletMultinomial.pdf vignetteTitles: An introduction to DirichletMultinomial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: dks Version: 1.8.0 Depends: R (>= 2.8) Imports: cubature License: GPL MD5sum: 52273ac0c0dc53524fd846db7ac70ad0 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: Bioinformatics,MultipleComparisons,QualityControl Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/dks_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/dks_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/dks_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/dks_1.8.0.tgz vignettes: vignettes/dks/inst/doc/betas2.pdf, vignettes/dks/inst/doc/dks.pdf vignetteTitles: betas2.pdf, dksTutorial hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/dks/inst/doc/dks.R Package: DNAcopy Version: 1.36.0 License: GPL (>= 2) Archs: i386, x64 MD5sum: e40f7a3ad4261751d623911c968ed6ee 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, CopyNumberVariants Author: Venkatraman E. Seshan, Adam Olshen Maintainer: Venkatraman E. Seshan source.ver: src/contrib/DNAcopy_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DNAcopy_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DNAcopy_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DNAcopy_1.36.0.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, CNAnorm, CNVrd2, CRImage, MEDIPS, snapCGH, SomatiCA importsMe: ADaCGH2, ArrayTV, ChAMP, Clonality, cn.farms, GWASTools, MEDIPS, MinimumDistance, Repitools, snapCGH, SomatiCA suggestsMe: beadarraySNP, Clonality, cn.mops, fastseg, genoset Package: DNaseR Version: 1.0.0 Depends: R (>= 2.10.0), IRanges Imports: Rsamtools, GenomicRanges Suggests: RUnit, BiocGenerics License: GPL-2 + file LICENSE MD5sum: 22981622f2af599cfbd19fea0c3adc5a 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DNaseR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DNaseR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DNaseR_1.0.0.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: 1.22.0 Depends: R (>= 2.4.0), KEGG.db, prada, biomaRt, methods Imports: AnnotationDbi License: Artistic-2.0 MD5sum: a2434ada8ec8069fbcfa39ea4310b8c8 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/domainsignatures_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/domainsignatures_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/domainsignatures_1.22.0.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: 2.0.0 Depends: R (>= 2.10), ggplot2 Imports: methods, plyr, qvalue, stats4, AnnotationDbi, DO.db, org.Hs.eg.db, igraph, scales, reshape2, graphics, GOSemSim, grid Suggests: clusterProfiler, ReactomePA, knitr License: Artistic-2.0 MD5sum: c66fc205ff4da92f75243868a5b4930f 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: Bioinformatics, Annotation Author: Guangchuang Yu, Li-Gen Wang Maintainer: Guangchuang Yu VignetteBuilder: knitr source.ver: src/contrib/DOSE_2.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DOSE_2.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DOSE_2.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DOSE_2.0.0.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: GOSemSim Package: DriverNet Version: 1.2.0 Depends: R (>= 2.10), methods License: GPL-3 MD5sum: 67b04d4dd947787b814996baa8fa4b29 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. Author: Ali Bashashati, Reza Haffari, Jiarui Ding, Gavin Ha, Kenneth Liu, Jamie Rosner and Sohrab Shah Maintainer: Jiarui Ding source.ver: src/contrib/DriverNet_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DriverNet_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DriverNet_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DriverNet_1.2.0.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: 2.2.0 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: eca330d914e8482a0ca0329c102b5136 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. Author: C. Pacini Maintainer: j. Saez-Rodriguez source.ver: src/contrib/DrugVsDisease_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DrugVsDisease_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DrugVsDisease_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DrugVsDisease_2.2.0.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: 1.8.0 Depends: Biobase, locfdr Imports: methods,bsseq,edgeR License: GPL MD5sum: 9e9821fb4b7d1fa61a1e7fc3886761b0 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: HighThroughputSequencing, RNAseq, ChIPseq, DNAMethylation, DifferentialExpression Author: Hao Wu Maintainer: Hao Wu source.ver: src/contrib/DSS_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DSS_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DSS_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DSS_1.8.0.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 Package: DTA Version: 2.8.0 Depends: R (>= 2.10), LSD Imports: scatterplot3d License: Artistic-2.0 MD5sum: 9392571037a68225272321ef154b6270 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_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DTA_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DTA_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DTA_2.8.0.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: dyebias Version: 1.20.0 Depends: R (>= 1.4.1), marray, Biobase Suggests: limma, convert, GEOquery, dyebiasexamples, methods License: GPL-3 MD5sum: 732d40a4a4b9d2b51c738c3264ef9b5b 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/dyebias_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/dyebias_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/dyebias_1.20.0.tgz vignettes: vignettes/dyebias/inst/doc/dyebias-vignette.pdf, vignettes/dyebias/inst/doc/dyebiasCompleteVignette.pdf, vignettes/dyebias/inst/doc/gassco.pdf vignetteTitles: dye bias correction, dyebiasCompleteVignette.pdf, gassco.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/dyebias/inst/doc/dyebias-vignette.R Package: DynDoc Version: 1.40.0 Depends: methods, utils Imports: methods License: Artistic-2.0 MD5sum: 2a474f56576857f4cac8d85b8c3c2abd 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/DynDoc_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/DynDoc_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/DynDoc_1.40.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: tkWidgets Package: EasyqpcR Version: 1.5.0 Imports: plyr, matrixStats, plotrix, gWidgetsRGtk2 Suggests: SLqPCR, qpcrNorm, qpcR, knitr License: GPL (>=2) MD5sum: f5825b692007129dd4a8001bc23589fd 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_1.5.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EasyqpcR_1.5.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EasyqpcR_1.5.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EasyqpcR_1.5.0.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: 1.8.8 Depends: genomeIntervals (>= 1.18.0), Biobase (>= 2.22.0), biomaRt (>= 2.18.0), edgeR (>= 3.4.0), Biostrings (>= 2.30.0), DESeq (>= 1.14.0), GenomicRanges (>= 1.14.3), IRanges (>= 1.20.5), Rsamtools (>= 1.14.1), ShortRead (>= 1.20.0) Imports: graphics, methods, parallel, utils, BiocGenerics (>= 0.8.0), LSD (>= 2.5) Suggests: BSgenome (>= 1.30.0), BSgenome.Dmelanogaster.UCSC.dm3 (>= 1.3.19), GenomicFeatures (>= 1.14.0), RnaSeqTutorial (>= 0.0.13), BiocStyle (>= 1.0.0) License: Artistic-2.0 MD5sum: 3816ae03ce766be4c4e479e32e892fe4 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_1.8.8.tar.gz win.binary.ver: bin/windows/contrib/3.0/easyRNASeq_1.8.8.zip win64.binary.ver: bin/windows64/contrib/3.0/easyRNASeq_1.8.8.zip mac.binary.ver: bin/macosx/contrib/3.0/easyRNASeq_1.8.8.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 Package: EBarrays Version: 2.26.0 Depends: R (>= 1.8.0), Biobase, lattice, methods Imports: Biobase, cluster, graphics, grDevices, lattice, methods, stats License: GPL (>= 2) Archs: i386, x64 MD5sum: 78d0e62674b879e1e26dc058b8c9010f 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_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EBarrays_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EBarrays_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EBarrays_2.26.0.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 suggestsMe: Category Package: EBcoexpress Version: 1.6.0 Depends: EBarrays, mclust, minqa Suggests: graph, igraph, colorspace License: GPL (>= 2) Archs: i386, x64 MD5sum: 2ffd3899d9eb837971c49e70766686d1 NeedsCompilation: yes Title: EBcoexpress for Differential Co-Expression Analysis Description: An Empirical Bayesian Approach to Differential Co-Expression Analysis at the Gene-Pair Level Author: John A. Dawson Maintainer: John A. Dawson source.ver: src/contrib/EBcoexpress_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EBcoexpress_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EBcoexpress_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EBcoexpress_1.6.0.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: 4.4.0 Imports: BiocGenerics (>= 0.7.1), methods, graphics, stats, abind, tiff, jpeg, png, locfit Suggests: BiocStyle License: LGPL Archs: i386, x64 MD5sum: f32947207f8835aee2ced389c1d3b038 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_4.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EBImage_4.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EBImage_4.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EBImage_4.4.0.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: 1.2.0 Depends: blockmodeling, gplots, R (>= 2.10) License: Artistic-2.0 MD5sum: 29f6b05fd6267f98d28b7e0615d854b8 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 Author: Ning Leng Maintainer: Ning Leng source.ver: src/contrib/EBSeq_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EBSeq_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EBSeq_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EBSeq_1.2.0.tgz vignettes: vignettes/EBSeq/inst/doc/EBSeq_Vignette.pdf vignetteTitles: EBSeq hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/EBSeq/inst/doc/EBSeq_Vignette.R importsMe: TCC Package: ecolitk Version: 1.34.0 Depends: R (>= 2.10) Imports: Biobase, graphics, methods Suggests: ecoliLeucine, ecolicdf, graph, multtest, affy License: GPL (>= 2) MD5sum: 02352023de4aea12a1bef3b5e650f214 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ecolitk_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ecolitk_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ecolitk_1.34.0.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: 1.8.0 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: 50da44bd4efff0b328cc40eac9f7c9de 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: HighThroughputSequencing, RNAseq, Preprocessing, QualityControl, DifferentialExpression Author: Davide Risso and Sandrine Dudoit Maintainer: Davide Risso source.ver: src/contrib/EDASeq_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/EDASeq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/EDASeq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/EDASeq_1.8.0.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 suggestsMe: HTSFilter, oneChannelGUI Package: edgeR Version: 3.4.2 Depends: R (>= 2.15.0), methods, limma Suggests: MASS, statmod, splines, locfit, KernSmooth License: GPL (>=2) Archs: i386, x64 MD5sum: d506df9467878c058f36de7df4023f11 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: Bioinformatics, DifferentialExpression, SAGE, HighThroughputSequencing, RNAseq, ChIPseq Author: Mark Robinson , Davis McCarthy , Yunshun Chen , Aaron Lun , Gordon Smyth Maintainer: Mark Robinson , Davis McCarthy , Yunshun Chen , Gordon Smyth source.ver: src/contrib/edgeR_3.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/edgeR_3.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/edgeR_3.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/edgeR_3.4.2.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, easyRNASeq, manta, methylMnM, TCC, tRanslatome importsMe: ampliQueso, ArrayExpressHTS, DiffBind, HTSFilter, MEDIPS, msmsTests, Repitools, rnaSeqMap, tweeDEseq suggestsMe: baySeq, BitSeq, clonotypeR, cqn, EDASeq, gage, GenomicRanges, goseq, GSVA, oneChannelGUI, SSPA Package: eiR Version: 1.2.0 Depends: R (>= 2.10.0), ChemmineR (>= 2.13.8), methods, DBI Imports: snow, tools, snowfall, RUnit, methods,ChemmineR,RCurl,digest, BiocGenerics Suggests: RCurl,snow,BiocStyle License: Artistic-2.0 MD5sum: 107cfcf5d5f73e59aa8ca27e9292ac9f 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, Bioinformatics, Proteomics Author: Kevin Horan Maintainer: Kevin Horan source.ver: src/contrib/eiR_1.2.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/eiR_1.2.0.tgz vignettes: vignettes/eiR/inst/doc/eiR.pdf vignetteTitles: eiR hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/eiR/inst/doc/eiR.R Package: eisa Version: 1.14.0 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: 576c7af718d25408212f333db1705db9 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/eisa_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/eisa_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/eisa_1.14.0.tgz vignettes: vignettes/eisa/inst/doc/EISA_biclust.pdf, vignettes/eisa/inst/doc/EISA_tutorial.pdf, vignettes/eisa/inst/doc/ISA_internals.pdf, vignettes/eisa/inst/doc/tissues.pdf vignetteTitles: The eisa and the biclust packages, The Iterative Signature Algorithm for Gene Expression Data, ISA_internals.pdf, tissues.pdf 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: ensemblVEP Version: 1.2.2 Depends: methods, BiocGenerics, GenomicRanges, VariantAnnotation Imports: Biostrings, IRanges Suggests: RUnit, BiocGenerics License: Artistic-2.0 MD5sum: c606f7f93a74f2af835c4dd39591911d NeedsCompilation: no Title: R Interface to Ensembl Variant Effect Predictor Description: Query the Ensembl Variant Effect Predictor via the perl API biocViews: Annotation, Bioinformatics Author: Valerie Obenchain , Maintainer: Valerie Obenchain SystemRequirements: Ensembl VEP (API version 67, 73 or 74) and the Perl package DBD::mysql must be installed. See the package README and Ensembl web site, http://www.ensembl.org/info/docs/variation/vep/index.html for installation instructions. source.ver: src/contrib/ensemblVEP_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/ensemblVEP_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/ensemblVEP_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/ensemblVEP_1.2.2.tgz vignettes: vignettes/ensemblVEP/inst/doc/ensemblVEP.pdf vignetteTitles: ensemblVEP hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ensemblVEP/inst/doc/ensemblVEP.R Package: ENVISIONQuery Version: 1.10.0 Depends: rJava, XML, utils License: GPL-2 MD5sum: f5b43c9f1bb374b0e5715360a064e072 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ENVISIONQuery_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ENVISIONQuery_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ENVISIONQuery_1.10.0.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: 1.2.0 Depends: R (>= 2.12.0), methods, Biobase, IRanges, GenomicRanges Imports: methods, BiocGenerics, Biobase, IRanges, GenomicRanges, beadarray License: LGPL-3 MD5sum: bbd5989ca154572648ea0ebfb67dd604 NeedsCompilation: no Title: Epigenetic and gene expression data normalization and integration with mixture models Description: A package for the integrative analysis of microarray based gene expression 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/epigenomix_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/epigenomix_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/epigenomix_1.2.0.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: 1.0.0 Depends: R (>= 3.0.1), methods, Biobase, GenomicRanges (>= 1.13.47), Imports: httpuv, rjson LinkingTo: GenomicRanges, httpuv Suggests: testthat, roxygen2, knitr, antiProfilesData, hgu133plus2.db License: GPL-3 MD5sum: a6f3976f1b3f4aea31aed200d9f14f60 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, Bioinformatics, GUI Author: Hector Corrada Bravo, Florin Chelaru, Llewellyn Smith, Naomi Goldstein Maintainer: Hector Corrada Bravo VignetteBuilder: knitr source.ver: src/contrib/epivizr_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/epivizr_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/epivizr_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/epivizr_1.0.0.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: 2.4.0 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: 094ca4267b1ba2de2aad085248709ea8 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, DualChannel, Preprocessing, GeneExpression, Transcription Author: Sylvain Gubian , Alain Sewer , PMP SA Maintainer: Sylvain Gubian source.ver: src/contrib/ExiMiR_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ExiMiR_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ExiMiR_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ExiMiR_2.4.0.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: 1.8.1 Depends: IRanges, GenomicRanges, Rsamtools Imports: stats4, methods Suggests: Biostrings License: GPL (>= 2) Archs: i386, x64 MD5sum: 8b2a274da99bb0769b622b3cba4e9c28 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: CopyNumberVariants, Sequencing, HighThroughputSequencing, Genetics Author: Michael Love Maintainer: Michael Love source.ver: src/contrib/exomeCopy_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/exomeCopy_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/exomeCopy_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/exomeCopy_1.8.1.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 Package: exomePeak Version: 1.0.0 Depends: Rsamtools, GenomicFeatures (>= 1.0.0), rtracklayer License: GPL-2 MD5sum: 12ea90e70ed71adc86b40960f8884d5c 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, HighThroughputSequencing, Methylseq, RNAseq Author: Jia Meng Maintainer: Jia Meng source.ver: src/contrib/exomePeak_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/exomePeak_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/exomePeak_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/exomePeak_1.0.0.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: 1.26.0 Depends: R (>= 2.6.2) Imports: limma, rggobi, RGtk2 Suggests: cairoDevice License: GPL-2 MD5sum: fd7a41ac08533c122b211f24dc36ed9f 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/explorase_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/explorase_1.26.0.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: 1.14.0 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: e31903f8da9f509bc3f1dc8519756ffb 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ExpressionView_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ExpressionView_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ExpressionView_1.14.0.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: 2.8.0 Depends: R (>= 2.8.0), Biobase Imports: methods, graphics, grDevices, stats, utils License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: f9939b8e35f1f6f38660224ffc16536e 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: Bioinformatics, Statistics, Microarray, DifferentialExpression, MultipleComparisons, Clustering, Visualization Author: Sepp Hochreiter Maintainer: Sepp Hochreiter URL: http://www.bioinf.jku.at/software/fabia/fabia.html source.ver: src/contrib/fabia_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/fabia_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/fabia_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/fabia_2.8.0.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: 1.38.0 Depends: Biobase (>= 2.5.5) Imports: stats Suggests: affy, genefilter, multtest License: LGPL MD5sum: 959ab3f9b4379c6c46cc82df060454ad 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: Bioinformatics, Microarray, DifferentialExpression Author: Denise Scholtens Maintainer: Denise Scholtens source.ver: src/contrib/factDesign_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/factDesign_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/factDesign_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/factDesign_1.38.0.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: 1.14.0 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: 6a67655c732c0dc14fd56ffb57a9bf18 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/farms_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/farms_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/farms_1.14.0.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: fastseg Version: 1.8.0 Depends: R (>= 2.13), GenomicRanges, Biobase Imports: graphics, stats, IRanges, BiocGenerics Suggests: DNAcopy, oligo License: LGPL (>= 2.0) Archs: i386, x64 MD5sum: d4532efc7a013925022ae42ca5b13da1 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, CopyNumberVariants Author: Guenter Klambauer Maintainer: Guenter Klambauer URL: http://www.bioinf.jku.at/software/fastseg/fastseg.html source.ver: src/contrib/fastseg_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/fastseg_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/fastseg_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/fastseg_1.8.0.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: 1.34.0 Imports: tcltk, graphics, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 02a8161d9bc8d178226e594063cd85a8 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,MultipleComparisons Author: Yoav Benjamini, Effi Kenigsberg, Anat Reiner, Daniel Yekutieli Maintainer: Effi Kenigsberg source.ver: src/contrib/fdrame_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/fdrame_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/fdrame_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/fdrame_1.34.0.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: 1.6.0 Depends: R (>= 2.10.0), TTR, methods Imports: Biobase, BiocGenerics, affy, lumi, methylumi, sfsmisc Suggests: genefilter, affy, ffpeExampleData License: GPL (>2) MD5sum: 04aa6d9f0c9a6f003b959a1105013a4f 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, Bioinformatics Author: Levi Waldron Maintainer: Levi Waldron source.ver: src/contrib/ffpe_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ffpe_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ffpe_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ffpe_1.6.0.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: 1.2.2 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: 8da6f24fc3e8eb6c606b9996b7e875c6 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_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/FGNet_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/FGNet_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/FGNet_1.2.2.tgz vignettes: vignettes/FGNet/inst/doc/FGNet-vignette.pdf vignetteTitles: FGNet hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FGNet/inst/doc/FGNet-vignette.R Package: flagme Version: 1.18.0 Depends: gcspikelite, xcms Imports: gplots, graphics, MASS, methods, SparseM, stats, utils License: LGPL (>= 2) Archs: i386, x64 MD5sum: cd5d95ad54efd5d81958b5b0a5a14881 NeedsCompilation: yes Title: Analysis of Metabolomics GC/MS Data Description: Fragment-level analysis of gas chromatography - mass spectrometry metabolomics data biocViews: Bioinformatics, DifferentialExpression, MassSpectrometry Author: Mark Robinson Maintainer: Mark Robinson source.ver: src/contrib/flagme_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flagme_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flagme_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flagme_1.18.0.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: 1.0.1 Depends: R (>= 2.10.0) Imports: methods, Matrix, IRanges, GenomicRanges License: GPL-3 Archs: i386, x64 MD5sum: 9b10511af759e5d8a3b74ea3e4d123b8 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: Bioinformatics, RNAseq Author: Elsa Bernard, Laurent Jacob, Julien Mairal and Jean-Philippe Vert Maintainer: Elsa Bernard source.ver: src/contrib/flipflop_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/flipflop_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.0/flipflop_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.0/flipflop_1.0.1.tgz vignettes: vignettes/flipflop/inst/doc/flipflop.pdf vignetteTitles: FlipFlop: Fast Lasso-based Isoform Prediction as a Flow Problem hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flipflop/inst/doc/flipflop.R Package: flowBeads Version: 1.0.0 Depends: R (>= 2.15.0), methods, Biobase, rrcov, flowCore Imports: flowCore, rrcov, knitr, xtable Suggests: flowViz License: Artistic-2.0 MD5sum: b66125a7dd680b7cc09eb3415c41b154 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowBeads_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowBeads_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowBeads_1.0.0.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: flowClust Version: 3.2.8 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: 5ea7c336fad0cfa431c515f8cfef4a58 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, Bioinformatics, Visualization, FlowCytometry Author: Raphael Gottardo , Kenneth Lo , Greg Finak Maintainer: Greg Finak , Mike Jiang source.ver: src/contrib/flowClust_3.2.8.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowClust_3.2.8.zip win64.binary.ver: bin/windows64/contrib/3.0/flowClust_3.2.8.zip mac.binary.ver: bin/macosx/contrib/3.0/flowClust_3.2.8.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 dependsOnMe: flowMerge importsMe: flowPhyto, flowTrans, flowType suggestsMe: BiocGenerics Package: flowCore Version: 1.28.24 Depends: R (>= 2.10.0) Imports: Biobase, BiocGenerics (>= 0.1.14), feature, graph, graphics, grDevices, MASS, methods, rrcov, stats, utils, stats4, corpcor Suggests: Rgraphviz, flowViz, ncdf License: Artistic-2.0 Archs: i386, x64 MD5sum: 13fd089a2e6eb6b17b110b1cd1ba5ddf 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_1.28.24.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowCore_1.28.24.zip win64.binary.ver: bin/windows64/contrib/3.0/flowCore_1.28.24.zip mac.binary.ver: bin/macosx/contrib/3.0/flowCore_1.28.24.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, flowClust, flowFP, flowMerge, flowStats, flowTrans, flowUtils, flowViz, ncdfFlow, plateCore importsMe: flowBeads, flowFit, flowFlowJo, flowFP, flowMeans, flowPhyto, flowQ, flowStats, flowTrans, flowType, flowUtils, flowViz, plateCore, spade suggestsMe: flowQB, RchyOptimyx Package: flowFit Version: 1.0.0 Depends: R (>= 2.12.2) Imports: flowCore, flowViz, graphics, methods, kza, minpack.lm, gplots Suggests: flowFitExampleData License: Artistic-2.0 MD5sum: ff1ab7c4faaf3da63cdd0fa7c58b16e9 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, Bioinformatics Author: Davide Rambaldi Maintainer: Davide Rambaldi source.ver: src/contrib/flowFit_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowFit_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowFit_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowFit_1.0.0.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: 1.20.0 Depends: R (>= 2.5.0), MASS, Imports: flowCore, XML (>= 1.96), methods, Biobase License: GPL (>=3) MD5sum: 2154bab4a91402227d9faa94e8eee945 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowFlowJo_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowFlowJo_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowFlowJo_1.20.0.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: 1.20.0 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: 1beb5b580f9f95471a4d339bfe8419b9 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: Bioinformatics, FlowCytometry, CellBasedAssays, Clustering, Visualization Author: Herb Holyst , Wade Rogers Maintainer: Herb Holyst source.ver: src/contrib/flowFP_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowFP_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowFP_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowFP_1.20.0.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 Package: flowMap Version: 1.0.0 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), scales(>= 0.2.3), methods (>= 2.14), License: GPL (>=2) MD5sum: 682cbfafe3862cfc0fe9b76a2e918cee NeedsCompilation: no Title: A probabilistic algorithm for matching and comparing multiple flow cytometry samples Description: This package provides an algorithm to compare and match cell populations across multiple flow cytometry samples. The method is based on the Friedman-Rafsky test, a nonparametric multivariate statistical test, where two cell distributions match if they occupy a similar feature space. The algorithm allows the users to specify a reference sample for comparison or to construct a reference sample from the available data. The output of the algorithm is a set of text files where the cell population labels are replaced by a metaset of population labels, generated from the matching process. biocViews: MultipleComparisons, FlowCytometry Author: Chiaowen Joyce Hsiao and Yu Qian Maintainer: Chiaowen Joyce Hsiao source.ver: src/contrib/flowMap_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowMap_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowMap_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowMap_1.0.0.tgz vignettes: vignettes/flowMap/inst/doc/flowMap.pdf vignetteTitles: Multiple sample comparison in flow cytometry data with flowMap hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowMap/inst/doc/flowMap.R Package: flowMeans Version: 1.14.0 Depends: R (>= 2.10.0) Imports: Biobase, graphics, grDevices, methods, rrcov, stats, feature, flowCore License: Artistic-2.0 MD5sum: 56ac5698e7aff623441e6ba02e7b8694 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: Bioinformatics, FlowCytometry, CellBiology, Clustering, Cancer, FlowCytData, StemCells, HIV Author: Nima Aghaeepour Maintainer: Nima Aghaeepour source.ver: src/contrib/flowMeans_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowMeans_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowMeans_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowMeans_1.14.0.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: 2.10.0 Depends: Rgraphviz, flowClust, flowCore, methods,snow,foreach,graph,feature Imports: rrcov, flowClust,flowCore, graphics, methods, rrcov, stats, utils, BiocGenerics (>= 0.1.6) Suggests: Rgraphviz Enhances: doMC, multicore License: Artistic-2.0 MD5sum: 71b9c3210fa41f0be684594a2a878c0a 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: Bioinformatics, Clustering, FlowCytometry Author: Greg Finak , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowMerge_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowMerge_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowMerge_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowMerge_2.10.0.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: 1.4.0 Depends: R (>= 2.12.0) Enhances: flowCore License: Artistic-1.0 Archs: i386, x64 MD5sum: 91b84958e6e80e638265a84b71ba4425 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: Flow cytometry, Clustering, Gating, Bioinformatics Author: Yongchao Ge Maintainer: Yongchao Ge source.ver: src/contrib/flowPeaks_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowPeaks_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowPeaks_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowPeaks_1.4.0.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: 1.14.0 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: 89757a8be9e8ee2ce66516bafbde7bcb NeedsCompilation: no Title: Methods for Continuous Flow Cytometry Description: Automated Analysis of Continuous Flow Cytometry Data. biocViews: FlowCytometry, DataImport, QualityControl, Classification, Bioinformatics, Visualization, Clustering Author: Francois Ribalet and David M. Schruth Maintainer: Chris Berthiaume URL: http://seaflow.ocean.washington.edu source.ver: src/contrib/flowPhyto_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowPhyto_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowPhyto_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowPhyto_1.14.0.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: 1.10.0 Depends: R (>= 2.13.0), methods Suggests: vcd License: Artistic-2.0 MD5sum: dffd6093206d52344a7873cb34579ac8 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowPlots_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowPlots_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowPlots_1.10.0.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: 1.22.4 Depends: R (>= 2.10.0), methods, BiocGenerics (>= 0.1.3), outliers, lattice, flowViz, mvoutlier, bioDist, parody, RColorBrewer, latticeExtra Imports: methods, BiocGenerics, geneplotter, flowCore, flowViz, IRanges Suggests: flowStats License: Artistic-2.0 MD5sum: 3a7ca352cedd647be4810e3184a696be 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_1.22.4.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/flowQ_1.22.4.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: 1.4.0 Imports: Biobase, graphics,methods, flowCore,stats,MASS Suggests: MASS, flowCore, xtable License: Artistic-2.0 MD5sum: d60903c68331e1eb35ec890749b54bba 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowQB_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowQB_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowQB_1.4.0.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/flowQB_Sweave_.R, vignettes/flowQB/inst/doc/IntroductoryflowQBNIH.R Package: flowStats Version: 3.20.12 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 Suggests: flowViz, xtable Enhances: RBGL,ncdfFlow,graph License: Artistic-2.0 MD5sum: 47de71e0d6610ac535c2219ba41462de 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_3.20.12.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowStats_3.20.3.zip win64.binary.ver: bin/windows64/contrib/3.0/flowStats_3.20.3.zip mac.binary.ver: bin/macosx/contrib/3.0/flowStats_3.20.12.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 suggestsMe: flowQ Package: flowTrans Version: 1.14.0 Depends: R (>= 2.11.0), flowCore, flowViz,flowClust Imports: flowCore, methods, flowViz, stats, flowClust License: Artistic-2.0 MD5sum: bb53b8c7af3c534368eb88eb2508f2b2 NeedsCompilation: no Title: Parameter Optimization for Flow Cytometry Data Transformation Description: Profile maximum likelihood estimation of parameters for flow cytometry data transformations. biocViews: Bioinformatics, FlowCytometry Author: Greg Finak , Juan Manuel-Perez , Raphael Gottardo Maintainer: Greg Finak source.ver: src/contrib/flowTrans_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowTrans_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowTrans_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowTrans_1.14.0.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: 2.2.1 Depends: R (>= 2.10), Rcpp (>= 0.10.4) Imports: Biobase, graphics, grDevices, methods, flowCore, flowMeans, sfsmisc, rrcov, flowClust, flowMerge, stats LinkingTo: Rcpp Suggests: xtable License: Artistic-2.0 Archs: i386, x64 MD5sum: d69a6f11dcc3472e6be941067dee473f 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_2.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowType_2.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/flowType_2.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/flowType_2.2.1.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: 1.22.0 Depends: R (>= 2.2.0), flowCore (>= 1.2.0) Imports: Biobase, flowCore, graph, methods, RUnit, stats, utils, XML, flowViz Suggests: gatingMLData License: Artistic-2.0 MD5sum: 6c92e7880aec396ddeaa86a9cda6088c 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: Nishant Gopalakrishnan source.ver: src/contrib/flowUtils_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowUtils_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/flowUtils_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/flowUtils_1.22.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: flowViz Version: 1.26.16 Depends: R (>= 2.7.0), flowCore (>= 1.4.17), lattice Imports: stats4, Biobase, flowCore, graphics, grDevices, grid, KernSmooth, lattice, latticeExtra, MASS, methods, RColorBrewer, stats, utils, hexbin,IDPmisc Suggests: colorspace License: Artistic-2.0 MD5sum: e744dd24966f16aaaa1f58ee9c9e6b0d 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 source.ver: src/contrib/flowViz_1.26.16.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowViz_1.26.16.zip win64.binary.ver: bin/windows64/contrib/3.0/flowViz_1.26.16.zip mac.binary.ver: bin/macosx/contrib/3.0/flowViz_1.26.16.tgz vignettes: vignettes/flowViz/inst/doc/filters.pdf vignetteTitles: Visualizing Gates with Flow Cytometry Data hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/flowViz/inst/doc/filters.R dependsOnMe: flowClust, flowFP, flowQ, ncdfFlow, plateCore importsMe: flowFit, flowFP, flowQ, flowStats, flowTrans, flowUtils suggestsMe: flowBeads, flowCore, flowStats, spade Package: flowWorkspace Version: 3.8.61 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 License: Artistic-2.0 Archs: i386, x64 MD5sum: 95e97cde157e158cddda0fafc86fc494 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_3.8.61.tar.gz win.binary.ver: bin/windows/contrib/3.0/flowWorkspace_3.8.61.zip win64.binary.ver: bin/windows64/contrib/3.0/flowWorkspace_3.8.61.zip mac.binary.ver: bin/macosx/contrib/3.0/flowWorkspace_3.8.61.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 Package: fmcsR Version: 1.4.0 Depends: R (>= 2.10.0), ChemmineR, methods Suggests: BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: 5e5f968c3787b85b2be1df20481f3926 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, Bioinformatics, Proteomics Author: Yan Wang, Tyler Backman, Kevin Horan, Thomas Girke Maintainer: ChemmineR Team URL: http://manuals.bioinformatics.ucr.edu/home/chemminer source.ver: src/contrib/fmcsR_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/fmcsR_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/fmcsR_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/fmcsR_1.4.0.tgz vignettes: vignettes/fmcsR/inst/doc/fmcsR.pdf vignetteTitles: gpls Tutorial hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/fmcsR/inst/doc/fmcsR.R Package: frma Version: 1.14.0 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: 52fa2bf38c4590957f238d7a12400ffe 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/frma_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/frma_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/frma_1.14.0.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: 1.14.0 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: 6e4f1863492df0cc47860fddb1c87ca9 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/frmaTools_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/frmaTools_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/frmaTools_1.14.0.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: 1.4.0 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: 7958926015cce5abd4c11775a6cf5a83 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/FunciSNP_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/FunciSNP_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/FunciSNP_1.4.0.tgz vignettes: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.pdf, vignettes/FunciSNP/inst/doc/UCSC_genomeviewer_glioma.pdf vignetteTitles: FunciSNP Vignette, UCSC_genomeviewer_glioma.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/FunciSNP/inst/doc/FunciSNP_vignette.R Package: gaga Version: 2.8.0 Depends: R (>= 2.8.0), Biobase, coda, EBarrays, mgcv Enhances: parallel License: GPL (>= 2) Archs: i386, x64 MD5sum: f22d24daf95e384cb95d246a2b61e1d0 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,MultipleComparisons,DifferentialExpression,Classification Author: David Rossell . Maintainer: David Rossell source.ver: src/contrib/gaga_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gaga_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gaga_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gaga_2.8.0.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 dependsOnMe: casper Package: gage Version: 2.12.3 Depends: R (>= 2.10) Imports: graph, KEGGREST Suggests: pathview, gageData, GO.db, org.Hs.eg.db, hgu133a.db, GSEABase, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene, DESeq, DESeq2, edgeR, limma License: GPL (>=2.0) MD5sum: 70047008c3e6dee2f0ea4f830a7a74ec 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, MultipleComparisons, GeneSetEnrichment Author: Weijun Luo Maintainer: Weijun Luo URL: http://www.biomedcentral.com/1471-2105/10/161 source.ver: src/contrib/gage_2.12.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/gage_2.12.3.zip win64.binary.ver: bin/windows64/contrib/3.0/gage_2.12.3.zip mac.binary.ver: bin/macosx/contrib/3.0/gage_2.12.3.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: 1.30.0 Depends: R (>= 2.3.0), rJava (>= 0.4), graph (>= 1.10.2), RUnit (>= 0.4.17) License: GPL version 2 or newer MD5sum: f0b499272d62a4df868ee234295bc6c6 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: ConnectTools, NetworkVisualization, Annotation, GraphsAndNetworks, DataImport Author: Paul Shannon Maintainer: Christopher Bare URL: http://gaggle.systemsbiology.net/docs/geese/r/ source.ver: src/contrib/gaggle_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gaggle_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gaggle_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gaggle_1.30.0.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: 2.6.0 Depends: R (>= 2.10) License: GPL-2 MD5sum: 70aa3badaa5ddfa3911086a572b1668b 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, CopyNumberVariants Author: Sandro Morganella et al. Maintainer: S. Morganella source.ver: src/contrib/gaia_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gaia_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gaia_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gaia_2.6.0.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: gCMAP Version: 1.6.0 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: dcb7111da0d9cddd04c8e5ca4018ccf1 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: Bioinformatics, Microarray, Software, Pathways, Annotation Author: Thomas Sandmann , Richard Bourgon and Sarah Kummerfeld Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAP_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gCMAP_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gCMAP_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gCMAP_1.6.0.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: 1.2.0 Depends: brew, gCMAP (>= 1.3.0), R (>= 2.15.0), yaml Imports: Biobase, annotate, AnnotationDbi, BiocGenerics, brew, graphics, grDevices, GSEABase, hwriter, IRanges, methods, parallel, Rook, 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: b6cac726470d579bcfeaae4452c7da91 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: Bioinformatics, GUI, GeneSetEnrichment, Visualization Author: Thomas Sandmann Maintainer: Thomas Sandmann source.ver: src/contrib/gCMAPWeb_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gCMAPWeb_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gCMAPWeb_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gCMAPWeb_1.2.0.tgz vignettes: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.pdf, vignettes/gCMAPWeb/inst/doc/referenceDatasets.pdf, vignettes/gCMAPWeb/inst/doc/tutorial.pdf vignetteTitles: gCMAPWeb configuration, Recreating the Broad Connectivity Map v1, tutorial.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/gCMAPWeb/inst/doc/gCMAPWeb.R, vignettes/gCMAPWeb/inst/doc/referenceDatasets.R Package: gcrma Version: 2.34.0 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: 44f0435123c2a962914dc6737d6881c2 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_2.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gcrma_2.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gcrma_2.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gcrma_2.34.0.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: 1.38.0 Depends: R (>= 1.7.1), locfit, tkrplot, methods Imports: graphics, grDevices, methods, stats, tcltk, utils, xtable License: file LICENSE License_restricts_use: yes MD5sum: b2aa28768a99e9f59d77e562b939fb3f 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genArise_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genArise_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genArise_1.38.0.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: GENE.E Version: 1.2.0 Depends: R (>= 2.7.0), h5r (>= 1.4.1), RCurl (>= 1.6-6) Imports: h5r, RCurl Suggests: RUnit, BiocGenerics, knitr, golubEsets (>= 1.0) License: GPL-2 MD5sum: d94f9de38da2238474dbdbedeb3cc7f9 NeedsCompilation: no Title: Interact with GENE-E from R Description: Interactive exploration of matrices in GENE-E. biocViews: ConnectTools 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GENE.E_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GENE.E_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GENE.E_1.2.0.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: GeneAnswers Version: 2.4.0 Depends: R (>= 2.10.0), 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: 3bfb5e0b4060305f97f5b88c0a098990 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_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneAnswers_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneAnswers_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneAnswers_2.4.0.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: GeneExpressionSignature Version: 1.8.0 Depends: R (>= 2.13), Biobase, PGSEA Suggests: apcluster,GEOquery License: GPL-2 MD5sum: 94c73d44a69d21e96c3fa93256533f94 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: Bioinformatics, GeneExpression Author: Yang Cao Maintainer: Yang Cao , Fei Li ,Lu Han source.ver: src/contrib/GeneExpressionSignature_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneExpressionSignature_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneExpressionSignature_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneExpressionSignature_1.8.0.tgz vignettes: vignettes/GeneExpressionSignature/inst/doc/GeneExpressionSignature.pdf vignetteTitles: GeneExpressionSignature hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: genefilter Version: 1.44.0 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: 9b368a3942b705cc1547c2c36ddc23ee NeedsCompilation: yes Title: genefilter: methods for filtering genes from microarray experiments Description: Some basic functions for filtering genes biocViews: Bioinformatics, Microarray Author: R. Gentleman, V. Carey, W. Huber, F. Hahne Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/genefilter_1.44.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genefilter_1.44.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genefilter_1.44.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genefilter_1.44.0.tgz vignettes: vignettes/genefilter/inst/doc/howtogenefilter.pdf, vignettes/genefilter/inst/doc/howtogenefinder.pdf, vignettes/genefilter/inst/doc/independent_filtering_plots.pdf, vignettes/genefilter/inst/doc/independent_filtering.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, Additional plots for: Independent filtering increases power for detecting differentially expressed genes,, Bourgon et al.,, PNAS (2010), Diagnostics for independent filtering 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, Agi4x44PreProcess, cellHTS, cellHTS2, charm, CNTools, GeneMeta, MLInterfaces, simpleaffy importsMe: affycoretools, affyQCReport, annmap, arrayQualityMetrics, Category, DESeq, DESeq2, eisa, gCMAP, GGBase, GSRI, methyAnalysis, methylumi, minfi, phenoTest, Ringo, simpleaffy, tilingArray, XDE suggestsMe: AffyExpress, annotate, ArrayTools, BiocCaseStudies, BioNet, Category, categoryCompare, clusterStab, codelink, factDesign, ffpe, GOstats, GSEAlm, GSVA, logicFS, lumi, MCRestimate, oligo, oneChannelGUI, phyloseq, pvac, qpgraph, rtracklayer, siggenes, SSPA, topGO, VanillaICE, XDE Package: genefu Version: 1.12.0 Depends: R (>= 2.10), survcomp, mclust, biomaRt Imports: amap Suggests: GeneMeta, breastCancerVDX, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerUNT, breastCancerNKI, rmeta, Biobase, xtable License: Artistic-2.0 MD5sum: f8312822b06b1ab774051d89cb607ed6 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genefu_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genefu_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genefu_1.12.0.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: 1.12.1 Depends: seqinr, hash, methods License: GPL version 2 MD5sum: 3bd578793567f5726dbdae72df1791ad 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_1.12.1.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/GeneGA_1.12.1.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: 1.34.0 Depends: R (>= 2.10), methods, Biobase (>= 2.5.5), genefilter Imports: methods, Biobase (>= 2.5.5) Suggests: RColorBrewer License: Artistic-2.0 MD5sum: c0024ad667f196e0c1ae35d8bde513d1 NeedsCompilation: no Title: MetaAnalysis for High Throughput Experiments Description: A collection of meta-analysis tools for analysing high throughput experimental data biocViews: Bioinformatics Author: Lara Lusa , R. Gentleman, M. Ruschhaupt Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GeneMeta_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneMeta_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneMeta_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneMeta_1.34.0.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: 1.4.1 Depends: R (>= 2.15.1), Rcpp (>= 0.9.13), graph Imports: plyr, graph LinkingTo: Rcpp Suggests: RUnit, BiocGenerics, Rgraphviz, XML, RCytoscape License: GPL (>= 2) Archs: i386, x64 MD5sum: efc7d69b255a9af97fdb18b80a59973c 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: HighThroughputSequencing, Microarray, GraphsAndNetworks Author: Jianhong Ou and Lihua Julie Zhu Maintainer: Jianhong Ou source.ver: src/contrib/GeneNetworkBuilder_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneNetworkBuilder_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneNetworkBuilder_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneNetworkBuilder_1.4.1.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: geneplotter Version: 1.40.0 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: 6c8bead575f194a4331303b6d3a21bf4 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/geneplotter_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/geneplotter_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/geneplotter_1.40.0.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, flowQ, IsoGeneGUI, MethylSeekR, RNAinteract, RNAither suggestsMe: BiocCaseStudies, biocGraph, Category, GOstats, maDB Package: geneRecommender Version: 1.34.0 Depends: R (>= 1.8.0), Biobase (>= 1.4.22), methods Imports: Biobase, methods, stats License: GPL (>= 2) MD5sum: 3825b54b01bdd522a470084ac2a1c168 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/geneRecommender_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/geneRecommender_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/geneRecommender_1.34.0.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: 1.18.0 Depends: methods, Biobase (>= 2.5.5), Biostrings Imports: Biobase (>= 2.5.5), affxparser, RColorBrewer, Biostrings Suggests: BSgenome, affy, AnnotationDbi License: GPL (>= 2) MD5sum: e17945bcab8383af055b1e4a9c504fa0 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneRegionScan_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneRegionScan_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneRegionScan_1.18.0.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: GeneSelectMMD Version: 2.6.0 Depends: R (>= 2.13.2), Biobase Imports: Biobase, MASS, graphics, stats, survival, limma Suggests: ALL License: GPL (>= 2) Archs: i386, x64 MD5sum: 9291f73ddd82dbaf961b8656aabfcaaa 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: Bioinformatics, DifferentialExpression Author: Jarrett Morrow , Weiliang Qiu , Wenqing He , Xiaogang Wang , Ross Lazarus . Maintainer: Weiliang Qiu source.ver: src/contrib/GeneSelectMMD_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneSelectMMD_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneSelectMMD_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneSelectMMD_2.6.0.tgz vignettes: vignettes/GeneSelectMMD/inst/doc/GS207runTimesSim1k.pdf, vignettes/GeneSelectMMD/inst/doc/gsMMD.pdf vignetteTitles: GS207runTimesSim1k.pdf, 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: 2.12.1 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: 2c2d30187e6085d26d9108ffd69d530d 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: Statistics, DifferentialExpression Author: Martin Slawski , Anne-Laure Boulesteix . Maintainer: Martin Slawski source.ver: src/contrib/GeneSelector_2.12.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneSelector_2.12.1.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneSelector_2.12.1.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneSelector_2.12.1.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: 1.2.0 Depends: R (>= 2.10.1), Biobase (>= 2.5.5), EBarrays, minet, methods Imports: e1071, ipred, graphics, BiocGenerics Suggests: leukemiasEset Enhances: RColorBrewer, igraph License: GPL (>= 2) MD5sum: 184da30130b507518aa087cee9acc58e 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: Bioinformatics, 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/geNetClassifier_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/geNetClassifier_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/geNetClassifier_1.2.0.tgz vignettes: vignettes/geNetClassifier/inst/doc/geNetClassifier-manual.pdf, vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.pdf vignetteTitles: geNetClassifier-manual.pdf, geNetClassifier-vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/geNetClassifier/inst/doc/geNetClassifier-vignette.R Package: GeneticsDesign Version: 1.30.0 Imports: gmodels, graphics, gtools (>= 2.4.0), mvtnorm, stats License: GPL-2 MD5sum: 07c7abc5204fee6ccd78a2c18523b6cb 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneticsDesign_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneticsDesign_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneticsDesign_1.30.0.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: 1.24.0 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: dd3f093a3955b65c698890dc9167481d 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GeneticsPed_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GeneticsPed_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GeneticsPed_1.24.0.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: 1.14.0 Imports: graphics, stats, utils License: GPL (>=2) Archs: i386, x64 MD5sum: 9c3d242f05866785d24b8667476d85a6 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genoCN_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genoCN_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genoCN_1.14.0.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: 1.22.0 Depends: R (>= 2.10), methods, biomaRt, grid License: Artistic-2.0 MD5sum: 2af96c5bff1723ec1608b1bbf1589489 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GenomeGraphs_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GenomeGraphs_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GenomeGraphs_1.22.0.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: genomeIntervals Version: 1.18.0 Depends: R (>= 2.15.0), methods, intervals (>= 0.14.0), BiocGenerics (>= 0.3.2) Imports: methods, Biobase License: Artistic-2.0 MD5sum: 71dc893e51b2837753b25c8da8dbbabc 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genomeIntervals_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genomeIntervals_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genomeIntervals_1.18.0.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: easyRNASeq, girafe Package: genomes Version: 2.8.0 Depends: R (>= 2.11), XML, RCurl, GenomicRanges, IRanges, Biostrings License: Artistic-2.0 MD5sum: 7ab9665c6ba2bbb35c263f9795695df1 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_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genomes_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genomes_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genomes_2.8.0.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: GenomicFeatures Version: 1.14.5 Depends: BiocGenerics (>= 0.1.0), IRanges (>= 1.17.13), GenomicRanges (>= 1.13.16), AnnotationDbi (>= 1.23.14) Imports: methods, DBI (>= 0.2-5), RSQLite (>= 0.8-1), BiocGenerics, IRanges, GenomicRanges, Biostrings (>= 2.23.2), rtracklayer (>= 1.15.1), biomaRt (>= 2.17.1), RCurl, utils, Biobase (>= 2.15.1) Suggests: rtracklayer, biomaRt, org.Mm.eg.db, Biostrings, 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 License: Artistic-2.0 MD5sum: ead4526139cc292316cff8d328f56692 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, HighThroughputSequencing Author: M. Carlson, H. Pages, P. Aboyoun, S. Falcon, M. Morgan, D. Sarkar, M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicFeatures_1.14.5.tar.gz win.binary.ver: bin/windows/contrib/3.0/GenomicFeatures_1.14.5.zip win64.binary.ver: bin/windows64/contrib/3.0/GenomicFeatures_1.14.5.zip mac.binary.ver: bin/macosx/contrib/3.0/GenomicFeatures_1.14.5.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: ChIPpeakAnno, exomePeak, OrganismDbi, SplicingGraphs importsMe: AllelicImbalance, biovizBase, casper, ChIPpeakAnno, customProDB, ggbio, gmapR, Gviz, HTSeqGenie, lumi, MEDIPS, methyAnalysis, QuasR, SplicingGraphs, VariantAnnotation, VariantTools suggestsMe: biomvRCNS, Biostrings, chipseq, DEXSeq, easyRNASeq, GenomicRanges, Gviz, HTSeqGenie, MiRaGE, RIPSeeker, Rsamtools, ShortRead Package: GenomicRanges Version: 1.14.4 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.7.7), IRanges (>= 1.20.3), XVector (>= 0.1.3) Imports: methods, utils, stats, BiocGenerics, IRanges LinkingTo: IRanges, XVector Suggests: AnnotationDbi (>= 1.21.1), AnnotationHub, BSgenome, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Scerevisiae.UCSC.sacCer2, BSgenome.Dmelanogaster.UCSC.dm3, Biostrings (>= 2.25.3), Rsamtools (>= 1.13.53), rtracklayer, KEGG.db, KEGGgraph, GenomicFeatures, TxDb.Dmelanogaster.UCSC.dm3.ensGene, TxDb.Hsapiens.UCSC.hg19.knownGene, seqnames.db, org.Sc.sgd.db, VariantAnnotation, edgeR, DESeq, DEXSeq, pasilla, pasillaBamSubset, RUnit, digest, BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: 6ce463569f7336a98e7e6f735a82284f NeedsCompilation: yes Title: Representation and manipulation of genomic intervals Description: The ability to efficiently store 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 as well as more specialized containers for storing alignments against a reference genome. biocViews: Genetics, Sequencing, HighThroughputSequencing, Annotation Author: P. Aboyoun, H. Pages and M. Lawrence Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GenomicRanges_1.14.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/GenomicRanges_1.14.4.zip win64.binary.ver: bin/windows64/contrib/3.0/GenomicRanges_1.14.4.zip mac.binary.ver: bin/macosx/contrib/3.0/GenomicRanges_1.14.4.tgz vignettes: vignettes/GenomicRanges/inst/doc/GenomicRangesHOWTOs.pdf, vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.pdf, vignettes/GenomicRanges/inst/doc/OverlapEncodings.pdf, vignettes/GenomicRanges/inst/doc/summarizeOverlaps-modes.pdf, vignettes/GenomicRanges/inst/doc/summarizeOverlaps.pdf vignetteTitles: GenomicRanges HOWTOs, An Introduction to GenomicRanges, Overlap encodings, summarizeOverlaps-modes.pdf, Counting reads with summarizeOverlaps 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, baySeq, biomvRCNS, BiSeq, BSgenome, bsseq, bumphunter, casper, chimera, chipseq, cleanUpdTSeq, cn.mops, CSAR, DASiR, deepSNV, DESeq2, DiffBind, easyRNASeq, ensemblVEP, epigenomix, epivizr, exomeCopy, fastseg, genomes, GenomicFeatures, genoset, GGtools, gmapR, gwascat, HiTC, htSeqTools, intansv, methyAnalysis, minfi, PING, QuasR, Rcade, rfPred, RIPSeeker, Rsamtools, rSFFreader, RSVSim, rtracklayer, segmentSeq, seqbias, ShortRead, SigFuge, SomatiCA, SplicingGraphs, VariantAnnotation, VariantTools, vtpnet importsMe: AnnotationHub, ArrayExpressHTS, biovizBase, BiSeq, CAGEr, CexoR, chipenrich, chipseq, ChIPseqR, copynumber, customProDB, DEXSeq, DNaseR, epigenomix, flipflop, FunciSNP, GenomicFeatures, genoset, ggbio, gmapR, Gviz, h5vc, HTSeqGenie, HTSFilter, interactiveDisplay, lumi, MEDIPS, methyAnalysis, MethylSeekR, MinimumDistance, NarrowPeaks, nucleR, oligoClasses, PICS, prebs, QuasR, Repitools, rnaSeqMap, rSFFreader, rtracklayer, segmentSeq, SeqArray, SeqVarTools, SNPchip, SomatiCA, spliceR, SplicingGraphs, triplex, VanillaICE, VariantTools, waveTiling suggestsMe: BiocGenerics, IRanges, methylumi, MiRaGE, NarrowPeaks Package: Genominator Version: 1.16.0 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: a233a7dd952b5f2de67b42f6649f2c4d 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Genominator_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Genominator_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Genominator_1.16.0.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: 1.14.0 Depends: R (>= 2.10), BiocGenerics (>= 0.1.6), Biobase (>= 2.15.1), IRanges, GenomicRanges Imports: methods, graphics, IRanges, GenomicRanges Suggests: RUnit, DNAcopy, stats, BSgenome, Biostrings Enhances: parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: b5a0ffdd062d3925237dbb60fe08856d 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, CopyNumberVariants Author: Peter M. Haverty Maintainer: Peter M. Haverty source.ver: src/contrib/genoset_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/genoset_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/genoset_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/genoset_1.14.0.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: 1.22.0 Depends: GEOquery,RSQLite License: Artistic-2.0 MD5sum: 91a03ea98d04623f0e5c53f27d4dd8c1 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GEOmetadb_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GEOmetadb_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GEOmetadb_1.22.0.tgz vignettes: vignettes/GEOmetadb/inst/doc/GEOmetadb_diagram.pdf, vignettes/GEOmetadb/inst/doc/GEOmetadb.pdf vignetteTitles: GEOmetadb_diagram.pdf, GEOmetadb hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GEOmetadb/inst/doc/GEOmetadb.R Package: GEOquery Version: 2.28.0 Depends: methods, Biobase Imports: XML, RCurl Suggests: limma, RUnit License: GPL-2 MD5sum: 51bd3eb1003cd08d5b0c70a9c02a747d 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: http://watson.nci.nih.gov/~sdavis source.ver: src/contrib/GEOquery_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GEOquery_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GEOquery_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GEOquery_2.28.0.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, PGSEA, TargetScore Package: GEOsubmission Version: 1.14.0 Imports: affy, Biobase, utils License: GPL (>= 2) MD5sum: 6d465073b490d9fcbb4df8be9ae07b16 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GEOsubmission_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GEOsubmission_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GEOsubmission_1.14.0.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: 1.6.0 Depends: R (>= 2.10), car License: GPL-2 MD5sum: 152af878a10405a1f8bcfbdefb3e2049 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: Bioinformatics, MultipleComparisons, BiologicalDomains, Genetics Author: Wei Q. Deng, Guillaume Pare Maintainer: Wei Q. Deng source.ver: src/contrib/GEWIST_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GEWIST_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GEWIST_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GEWIST_1.6.0.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: 3.24.0 Depends: R (>= 2.14), methods, snpStats Imports: limma, genefilter, Biobase, BiocGenerics, Matrix, AnnotationDbi License: Artistic-2.0 MD5sum: 85adceb9bc1212143f96b28fa71001dd 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_3.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GGBase_3.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GGBase_3.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GGBase_3.24.0.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: 1.10.16 Depends: methods, ggplot2 (>= 0.9.3) Imports: methods, biovizBase(>= 1.10.5), reshape2, gtable, ggplot2(>= 0.9.2), lattice, BiocGenerics, Biobase, IRanges, GenomicRanges (>= 1.13.3), GenomicFeatures, Rsamtools (>= 1.13.1), BSgenome, gridExtra, scales, plyr, VariantAnnotation, Hmisc, rtracklayer Suggests: vsn, RUnit, testthat, BSgenome.Hsapiens.UCSC.hg19, TxDb.Hsapiens.UCSC.hg19.knownGene, affyPLM, chipseq, TxDb.Mmusculus.UCSC.mm9.knownGene, knitr License: Artistic-2.0 MD5sum: 36be24ee783a295b05aa3325d70068c4 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, Bioinformatics Author: Tengfei Yin, Dianne Cook, Michael Lawrence Maintainer: Tengfei Yin URL: http://tengfei.github.com/ggbio/ source.ver: src/contrib/ggbio_1.10.16.tar.gz win.binary.ver: bin/windows/contrib/3.0/ggbio_1.10.16.zip win64.binary.ver: bin/windows64/contrib/3.0/ggbio_1.10.16.zip mac.binary.ver: bin/macosx/contrib/3.0/ggbio_1.10.16.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: intansv importsMe: ReportingTools suggestsMe: gwascat, ReportingTools Package: GGtools Version: 4.10.0 Depends: R (>= 2.14), stats4, GGBase (>= 3.19.7), IRanges, GenomicRanges, Rsamtools Imports: methods, utils, stats, BiocGenerics, snpStats, ff, AnnotationDbi, Biobase, bit, VariantAnnotation Suggests: GGdata, illuminaHumanv1.db, SNPlocs.Hsapiens.dbSNP.20120608 Enhances: MatrixEQTL License: Artistic-2.0 MD5sum: 64a7f7af6b00f8f680a748f97b10e055 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_4.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GGtools_4.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GGtools_4.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GGtools_4.10.0.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_2012.R, vignettes/GGtools/inst/doc/GGtools.R Package: girafe Version: 1.14.0 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: 47646e25cdce2e575ed4c1b9245b932b 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, HighThroughputSequencing 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/girafe_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/girafe_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/girafe_1.14.0.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: 2.26.0 Depends: R (>= 2.10) Suggests: aws, tcltk License: GPL-2 Archs: i386, x64 MD5sum: 46d601622f6b03e752a4dd883e04cab6 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, CopyNumberVariants 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_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GLAD_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GLAD_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GLAD_2.26.0.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: 3.30.0 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: 5151b4f33283ecdf5aa994f8fd98a93e 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, Bioinformatics, DifferentialExpression, Pathways Author: U. Mansmann, R. Meister, M. Hummel, R. Scheufele, with contributions from S. Knueppel Maintainer: Manuela Hummel source.ver: src/contrib/GlobalAncova_3.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GlobalAncova_3.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GlobalAncova_3.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GlobalAncova_3.30.0.tgz vignettes: vignettes/GlobalAncova/inst/doc/GlobalAncova.pdf, vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.pdf vignetteTitles: GlobalAncova.pdf, GlobalAncovaDecomp.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GlobalAncova/inst/doc/GlobalAncova.R, vignettes/GlobalAncova/inst/doc/GlobalAncovaDecomp.R Package: globaltest Version: 5.16.0 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: e85273c688c059e774826f9ab5c4458c 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, Bioinformatics, 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_5.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/globaltest_5.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/globaltest_5.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/globaltest_5.16.0.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: 1.4.3 Depends: R (>= 2.15.0), methods, GenomicRanges Imports: IRanges, Rsamtools (>= 1.7.4), rtracklayer (>= 1.17.15), GenomicRanges, GenomicFeatures, Biostrings, VariantAnnotation (>= 1.7.34), tools, Biobase, BSgenome, methods Suggests: RUnit, BSgenome.Dmelanogaster.UCSC.dm3, BSgenome.Scerevisiae.UCSC.sacCer3, VariantAnnotation, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, BSgenome.Hsapiens.UCSC.hg19, LungCancerLines License: Artistic-2.0 MD5sum: 9fa83a6c83e48e30f551827fedb6b2b9 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. Author: Cory Barr, Thomas Wu, Michael Lawrence Maintainer: Michael Lawrence source.ver: src/contrib/gmapR_1.4.3.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: 1.10.0 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: abe8bcf279d612d8d6ca44b7441690a7 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GOFunction_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GOFunction_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GOFunction_1.10.0.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: 1.24.0 Depends: Biobase, AnnotationDbi, GO.db Suggests: org.Hs.eg.db License: GPL-2 MD5sum: fe693104678ae45aed1ac04d3d61296c 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/goProfiles_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/goProfiles_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/goProfiles_1.24.0.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: 1.20.3 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: f66075c66f5a5e596ea531172c4e6541 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, NetworkAnalysis Author: Guangchuang Yu Maintainer: Guangchuang Yu URL: http://bioinformatics.oxfordjournals.org/content/26/7/976.full VignetteBuilder: knitr source.ver: src/contrib/GOSemSim_1.20.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/GOSemSim_1.20.3.zip win64.binary.ver: bin/windows64/contrib/3.0/GOSemSim_1.20.3.zip mac.binary.ver: bin/macosx/contrib/3.0/GOSemSim_1.20.3.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 suggestsMe: ReactomePA Package: goseq Version: 1.14.0 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: 98c1aa4f627fd8b1abeb0ee6b0d73645 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: HighThroughputSequencingData, GO, GeneExpression, Transcription, RNAseq Author: Matthew Young Maintainer: Matthew Young , Nadia Davidson source.ver: src/contrib/goseq_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/goseq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/goseq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/goseq_1.14.0.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: 1.4.2 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: cc3aefb393d565fb83068aeb3755ea7c 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, NetworkAnalysis Author: Holger Froehlich Maintainer: Holger Froehlich source.ver: src/contrib/GOSim_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/GOSim_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/GOSim_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/GOSim_1.4.2.tgz vignettes: vignettes/GOSim/inst/doc/GOClusterExample.pdf, vignettes/GOSim/inst/doc/GOClustersil.pdf, vignettes/GOSim/inst/doc/GOExample.pdf, vignettes/GOSim/inst/doc/GOPCAExample.pdf, vignettes/GOSim/inst/doc/GOSim.pdf vignetteTitles: GOClusterExample.pdf, GOClustersil.pdf, GOExample.pdf, GOPCAExample.pdf, GOsim hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/GOSim/inst/doc/GOSim.R Package: GOstats Version: 2.28.0 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: 666c85c98404d7476004cfa19c5e4339 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: Bioinformatics, Annotation, GO, MultipleComparisons Author: R. Gentleman and S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GOstats_2.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GOstats_2.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GOstats_2.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GOstats_2.28.0.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, GSEAlm, HTSanalyzeR, MineICA, MLP, MmPalateMiRNA, oneChannelGUI, phenoDist, safe Package: goTools Version: 1.36.0 Depends: GO.db Imports: AnnotationDbi, GO.db, graphics, grDevices Suggests: hgu133a.db License: GPL-2 MD5sum: 22b61d91fe3282de365bf8be26d66faf 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/goTools_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/goTools_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/goTools_1.36.0.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: 1.34.0 Imports: stats Suggests: MASS License: Artistic-2.0 MD5sum: 15d07026741b6d4ca3b38df69e4b87f5 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: Bioinformatics, Classification, Microarray Author: Beiying Ding Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/gpls_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gpls_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gpls_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gpls_1.34.0.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: 1.6.0 Depends: R (>= 2.8.0), gptk Suggests: spam License: AGPL-3 MD5sum: ba0a5e3e6e09a8fc3252788957dbec35 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, Bioinformatics, DifferentialExpression, TimeCourse Author: Alfredo Kalaitzis Maintainer: Alfredo Kalaitzis source.ver: src/contrib/gprege_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gprege_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gprege_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gprege_1.6.0.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: 1.40.1 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: f40d6577e1e6bc1209158722284c660f NeedsCompilation: yes Title: graph: A package to handle graph data structures Description: A package that implements some simple graph handling capabilities. biocViews: GraphsAndNetworks Author: R. Gentleman, Elizabeth Whalen, W. Huber, S. Falcon Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/graph_1.40.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/graph_1.40.1.zip win64.binary.ver: bin/windows64/contrib/3.0/graph_1.40.1.zip mac.binary.ver: bin/macosx/contrib/3.0/graph_1.40.1.tgz vignettes: vignettes/graph/inst/doc/clusterGraph.pdf, vignettes/graph/inst/doc/graph.pdf, vignettes/graph/inst/doc/graphAttributes.pdf, vignettes/graph/inst/doc/GraphClass.pdf, vignettes/graph/inst/doc/MultiGraphClass.pdf vignetteTitles: clusterGraph and distGraph, Graph, Attributes for Graph Objects, Graph Design, graphBAM and MultiGraph classes hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/graph/inst/doc/clusterGraph.R, vignettes/graph/inst/doc/graph.R, vignettes/graph/inst/doc/graphAttributes.R, vignettes/graph/inst/doc/GraphClass.R, vignettes/graph/inst/doc/MultiGraphClass.R dependsOnMe: apComplex, biocGraph, BioMVCClass, BioNet, CellNOptR, clipper, CNORfeeder, ddgraph, flowClust, gaggle, GeneNetworkBuilder, GOFunction, GOstats, GraphAT, GSEABase, gwascat, hyperdraw, hypergraph, KEGGgraph, maigesPack, MineICA, NCIgraph, nem, netresponse, NetSAM, pathRender, pkgDepTools, RbcBook1, RBGL, RBioinf, RCytoscape, RDAVIDWebService, Rgraphviz, ROntoTools, RpsiXML, Rtreemix, SRAdb, topGO, vtpnet importsMe: biocGraph, biocViews, CAMERA, Category, categoryCompare, DEGraph, flowCore, flowUtils, flowWorkspace, gage, GeneNetworkBuilder, GOFunction, GOSim, GOstats, GraphAT, graphite, HTSanalyzeR, KEGGgraph, keggorthology, NCIgraph, nem, OrganismDbi, pathview, PCpheno, pkgDepTools, ppiStats, qpgraph, RchyOptimyx, rsbml, Rtreemix, SplicingGraphs, Streamer, topGO suggestsMe: AnnotationDbi, BiocCaseStudies, Category, DEGraph, EBcoexpress, ecolitk, GeneAnswers, MmPalateMiRNA, rBiopaxParser, rTRM, SPIA Package: GraphAlignment Version: 1.26.0 License: file LICENSE License_restricts_use: yes Archs: i386, x64 MD5sum: 004ecbc70225708d9ed35693c3646783 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: GraphsAndNetworks, NetworkAnalysis 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GraphAlignment_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GraphAlignment_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GraphAlignment_1.26.0.tgz vignettes: vignettes/GraphAlignment/inst/doc/a.pdf, vignettes/GraphAlignment/inst/doc/align_principle_short1.pdf, vignettes/GraphAlignment/inst/doc/align_principle2b1.pdf, vignettes/GraphAlignment/inst/doc/align_principle2c1.pdf, vignettes/GraphAlignment/inst/doc/binning-01a.pdf, vignettes/GraphAlignment/inst/doc/GraphAlignment.pdf vignetteTitles: a.pdf, align_principle_short1.pdf, align_principle2b1.pdf, align_principle2c1.pdf, binning-01a.pdf, GraphAlignment hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/GraphAlignment/inst/doc/GraphAlignment.R Package: GraphAT Version: 1.34.0 Depends: R (>= 2.10), graph, methods Imports: graph, MCMCpack, methods, stats License: LGPL MD5sum: a4295194518ee954a1d762467ec0a40f NeedsCompilation: no Title: Graph Theoretic Association Tests Description: Functions and data used in Balasubramanian, et al. (2004) biocViews: NetworkAnalysis, GraphsAndNetworks Author: R. Balasubramanian, T. LaFramboise, D. Scholtens Maintainer: Thomas LaFramboise source.ver: src/contrib/GraphAT_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GraphAT_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GraphAT_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GraphAT_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: graphite Version: 1.8.1 Depends: R (>= 2.10) Imports: AnnotationDbi, graph, graphics, methods, org.Hs.eg.db, stats, utils Suggests: DEGraph (>= 1.4), hgu133plus2.db, RCytoscape (>= 1.6), SPIA (>= 2.2), topologyGSA (>= 1.0), clipper, ALL License: AGPL-3 MD5sum: 73d8257c5db640526a90d162a9f7826e NeedsCompilation: no Title: GRAPH Interaction from pathway Topological Environment Description: Graph objects from pathway topology derived from Biocarta, KEGG, NCI, Reactome and SPIKE databases. biocViews: Pathways, ConnectTools, GraphsAndNetworks Author: Gabriele Sales , Enrica Calura , Chiara Romualdi Maintainer: Gabriele Sales source.ver: src/contrib/graphite_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/graphite_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/graphite_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/graphite_1.8.1.tgz vignettes: vignettes/graphite/inst/doc/graphite.pdf vignetteTitles: GRAPH Interaction from pathway Topological Environment hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/graphite/inst/doc/graphite.R importsMe: ReactomePA suggestsMe: clipper Package: GraphPAC Version: 1.4.0 Depends: R(>= 2.15),iPAC, igraph, TSP, RMallow Suggests: RUnit, BiocGenerics License: GPL-2 MD5sum: cde4f35c400fe9ea16c934b0cf55751f 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: Bioinformatics, Clustering, BiologicalDomains, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/GraphPAC_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GraphPAC_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GraphPAC_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GraphPAC_1.4.0.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: 1.14.1 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: 6828c7bc8ddae1282ba3beb950996949 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, GraphsAndNetworks Author: Edward Morrissey Maintainer: Edward Morrissey source.ver: src/contrib/GRENITS_1.14.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/GRENITS_1.14.1.zip win64.binary.ver: bin/windows64/contrib/3.0/GRENITS_1.14.1.zip mac.binary.ver: bin/macosx/contrib/3.0/GRENITS_1.14.1.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: GSEABase Version: 1.24.0 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: f5df90f2e665c1b2281edfbffe0be8d4 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, Bioinformatics Author: Martin Morgan, Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/GSEABase_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GSEABase_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GSEABase_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GSEABase_1.24.0.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, PROMISE importsMe: Category, categoryCompare, cellHTS2, gCMAPWeb, GSRI, GSVA, HTSanalyzeR, PCpheno, phenoTest, PROMISE, ReportingTools suggestsMe: BiocCaseStudies, gage, GlobalAncova, globaltest, GOstats, PGSEA, phenoTest Package: GSEAlm Version: 1.22.0 Depends: Biobase Suggests: GSEABase,Category, multtest, ALL, annotate, hgu95av2.db, genefilter, GOstats, RColorBrewer License: Artistic-2.0 MD5sum: b94a3959fc8fb81693ad1b0d7200bf72 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, Bioinformatics Author: Assaf Oron, Robert Gentleman (with contributions from S. Falcon and Z. Jiang) Maintainer: Assaf Oron source.ver: src/contrib/GSEAlm_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GSEAlm_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GSEAlm_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GSEAlm_1.22.0.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: 2.10.0 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: 8c46461ba496dfc1a8ae2fd6dc413cc6 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, Genetics, Bioinformatics Author: Julian Gehring, Kilian Bartholome, Clemens Kreutz, Jens Timmer Maintainer: Julian Gehring URL: http://julian-gehring.github.com/GSRI/ source.ver: src/contrib/GSRI_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/GSRI_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/GSRI_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/GSRI_2.10.0.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: 1.10.3 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: a7654267bf2ac22429543520e42e4a80 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_1.10.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/GSVA_1.10.3.zip win64.binary.ver: bin/windows64/contrib/3.0/GSVA_1.10.3.zip mac.binary.ver: bin/macosx/contrib/3.0/GSVA_1.10.3.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: 1.6.0 Depends: R (>= 2.10.0), methods, grid 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), BiocGenerics (>= 0.1.4), GenomicFeatures (>= 1.9.7), BSgenome (>= 1.25.1), Biostrings (>= 2.25.1), biovizBase (>= 1.5.7), Rsamtools(>= 1.11.1), latticeExtra(>= 0.6-26) Suggests: xtable, GenomicFeatures, BSgenome.Hsapiens.UCSC.hg19, biomaRt, rtracklayer License: Artistic-2.0 MD5sum: 0bcff07c6791c32fce881bc3991ff0f7 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 Maintainer: Florian Hahne source.ver: src/contrib/Gviz_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Gviz_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Gviz_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Gviz_1.6.0.tgz vignettes: vignettes/Gviz/inst/doc/Gviz.pdf, vignettes/Gviz/inst/doc/ucsc1.pdf, vignettes/Gviz/inst/doc/ucsc2.pdf vignetteTitles: Gviz users guide, ucsc1.pdf, ucsc2.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Gviz/inst/doc/Gviz.R dependsOnMe: biomvRCNS, cummeRbund importsMe: interactiveDisplay, methyAnalysis, PING suggestsMe: gwascat, QuasR, SplicingGraphs Package: gwascat Version: 1.6.0 Depends: R (>= 2.14.0), methods, IRanges, GenomicRanges, snpStats, graph, BiocGenerics Imports: Biostrings Suggests: DO.db, Gviz, ggbio, rtracklayer Enhances: SNPlocs.Hsapiens.dbSNP.20111119, pd.genomewidesnp.6 License: Artistic-2.0 MD5sum: b081f2e226f531a5f552ff6e50bbc7cc 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/gwascat_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/gwascat_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/gwascat_1.6.0.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 Package: GWASTools Version: 1.8.1 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: 5458669819fc3063bf78571c6c7ffc34 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_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/GWASTools_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/GWASTools_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/GWASTools_1.8.1.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: 1.0.6 Imports: rhdf5, ggplot2, reshape, bit64, IRanges, GenomicRanges, Biostrings Suggests: knitr, locfit, deepSNV, BSgenome.Hsapiens.UCSC.hg19, h5vcData License: GPL (>= 3) MD5sum: e7881bb04aa437c628f6d6707a242d5e NeedsCompilation: no 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_1.0.6.tar.gz win.binary.ver: bin/windows/contrib/3.0/h5vc_1.0.6.zip win64.binary.ver: bin/windows64/contrib/3.0/h5vc_1.0.6.zip mac.binary.ver: bin/macosx/contrib/3.0/h5vc_1.0.6.tgz vignettes: vignettes/h5vc/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/h5vc/inst/doc/h5vc.advanced.analyses.R, vignettes/h5vc/inst/doc/h5vc.creating.tallies.within.R.R, vignettes/h5vc/inst/doc/h5vc.R, vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.R htmlDocs: vignettes/h5vc/inst/doc/h5vc.advanced.analyses.html, vignettes/h5vc/inst/doc/h5vc.creating.tallies.html, vignettes/h5vc/inst/doc/h5vc.creating.tallies.within.R.html, vignettes/h5vc/inst/doc/h5vc.html, vignettes/h5vc/inst/doc/h5vc.simple.genome.browser.html htmlTitles: "Advanced analyses", "Creating Tallies with h5py/Python", "Creating Tallies within R", "Scalable nucleotide tallies with HDF5", "Building a minimal genome browser with h5vc and shiny" Package: hapFabia Version: 1.4.2 Depends: R (>= 2.12.0), Biobase, fabia (>= 2.3.1) Imports: methods, graphics, grDevices, stats, utils, KernSmooth License: LGPL (>= 2.1) Archs: i386, x64 MD5sum: 8a9cdb8e984624340ddd922abd6b1092 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, HighThroughputSequencing, 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_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/hapFabia_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/hapFabia_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/hapFabia_1.4.2.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: 1.34.0 Depends: R (>= 2.10) Imports: affy, altcdfenvs, Biobase, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 2c3dfadca0557774f8d4eee7de8cb759 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, AffymetrixChip, 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Harshlight_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Harshlight_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Harshlight_1.34.0.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: 1.2.0 Depends: R(>= 2.10.0), survival, coin, fpc, clusterRepro, impute, randomForestSRC, sm, sigaR, Biobase License: GPL (>= 2) MD5sum: 91c1edb87d7853f2e62cf2a471abb893 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, Bioinformatics, aCGH, GeneExpression, Clustering Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/HCsnip_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HCsnip_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HCsnip_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HCsnip_1.2.0.tgz vignettes: vignettes/HCsnip/inst/doc/densityR.pdf, vignettes/HCsnip/inst/doc/entropy.pdf, vignettes/HCsnip/inst/doc/HCsnip.pdf, vignettes/HCsnip/inst/doc/Rank.pdf vignetteTitles: densityR.pdf, entropy.pdf, HCsnip, Rank.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HCsnip/inst/doc/HCsnip.R Package: Heatplus Version: 2.8.0 Imports: graphics, grDevices, stats Suggests: Biobase, hgu95av2.db, limma License: GPL (>= 2) MD5sum: 1008ae5836fed78a7c286a2b722079c7 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_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Heatplus_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Heatplus_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Heatplus_2.8.0.tgz vignettes: vignettes/Heatplus/inst/doc/annHeatmap.pdf, vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.pdf, vignettes/Heatplus/inst/doc/oldHeatplus.pdf vignetteTitles: Annotated and regular heatmaps, Commented package source, Old functions (deprecated) hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Heatplus/inst/doc/annHeatmap.R, vignettes/Heatplus/inst/doc/annHeatmapCommentedSource.R, vignettes/Heatplus/inst/doc/oldHeatplus.R dependsOnMe: GeneAnswers, phenoTest, tRanslatome Package: HELP Version: 1.20.0 Depends: R (>= 2.8.0), stats, graphics, grDevices, Biobase, methods License: GPL (>= 2) MD5sum: c1e99ce8047480558b7136f5f1d6d179 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HELP_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HELP_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HELP_1.20.0.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: 1.34.0 Depends: R (>= 2.1.0) Imports: Biobase, grDevices, stats, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: 771734e2ff45028da69bb756893b66cb 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, Bioinformatics 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HEM_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HEM_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HEM_1.34.0.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: 1.20.0 Depends: R (>= 2.6.0), grid, lattice Suggests: IRanges, EBImage License: GPL (>= 3) Archs: i386, x64 MD5sum: dde69cd4cfcac618cfbe7faba6d01d3a 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HilbertVis_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HilbertVis_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HilbertVis_1.20.0.tgz vignettes: vignettes/HilbertVis/inst/doc/HilbertDisplay_GUI.pdf, vignettes/HilbertVis/inst/doc/HilbertVis.pdf, vignettes/HilbertVis/inst/doc/ThreeChTest.pdf vignetteTitles: HilbertDisplay_GUI.pdf, Visualising very long data vectors with the Hilbert curve, ThreeChTest.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/HilbertVis/inst/doc/HilbertVis.R dependsOnMe: HilbertVisGUI importsMe: ChIPseqR Package: HilbertVisGUI Version: 1.20.0 Depends: R (>= 2.6.0), HilbertVis (>= 1.1.6) Suggests: lattice, IRanges License: GPL (>= 3) Archs: i386, x64 MD5sum: e2504157af791db8ed17f965906201f3 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HilbertVisGUI_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HilbertVisGUI_1.20.0.zip 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: 1.6.0 Depends: R (>= 2.15.0), methods, GenomicRanges, IRanges, Matrix, RColorBrewer Imports: methods, Biobase, Biostrings, graphics, grDevices, rtracklayer Suggests: rtracklayer,BiocStyle License: Artistic-2.0 MD5sum: fed0a676518af395187600065ff6becd 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HiTC_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HiTC_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HiTC_1.6.0.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: 1.4.0 Depends: R (>= 2.10.0), IRanges (>= 1.4.16), geneplotter (>= 1.24.0) License: GPL-3 Archs: i386, x64 MD5sum: 4e90a70ef51040c113a50205236e8f39 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, CopyNumberVariants, HighThroughputSequencing, Microarray Author: Daniel Lai, Gavin Ha, Sohrab Shah Maintainer: Daniel Lai , Gavin Ha , Sohrab Shah source.ver: src/contrib/HMMcopy_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HMMcopy_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HMMcopy_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HMMcopy_1.4.0.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 Package: hopach Version: 2.22.0 Depends: R (>= 2.11.0), cluster, Biobase, methods Imports: Biobase, cluster, graphics, grDevices, methods, stats, utils, BiocGenerics License: GPL (>= 2) Archs: i386, x64 MD5sum: 473f591ceb9c818a461ac2eba59c6e9c 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_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/hopach_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/hopach_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/hopach_2.22.0.tgz vignettes: vignettes/hopach/inst/doc/bootplot.pdf, vignettes/hopach/inst/doc/dplot.pdf, vignettes/hopach/inst/doc/hopach.pdf, vignettes/hopach/inst/doc/hopachManuscript.pdf, vignettes/hopach/inst/doc/MSS.pdf vignetteTitles: bootplot.pdf, dplot.pdf, hopach, hopachManuscript.pdf, MSS.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/hopach/inst/doc/hopach.R importsMe: phenoTest suggestsMe: BiocCaseStudies Package: hpar Version: 1.4.0 Depends: R (>= 2.15) Suggests: org.Hs.eg.db, GO.db, knitr License: Artistic-2.0 MD5sum: 3befafae0cf93b4f9f1d9248a1f32a80 NeedsCompilation: no Title: Human Protein Atlas in R Description: A simple interface to and data from the Human Protein Atlas project. biocViews: Bioinformatics, Proteomics, Homo_sapiens, CellBiology Author: Laurent Gatto Maintainer: Laurent Gatto source.ver: src/contrib/hpar_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/hpar_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/hpar_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/hpar_1.4.0.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: 1.16.0 Depends: Biobase, RColorBrewer, limma Imports: affy, Biobase, gplots, graphics, grDevices, limma, methods, RColorBrewer, stats, stats4, utils Suggests: statmod License: Artistic-2.0 MD5sum: 335ebc98c793eaba1ba8d2aab8a77e00 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, Bioinformatics, Visualization, MultipleComparisons, qPCR Author: Heidi Dvinge, Paul Bertone Maintainer: Heidi Dvinge URL: http://www.ebi.ac.uk/bertone/software source.ver: src/contrib/HTqPCR_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HTqPCR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HTqPCR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HTqPCR_1.16.0.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 Package: HTSanalyzeR Version: 2.14.0 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: 0858952be67ee531b3bc3412dbd3c85f 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, Bioinformatics, MultipleComparisons Author: Xin Wang , Camille Terfve , John C. Rose , Florian Markowetz Maintainer: Xin Wang source.ver: src/contrib/HTSanalyzeR_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HTSanalyzeR_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HTSanalyzeR_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HTSanalyzeR_2.14.0.tgz vignettes: vignettes/HTSanalyzeR/inst/doc/Figure.pdf, vignettes/HTSanalyzeR/inst/doc/HTSanalyzeR-Vignette.pdf vignetteTitles: Figure.pdf, 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: 3.12.0 Depends: R (>= 3.0.0), ShortRead (>= 1.14.4), parallel, BiocParallel, hwriter, Cairo, tools, rtracklayer, gmapR (>= 1.1.10) 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), rtracklayer (>= 1.17.19), GenomicFeatures (>= 1.9.31), VariantTools (>= 1.3.6), VariantAnnotation (>= 1.5.41) Suggests: TxDb.Hsapiens.UCSC.hg19.knownGene, GenomicFeatures, LungCancerLines, org.Hs.eg.db License: Artistic-2.0 MD5sum: f753dae4845be7ad634ab20a54cff03a NeedsCompilation: no Title: A NGS analysis pipeline. Description: Libraries to perform NGS analysis. Author: Gregoire Pau, Jens Reeder Maintainer: Gregoire Pau source.ver: src/contrib/HTSeqGenie_3.12.0.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: 1.8.0 Depends: R (>= 2.12.2), methods, BiocGenerics (>= 0.1.0), Biobase, IRanges, methods, MASS, BSgenome, GenomicRanges Enhances: multicore License: GPL (>=2) MD5sum: 4a81999d2917430b1365b0852eaf2f23 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: HighThroughputSequencing,QualityControl Author: Evarist Planet, Camille Stephan-Otto, Oscar Reina, Oscar Flores, David Rossell Maintainer: Oscar Reina source.ver: src/contrib/htSeqTools_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/htSeqTools_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/htSeqTools_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/htSeqTools_1.8.0.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: 1.2.1 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: 133f501e252c40081a3c2bd9e2c80937 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: HighThroughputSequencing, RNAseq, Preprocessing, DifferentialExpression Author: Andrea Rau, Melina Gallopin, Gilles Celeux, and Florence Jaffrezic Maintainer: Andrea Rau source.ver: src/contrib/HTSFilter_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/HTSFilter_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/HTSFilter_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/HTSFilter_1.2.1.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: 1.6.0 Depends: R (>= 2.9.0), Biobase, fdrtool, MASS, survival Imports: stats License: GPL Version 2 or later MD5sum: 230472846bc9c471e253f5542182318a 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, Bioinformatics, Microarray Author: Stan Pounds , Demba Fofana Maintainer: Demba Fofana source.ver: src/contrib/HybridMTest_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/HybridMTest_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/HybridMTest_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/HybridMTest_1.6.0.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: 1.14.0 Depends: R (>= 2.9.0), methods, grid, graph, hypergraph, Rgraphviz Imports: stats4 License: GPL (>= 2) MD5sum: 5ba082f9a2e7a686d7c93c25f02e6358 NeedsCompilation: no Title: Visualizing Hypergaphs Description: Functions for visualizing hypergraphs. biocViews: NetworkVisualization, GraphsAndNetworks Author: Paul Murrell Maintainer: Paul Murrell SystemRequirements: graphviz source.ver: src/contrib/hyperdraw_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/hyperdraw_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/hyperdraw_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/hyperdraw_1.14.0.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: 1.34.0 Depends: R (>= 2.1.0), methods, graph License: Artistic-2.0 MD5sum: 87eb072cdc797b50555829399a2bdf2f NeedsCompilation: no Title: A package providing hypergraph data structures Description: A package that implements some simple capabilities for representing and manipulating hypergraphs. biocViews: GraphsAndNetworks Author: Seth Falcon, Robert Gentleman Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/hypergraph_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/hypergraph_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/hypergraph_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/hypergraph_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: altcdfenvs, hyperdraw, RpsiXML importsMe: BiGGR Package: iASeq Version: 1.6.0 Depends: R (>= 2.14.1) Imports: graphics, grDevices License: GPL-2 MD5sum: 16097d6fba099ceb15739d6caf41fc77 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, Bioinformatics Author: Yingying Wei, Hongkai Ji Maintainer: Yingying Wei source.ver: src/contrib/iASeq_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iASeq_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iASeq_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iASeq_1.6.0.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: 1.6.0 Depends: biclust Imports: stats4,xtable,ade4 Suggests: methods License: Artistic-2.0 Archs: i386, x64 MD5sum: dfd8d97c2916218ece83c45b4c87dcfe 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iBBiG_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iBBiG_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iBBiG_1.6.0.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: 1.10.0 Depends: simpIntLists Suggests: yeastCC, stats License: GPL (>= 2) MD5sum: 83daafab5527c484f586cff6193b7ce6 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, GraphsAndNetworks, NetworkEnrichment Author: Kircicegi Korkmaz, Volkan Atalay, Rengul Cetin Atalay. Maintainer: Kircicegi Korkmaz source.ver: src/contrib/ibh_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ibh_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ibh_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ibh_1.10.0.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: 1.2.0 Depends: R(>= 2.15.0),Biobase (>= 2.16.0), ggplot2 (>= 0.9.2) License: Artistic-2.0 Archs: i386, x64 MD5sum: 07725a229350032a83c58650d4f068d0 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: Marie-Pier Scott-Boyer URL: http://www.rglab.org SystemRequirements: GSL and OpenMP source.ver: src/contrib/iBMQ_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iBMQ_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iBMQ_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iBMQ_1.2.0.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: 1.34.0 Depends: survival Imports: graphics License: Artistic-2.0 MD5sum: f43ac0c84159ae0887d00712a312cf42 NeedsCompilation: no Title: NPMLE for Censored and Truncated Data Description: Many functions for computing the NPMLE for censored and truncated data. biocViews: Bioinformatics, Infrastructure Author: R. Gentleman and Alain Vandal Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/Icens_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Icens_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Icens_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Icens_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: PROcess importsMe: PROcess Package: iChip Version: 1.16.0 Depends: R (>= 2.10.0) Imports: limma License: GPL (>= 2) Archs: i386, x64 MD5sum: 2be2f2d2c7832014c839f82acde2e778 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, Affymetrix, Agilent,Microarray, Bioinformatics Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iChip_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iChip_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iChip_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iChip_1.16.0.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: idiogram Version: 1.38.0 Depends: R (>= 2.10), methods, Biobase, annotate, plotrix Suggests: hu6800.db, hgu95av2.db, golubEsets License: GPL-2 MD5sum: 37f7215dd9a514fab1257e74bd85182e 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/idiogram_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/idiogram_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/idiogram_1.38.0.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: 1.6.0 Depends: R (>= 2.14), R.oo (>= 1.13.0), rChoiceDialogs Imports: boot, mclust, RColorBrewer, Biobase License: GPL-2 MD5sum: 0bff1a0c15ae95c0bb7b5e8bacfa13ce NeedsCompilation: no Title: ID Mapping Analysis Description: Identifier mapping performance analysis biocViews: Bioinformatics, Annotation, MultipleComparisons Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingAnalysis_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/IdMappingAnalysis_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/IdMappingAnalysis_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/IdMappingAnalysis_1.6.0.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: 1.8.0 Depends: R.oo, XML, RCurl, rChoiceDialogs, ENVISIONQuery Imports: biomaRt, ENVISIONQuery, DAVIDQuery, AffyCompatible, R.methodsS3, R.oo, utils License: GPL-2 MD5sum: dd2b555a5b3bf516368c46215612bf86 NeedsCompilation: no Title: ID Mapping Data Retrieval Description: Data retrieval for identifier mapping performance analysis biocViews: Bioinformatics, Annotation, MultipleComparisons Author: Alex Lisovich, Roger Day Maintainer: Alex Lisovich , Roger Day source.ver: src/contrib/IdMappingRetrieval_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/IdMappingRetrieval_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/IdMappingRetrieval_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/IdMappingRetrieval_1.8.0.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: 0.4.0 Imports: base64 Suggests: RUnit, BiocGenerics, IlluminaDataTestFiles, BiocStyle License: GPL-2 Archs: i386, x64 MD5sum: 4c26632da0151b00c98b7090e8b7ab61 NeedsCompilation: yes Title: Parsing Illumina microarray output files Description: Tools for parsing Illumina's microarray output files, including IDAT. biocViews: Infrastructure, DataImport Author: Keith Baggerly, Henrik Bengtsson, Kasper Daniel Hansen, Matt Ritchie, Mike L. Smith Maintainer: Kasper Daniel Hansen source.ver: src/contrib/illuminaio_0.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/illuminaio_0.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/illuminaio_0.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/illuminaio_0.4.0.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: crlmm, minfi Package: imageHTS Version: 1.12.0 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: 26ae92615f2226d86a3755d56f65e16e 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, Bioinformatics, CellBasedAssays, Preprocessing, Visualization Author: Gregoire Pau, Xian Zhang, Michael Boutros, Wolfgang Huber Maintainer: Gregoire Pau source.ver: src/contrib/imageHTS_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/imageHTS_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/imageHTS_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/imageHTS_1.12.0.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: 1.36.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: 1774a8507fe6ad7cbba0346c0c7dae30 NeedsCompilation: yes Title: impute: Imputation for microarray data Description: Imputation for microarray data (currently KNN only) biocViews: Bioinformatics, Microarray Author: Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, Gilbert Chu Maintainer: Balasubramanian Narasimhan source.ver: src/contrib/impute_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/impute_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/impute_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/impute_1.36.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: CGHcall, HCsnip importsMe: ChAMP, MSnbase suggestsMe: BioNet Package: inSilicoDb Version: 1.10.1 Depends: R (>= 2.11.0), rjson, Biobase Imports: RCurl Suggests: limma License: GPL-2 MD5sum: 317a64c2f124f3e4be651bd8d3af4686 NeedsCompilation: no Title: Access to the InSilico Database Description: Access Human Affymetrix expert curated Gene Expression Omnibus (GEO) datasets from the InSilico Database. biocViews: Microarray, DataImport Author: Jonatan Taminau Maintainer: Jonatan Taminau , David Steenhoff URL: https://insilicodb.org source.ver: src/contrib/inSilicoDb_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/inSilicoDb_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.0/inSilicoDb_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.0/inSilicoDb_1.10.1.tgz vignettes: vignettes/inSilicoDb/inst/doc/inSilicoDb.pdf vignetteTitles: Using the inSilicoDb package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoDb/inst/doc/inSilicoDb.R suggestsMe: inSilicoMerging Package: inSilicoMerging Version: 1.6.0 Depends: R (>= 2.11.1), Biobase, DWD Suggests: BiocGenerics, inSilicoDb License: GPL-2 MD5sum: 44955bd28c2df435d4ba61a3d94cd2d0 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: Jonatan Taminau , Stijn Meganck URL: http://insilico.ulb.ac.be/insilico-project/ source.ver: src/contrib/inSilicoMerging_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/inSilicoMerging_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/inSilicoMerging_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/inSilicoMerging_1.6.0.tgz vignettes: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.pdf vignetteTitles: Using the inSilicoMerging package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inSilicoMerging/inst/doc/inSilicoMerging.R Package: intansv Version: 1.2.0 Depends: R (>= 2.14.0), plyr, ggbio, GenomicRanges Imports: BiocGenerics, IRanges License: Artistic-2.0 MD5sum: 68e6bef24fb273492fc705a4e5a7a750 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/intansv_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/intansv_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/intansv_1.2.0.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: 1.0.9 Depends: R (>= 2.10), methods, BiocGenerics, grid Imports: shiny, GenomicRanges, Gviz, RColorBrewer, ggplot2, reshape2, rtracklayer, GO.db, plyr, gridSVG, XML Suggests: RUnit, hgu95av2.db, knitr License: Artistic-2.0 MD5sum: b659ae567448c6a4c34185a6a353b91f 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 Networks QualityControl Visualization NetworkVisualization Genetics DataRepresentation GUI AnnotationData Author: Shawn Balcome, Marc Carlson Maintainer: Shawn Balcome VignetteBuilder: knitr source.ver: src/contrib/interactiveDisplay_1.0.9.tar.gz win.binary.ver: bin/windows/contrib/3.0/interactiveDisplay_1.0.9.zip win64.binary.ver: bin/windows64/contrib/3.0/interactiveDisplay_1.0.9.zip mac.binary.ver: bin/macosx/contrib/3.0/interactiveDisplay_1.0.9.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" Package: inveRsion Version: 1.10.0 Depends: methods, haplo.stats Imports: graphics, methods, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: eb59b13526b732c6675f46216bc05a4d 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/inveRsion_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/inveRsion_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/inveRsion_1.10.0.tgz vignettes: vignettes/inveRsion/inst/doc/inveRsion.pdf, vignettes/inveRsion/inst/doc/Manual.pdf vignetteTitles: Quick start guide for inveRsion package, Manual.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/inveRsion/inst/doc/inveRsion.R Package: iontree Version: 1.8.0 Depends: methods, rJava, RSQLite, XML Suggests: iontreeData License: GPL-2 MD5sum: 0d4801931425e658b4de12bb5ef648d4 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iontree_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iontree_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iontree_1.8.0.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: 1.6.0 Depends: R(>= 2.15),gdata, scatterplot3d, Biostrings, multtest License: GPL-2 MD5sum: adb2f8ce59f7770760bee80fe2aa0beb 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: Bioinformatics, Clustering, BiologicalDomains, Proteomics Author: Gregory Ryslik, Hongyu Zhao Maintainer: Gregory Ryslik source.ver: src/contrib/iPAC_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iPAC_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iPAC_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iPAC_1.6.0.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: 1.10.0 Depends: R (>= 2.12.0), MASS, Matrix, XML, digest, bitops Imports: methods, stats, graphics License: GPL (version 2 or later) Archs: i386, x64 MD5sum: 5b163900123662a782f00fe364d1866a 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/IPPD_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/IPPD_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/IPPD_1.10.0.tgz vignettes: vignettes/IPPD/inst/doc/IPPD.pdf, vignettes/IPPD/inst/doc/templatedetail.pdf, vignettes/IPPD/inst/doc/templates.pdf vignetteTitles: IPPD Manual, templatedetail.pdf, templates.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/IPPD/inst/doc/IPPD.R Package: IRanges Version: 1.20.7 Depends: R (>= 2.8.0), methods, utils, stats, BiocGenerics (>= 0.7.7) Imports: methods, utils, stats, BiocGenerics, stats4 Suggests: XVector, GenomicRanges, BSgenome.Celegans.UCSC.ce2, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: 8dcdc4bc1b640f8052ed28a9d9f566ff 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_1.20.7.tar.gz win.binary.ver: bin/windows/contrib/3.0/IRanges_1.20.7.zip win64.binary.ver: bin/windows64/contrib/3.0/IRanges_1.20.7.zip mac.binary.ver: bin/macosx/contrib/3.0/IRanges_1.20.7.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, casper, CexoR, ChIPpeakAnno, chipseq, chroGPS, cn.mops, CSAR, customProDB, DASiR, DECIPHER, deepSNV, DESeq2, DirichletMultinomial, DNaseR, easyRNASeq, epigenomix, exomeCopy, genomes, GenomicFeatures, GenomicRanges, Genominator, genoset, GGtools, girafe, gwascat, HiTC, HMMcopy, htSeqTools, methyAnalysis, MinimumDistance, MotifDb, motifRG, nucleR, oneChannelGUI, PING, PSICQUIC, rfPred, rGADEM, RIPSeeker, rMAT, Rsamtools, rSFFreader, segmentSeq, ShortRead, SomatiCA, SplicingGraphs, TEQC, TFBSTools, triform, triplex, VariantAnnotation, VariantTools, XVector importsMe: AllelicImbalance, annmap, AnnotationDbi, ArrayExpressHTS, BayesPeak, Biostrings, biovizBase, BiSeq, BitSeq, CAGEr, charm, chipenrich, ChIPpeakAnno, chipseq, ChIPseqR, ChIPsim, ChromHeatMap, cleaver, cn.mops, CNVrd2, cobindR, copynumber, customProDB, DECIPHER, DiffBind, EDASeq, ensemblVEP, epigenomix, fastseg, flipflop, flowQ, FunciSNP, gCMAPWeb, GenomicFeatures, GenomicRanges, genoset, ggbio, girafe, gmapR, Gviz, h5vc, HTSeqGenie, HTSFilter, intansv, MEDIPS, methVisual, methyAnalysis, MethylSeekR, minfi, mosaics, MotIV, MSnbase, NarrowPeaks, nucleR, oligoClasses, OTUbase, pdInfoBuilder, PICS, plethy, prebs, QuasR, R453Plus1Toolbox, Rcade, REDseq, Repitools, ReportingTools, rGADEM, rMAT, rnaSeqMap, Rolexa, rSFFreader, RSVSim, rtracklayer, segmentSeq, SeqArray, SeqVarTools, SomatiCA, spliceR, SplicingGraphs, triform, TSSi, VanillaICE, VariantAnnotation, VariantTools, waveTiling, XVector suggestsMe: BiocGenerics, HilbertVis, HilbertVisGUI, MiRaGE, SNPchip Package: iSeq Version: 1.14.0 Depends: R (>= 2.10.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: ad010bbdfce74a9bc61a46c63a20c635 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, HighThroughputSequencing, Bioinformatics Author: Qianxing Mo Maintainer: Qianxing Mo source.ver: src/contrib/iSeq_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iSeq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iSeq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iSeq_1.14.0.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: 1.8.1 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 License: LGPL-2 MD5sum: 0b307458c9db5bc87ce86c9be48aedfd 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. 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://bioinformatics.cemm.oeaw.ac.at source.ver: src/contrib/isobar_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/isobar_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/isobar_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/isobar_1.8.1.tgz vignettes: vignettes/isobar/inst/doc/isobar-devel.pdf, vignettes/isobar/inst/doc/isobar-ptm.pdf, vignettes/isobar/inst/doc/isobar.pdf vignetteTitles: isobar for developers, isobar for quantification of PTM datasets, isobar package for iTRAQ and TMT protein quantification 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: 1.18.0 Depends: tcltk, tkrplot, IsoGene Imports: multtest, relimp, WriteXLS,gdata, RColorBrewer, geneplotter Suggests: RUnit License: GPL-2 MD5sum: 1f3d838dd5e2fc88ff96647b743e9d8b 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/IsoGeneGUI_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/IsoGeneGUI_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/IsoGeneGUI_1.18.0.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: 2.22.0 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: adb169c03abbb5d90ecd78f7a8e72356 NeedsCompilation: no Title: ITALICS Description: A Method to normalize of Affymetrix GeneChip Human Mapping 100K and 500K set biocViews: Microarray, CopyNumberVariants Author: Guillem Rigaill, Philippe Hupe Maintainer: Guillem Rigaill URL: http://bioinfo.curie.fr source.ver: src/contrib/ITALICS_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ITALICS_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ITALICS_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ITALICS_2.22.0.tgz vignettes: vignettes/ITALICS/inst/doc/ITALICS-006.pdf, vignettes/ITALICS/inst/doc/ITALICS.pdf vignetteTitles: ITALICS-006.pdf, ITALICS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ITALICS/inst/doc/ITALICS.R Package: iterativeBMA Version: 1.20.0 Depends: BMA, leaps, Biobase (>= 2.5.5) License: GPL (>= 2) MD5sum: 15bb1278d911f53b05799ef547c64c1b 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, Bioinformatics, 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iterativeBMA_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iterativeBMA_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iterativeBMA_1.20.0.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: 1.20.0 Depends: BMA, leaps, survival, splines Imports: graphics, grDevices, stats, survival, utils License: GPL (>= 2) MD5sum: 596739f8e69257eeb521586180b1540f 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, Bioinformatics 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/iterativeBMAsurv_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/iterativeBMAsurv_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/iterativeBMAsurv_1.20.0.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: 1.2.0 Depends: R (>= 2.15.2), mosaics License: GPL (>= 2) MD5sum: a569d7b77c30148d849390e7997fe437 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, Bioinformatics Author: Xin Zeng Maintainer: Xin Zeng source.ver: src/contrib/jmosaics_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/jmosaics_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/jmosaics_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/jmosaics_1.2.0.tgz vignettes: vignettes/jmosaics/inst/doc/jmosaics-h3k27me3_g1e-plot.pdf, vignettes/jmosaics/inst/doc/jmosaics-h3k4me1_g1e-plot.pdf, vignettes/jmosaics/inst/doc/jmosaics.pdf vignetteTitles: jmosaics-h3k27me3_g1e-plot.pdf, jmosaics-h3k4me1_g1e-plot.pdf, jMOSAiCS hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/jmosaics/inst/doc/jmosaics.R Package: joda Version: 1.10.0 Depends: R (>= 2.0), bgmm, RBGL License: GPL (>= 2) MD5sum: 42e6359cdd77cf205e82f4b79e46d895 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, GraphsAndNetworks, Statistics, NetworkInference Author: Ewa Szczurek Maintainer: Ewa Szczurek URL: http://www.bioconductor.org source.ver: src/contrib/joda_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/joda_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/joda_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/joda_1.10.0.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: 2.20.0 Depends: siggenes, multtest, KernSmooth Imports: methods, BiocGenerics Enhances: Biobase, CGHbase License: GPL-3 MD5sum: d6e1b2c599e9fede81bde77706b2fc54 NeedsCompilation: no Title: Multi sample aCGH analysis package using kernel convolution Description: Multi sample aCGH analysis package using kernel convolution biocViews: CopyNumberVariants, Visualization, aCGH, Microarray Author: Jorma de Ronde, Christiaan Klijn, Arno Velds Maintainer: Jorma de Ronde source.ver: src/contrib/KCsmart_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/KCsmart_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/KCsmart_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/KCsmart_2.20.0.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: 1.20.0 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: fb7af5e332534bff50c556e94dee1ef8 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, GraphsAndNetworks, NetworkVisualization Author: Jitao David Zhang Maintainer: Jitao David Zhang URL: http://www.nextbiomotif.com source.ver: src/contrib/KEGGgraph_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/KEGGgraph_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/KEGGgraph_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/KEGGgraph_1.20.0.tgz vignettes: vignettes/KEGGgraph/inst/doc/KEGGgraph.pdf, vignettes/KEGGgraph/inst/doc/KEGGgraphApp.pdf vignetteTitles: KEGGgraph: graph approach to KEGG PATHWAY, KEGGgraph: Application Examples hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/KEGGgraph/inst/doc/KEGGgraph.R, vignettes/KEGGgraph/inst/doc/KEGGgraphApp.R dependsOnMe: pathview, ROntoTools, SPIA importsMe: clipper, DEGraph, NCIgraph suggestsMe: DEGraph, GenomicRanges Package: keggorthology Version: 2.14.0 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: 3ac0e9fcad41e237f3f3ca5d265d6fca 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, GraphsAndNetworks, NetworkVisualization Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/keggorthology_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/keggorthology_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/keggorthology_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/keggorthology_2.14.0.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: 1.4.0 Depends: XML, png, TeachingDemos, KEGG.db Imports: AnnotationDbi License: GPL (>= 2) MD5sum: d3d6ca0b2a4612fcab7ef087e2142a19 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 Maintainer: Shilin Zhao source.ver: src/contrib/KEGGprofile_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/KEGGprofile_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/KEGGprofile_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/KEGGprofile_1.4.0.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: 1.2.2 Imports: methods, httr, png, Biostrings Suggests: RUnit, BiocGenerics, knitr License: Artistic-2.0 MD5sum: 073ca4570002085a48ad09a65fc33a6b 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, ConnectTools Author: Dan Tenenbaum Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/KEGGREST_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/KEGGREST_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/KEGGREST_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/KEGGREST_1.2.2.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, pathview Package: lapmix Version: 1.28.0 Depends: R (>= 2.6.0),stats Imports: Biobase, graphics, grDevices, methods, stats, tools, utils License: GPL (>= 2) MD5sum: f996a75e4380e33909c4a6d0e4ca3f3c 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: Bioinformatics, 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/lapmix_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/lapmix_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/lapmix_1.28.0.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: 1.30.0 Depends: stats Imports: graphics, grDevices, methods, stats, utils Suggests: qvalue License: GPL-2 MD5sum: f97fee21916c73083e31be98333a7b46 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: Bioinformatics, MultipleComparisons Author: Cyril Dalmasso Maintainer: Cyril Dalmasso source.ver: src/contrib/LBE_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LBE_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LBE_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LBE_1.30.0.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: 1.12.0 Depends: R (>= 2.13.2), methods, graphics, fdrtool Imports: boot, gplots, RColorBrewer Suggests: Biobase, limma Enhances: parallel License: GPL-3 MD5sum: 716d6e20377fadd4af9c1ab50a944b5b 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, Bioinformatics, 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/les_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/les_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/les_1.12.0.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: 3.18.13 Depends: R (>= 2.3.0), methods Suggests: statmod (>= 1.2.2), splines, locfit, MASS, ellipse, affy, vsn, AnnotationDbi, org.Hs.eg.db License: GPL (>=2) Archs: i386, x64 MD5sum: 31928f4b3653747db35f3e2c3900e635 NeedsCompilation: yes Title: Linear Models for Microarray Data Description: Data analysis, linear models and differential expression for microarray data. biocViews: Microarray, OneChannel, TwoChannel, DataImport, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, MultipleComparisons, TimeCourse Author: Gordon Smyth [cre,aut], Matthew Ritchie [ctb], Jeremy Silver [ctb], James Wettenhall [ctb], Natalie Thorne [ctb], Mette Langaas [ctb], Egil Ferkingstad [ctb], Marcus Davy [ctb], Francois Pepin [ctb], Dongseok Choi [ctb], Davis McCarthy [ctb], Di Wu [ctb], Alicia Oshlack [ctb], Carolyn de Graaf [ctb], Yifang Hu [ctb], Wei Shi [ctb], Belinda Phipson [ctb] Maintainer: Gordon Smyth URL: http://bioinf.wehi.edu.au/limma source.ver: src/contrib/limma_3.18.13.tar.gz win.binary.ver: bin/windows/contrib/3.0/limma_3.18.13.zip win64.binary.ver: bin/windows64/contrib/3.0/limma_3.18.13.zip mac.binary.ver: bin/macosx/contrib/3.0/limma_3.18.13.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, Agi4x44PreProcess, attract, birta, CALIB, cghMCR, ChIPpeakAnno, codelink, convert, Cormotif, coRNAi, DrugVsDisease, edgeR, ExiMiR, gCMAP, HTqPCR, limmaGUI, lmdme, maDB, maigesPack, marray, metagenomeSeq, 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, explorase, GeneSelectMMD, GeneSelector, GGBase, HTqPCR, iChip, maSigPro, minfi, MmPalateMiRNA, OLIN, PADOG, phenoTest, Ringo, RNAinteract, RNAither, RTN, RTopper, SimBindProfiles, snapCGH, timecourse, tweeDEseq, vsn suggestsMe: ABarray, ADaCGH2, beadarraySNP, BiocCaseStudies, BioNet, Category, categoryCompare, CMA, coGPS, dyebias, gage, GeneSelector, GEOquery, GSRI, GSVA, Heatplus, inSilicoDb, isobar, les, lumi, methylumi, MLP, oligo, oneChannelGUI, PGSEA, piano, plw, PREDA, puma, Rcade, RTopper, rtracklayer, virtualArray Package: limmaGUI Version: 1.38.0 Depends: limma, tcltk Suggests: statmod, R2HTML, xtable, tkrplot License: LGPL MD5sum: 50630ab8cfe8a8e8e4a273e85a53be24 NeedsCompilation: no Title: GUI for limma package Description: A Graphical User Interface for the limma Microarray package biocViews: Microarray, TwoChannel, DataImport, QualityControl, Preprocessing, Bioinformatics, DifferentialExpression, MultipleComparisons, 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/limmaGUI_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/limmaGUI_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/limmaGUI_1.38.0.tgz vignettes: vignettes/limmaGUI/inst/doc/extract.pdf, vignettes/limmaGUI/inst/doc/limmaGUI.pdf, vignettes/limmaGUI/inst/doc/LinModIntro.pdf vignetteTitles: Extracting limma objects from limmaGUI files, limmaGUI Vignette, LinModIntro.pdf 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: 1.16.0 Depends: geepack, methods, yeastCC, org.Sc.sgd.db Imports: Biobase, graphics, grDevices, methods, stats License: GPL (>=3) MD5sum: edc6c16c0734e10450f01b867c07a4ad 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, NetworkAnalysis, TimeCourse Author: Yen-Yi Ho Maintainer: Yen-Yi Ho source.ver: src/contrib/LiquidAssociation_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LiquidAssociation_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LiquidAssociation_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LiquidAssociation_1.16.0.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 Package: lmdme Version: 1.4.0 Depends: R (>= 2.14.1), methods, limma, pls, stemHypoxia Imports: stats Enhances: parallel License: GPL (>=2) MD5sum: e3efa912ad39459687ded580b0882db3 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, Bioinformatics, Visualization, AssayDomains, 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/lmdme_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/lmdme_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/lmdme_1.4.0.tgz vignettes: vignettes/lmdme/inst/doc/lmdme-vignette.pdf vignetteTitles: lmdme: Linear Model 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: 2.18.0 Depends: R (>= 2.10.0), Biobase (>= 2.5.5), multtest, survival, affy Suggests: affydata License: LGPL MD5sum: b2f7614c10a67a0ccf535bc41bb1eebd 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, Bioinformatics, 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_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LMGene_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LMGene_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LMGene_2.18.0.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: 1.32.0 Depends: LogicReg, mcbiopi Suggests: genefilter, siggenes License: LGPL (>= 2) MD5sum: cfe32b6e6d67ef42b1f57b8d826af231 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/logicFS_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/logicFS_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/logicFS_1.32.0.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: 1.20.0 Depends: affy Suggests: SpikeInSubset License: GPL (>= 2) Archs: i386, x64 MD5sum: 27926b7c6bb235d863d753c94d3bb713 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/logitT_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/logitT_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/logitT_1.20.0.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: 1.10.0 Depends: penalized, Matrix Imports: Matrix, penalized, graphics, grDevices, stats License: GPL-2 MD5sum: c451032c54eb9f8f3d698509a8abcff1 NeedsCompilation: no Title: Lots Of Lasso Description: Various optimization methods for Lasso inference with matrix warpper Author: Yinyin Yuan Maintainer: Yinyin Yuan source.ver: src/contrib/lol_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/lol_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/lol_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/lol_1.10.0.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: 1.36.0 Depends: R (>= 2.10) Imports: stats License: LGPL MD5sum: df6992233c1d8f48fc8b8598845eaa1a 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, Bioinformatics, 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LPE_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LPE_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LPE_1.36.0.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: 1.22.0 Depends: LPE Imports: LPE, stats License: LGPL MD5sum: 8e2d57fa153d63a845ed11cb1e911a70 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, Bioinformatics, Proteomics Author: Carl Murie , Robert Nadon Maintainer: Carl Murie source.ver: src/contrib/LPEadj_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LPEadj_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LPEadj_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LPEadj_1.22.0.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: 1.2.0 Depends: lpSolve, nem License: Artistic License 2.0 MD5sum: 949d7ed9b7ec2b9293b64b91146451e6 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. Author: Bettina Knapp, Johanna Mazur, Lars Kaderali Maintainer: Bettina Knapp source.ver: src/contrib/lpNet_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/lpNet_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/lpNet_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/lpNet_1.2.0.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: 2.14.2 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: 6527bd5bd376383ef3462ab798c192b1 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_2.14.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/lumi_2.14.2.zip win64.binary.ver: bin/windows64/contrib/3.0/lumi_2.14.2.zip mac.binary.ver: bin/macosx/contrib/3.0/lumi_2.14.2.tgz vignettes: vignettes/lumi/inst/doc/IlluminaAnnotation.pdf, vignettes/lumi/inst/doc/lumi_VST_evaluation.pdf, vignettes/lumi/inst/doc/lumi.pdf, vignettes/lumi/inst/doc/methylationAnalysis.pdf vignetteTitles: Resolve the inconsistency of Illumina identifiers through nuID, Evaluation of VST algorithm in lumi package, Using lumi A package processing Illumina Microarray, 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_VST_evaluation.R, vignettes/lumi/inst/doc/lumi.R, vignettes/lumi/inst/doc/methylationAnalysis.R dependsOnMe: arrayMvout, wateRmelon importsMe: ffpe, methyAnalysis, MineICA suggestsMe: beadarray, methylumi, tigre, virtualArray Package: LVSmiRNA Version: 1.12.0 Depends: R (>= 2.10), Biobase,quantreg,splines,MASS,limma,affy,methods, SparseM, vsn Imports: BiocGenerics, stats4 Enhances: parallel,snow, Rmpi License: GPL-2 Archs: i386, x64 MD5sum: 7354450293d5b908999eacf12c90aa21 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/LVSmiRNA_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/LVSmiRNA_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/LVSmiRNA_1.12.0.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: 1.33.2 Depends: R (>= 2.10) Imports: Biobase, graphics, grDevices, methods, stats, utils Suggests: qvalue, snow Enhances: Rmpi License: GPL (>= 2) Archs: i386, x64 MD5sum: 2e54f7ea7c57e6af6c69a5ff02421737 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_1.33.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/maanova_1.33.2.zip win64.binary.ver: bin/windows64/contrib/3.0/maanova_1.33.2.zip mac.binary.ver: bin/macosx/contrib/3.0/maanova_1.33.2.tgz vignettes: vignettes/maanova/inst/doc/abf1fig.pdf, vignettes/maanova/inst/doc/hckidney.pdf, vignettes/maanova/inst/doc/maanova.pdf, vignettes/maanova/inst/doc/vgprofile.pdf vignetteTitles: abf1fig.pdf, hckidney.pdf, R/maanova HowTo, vgprofile.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/maanova/inst/doc/maanova.R Package: macat Version: 1.36.0 Depends: Biobase, annotate Suggests: hgu95av2.db, stjudem License: Artistic-2.0 MD5sum: 25c1dc0de3fdaef4f7ca5c26ca83b455 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/macat_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/macat_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/macat_1.36.0.tgz vignettes: vignettes/macat/inst/doc/chrom6T.pdf, vignettes/macat/inst/doc/chrom6TkNN.pdf, vignettes/macat/inst/doc/evalkNN6.pdf, vignettes/macat/inst/doc/macat.pdf, vignettes/macat/inst/doc/Slidingchrom6s3.pdf vignetteTitles: chrom6T.pdf, chrom6TkNN.pdf, evalkNN6.pdf, MicroArray Chromosome Analysis Tool, Slidingchrom6s3.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/macat/inst/doc/macat.R Package: maCorrPlot Version: 1.32.0 Depends: lattice Imports: graphics, grDevices, lattice, stats License: GPL (>= 2) MD5sum: bd7b0c64857b79afdad7a079fcaca0dc 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/maCorrPlot_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/maCorrPlot_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/maCorrPlot_1.32.0.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: maDB Version: 1.34.0 Depends: R (>= 2.6.0), Biobase (>= 2.5.5), affy (>= 1.23.4), pgUtils (>= 1.23.2), limma (>= 1.8.0), methods Suggests: annaffy (>= 1.6.2), biomaRt (>= 1.8.2), geneplotter License: LGPL (>= 2) MD5sum: bef9a5636fca0df34852d3ef15e7ad2e NeedsCompilation: no Title: Microarray database and utility functions for microarray data analysis. Description: maDB allows to create a simple microarray database to store microarray experiments and annotation data into it. Affymetrix GeneChip expression values as well as values from two color microarrays can be stored into the database. Whole experiments or subsets from a experiment (or also values for a subset of genes in a subset of microarrays) can be fetched back to R. Additionally maDB provides different utility functions for the microarray data analysis like functions to draw MA plots or volcano plots with the data points color coded according to the local point density or functions that allow a replicate handling of miroarrays. biocViews: Microarray,TwoChannel,OneChannel,Visualization Author: Johannes Rainer Maintainer: Johannes Rainer source.ver: src/contrib/maDB_1.34.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/maDB_1.34.0.tgz vignettes: vignettes/maDB/inst/doc/maDB-015.pdf, vignettes/maDB/inst/doc/maDB-016.pdf, vignettes/maDB/inst/doc/maDB.pdf vignetteTitles: maDB-015.pdf, maDB-016.pdf, maDB.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: made4 Version: 1.36.1 Depends: ade4, RColorBrewer,gplots,scatterplot3d Suggests: affy License: Artistic-2.0 MD5sum: 97a8c1b7cf1616724ad3a7629f877020 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: Bioinformatics, Clustering, Classification, MultipleComparisons Author: Aedin Culhane Maintainer: Aedin Culhane URL: http://www.hsph.harvard.edu/aedin-culhane/ source.ver: src/contrib/made4_1.36.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/made4_1.36.1.zip win64.binary.ver: bin/windows64/contrib/3.0/made4_1.36.1.zip mac.binary.ver: bin/macosx/contrib/3.0/made4_1.36.1.tgz vignettes: vignettes/made4/inst/doc/html3D.pdf, vignettes/made4/inst/doc/introduction.pdf vignetteTitles: html3D.pdf, introduction.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/made4/inst/doc/introduction.R dependsOnMe: bgafun importsMe: omicade4 Package: maigesPack Version: 1.26.0 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: bb35259c517a9e50856d5242deae6d5d 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, ConnectTools, DifferentialExpression, Clustering, Classification, GraphsAndNetworks 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/maigesPack_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/maigesPack_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/maigesPack_1.26.0.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: 1.38.0 Depends: R (>= 2.6.0), methods, affyio Imports: Biobase, affy, methods, stats, utils, zlibbioc License: GPL (>= 2) Archs: i386, x64 MD5sum: 3f2338fe3351eaa7d8a86faa5223de0c 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/makecdfenv_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/makecdfenv_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/makecdfenv_1.38.0.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: 1.34.0 Depends: R (>= 2.10), GLAD Imports: GLAD, graphics, grDevices, stats, utils License: GPL-2 Archs: i386, x64 MD5sum: 189e96b524ead76a44764b71d85e3fd9 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, CopyNumberVariants Author: Pierre Neuvial , Philippe Hupe Maintainer: Pierre Neuvial URL: http://bioinfo.curie.fr/projects/manor/index.html source.ver: src/contrib/MANOR_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MANOR_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MANOR_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MANOR_1.34.0.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: 1.8.0 Depends: R (>= 1.8.0), methods, edgeR (>= 2.5.13) Imports: Hmisc, caroline(>= 0.6.6) Suggests: RSQLite, plotrix License: Artistic-2.0 MD5sum: 70c4dfaa9f2357d641666f73e7b269b1 NeedsCompilation: no Title: Microbial Assemblage Normalized Transcript Analysis Description: Tools for robust comparative metatranscriptomics. biocViews: DifferentialExpression, RNAseq, Genetics, GeneExpression, Bioinformatics, HighThroughputSequencing, QualityControl, DataImport, Visualization Author: Ginger Armbrust, Adrian Marchetti, David M. Schruth Maintainer: Chris Berthiaume , Adrian Marchetti URL: http://manta.ocean.washington.edu/ source.ver: src/contrib/manta_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/manta_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/manta_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/manta_1.8.0.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: 1.32.0 Depends: R (>= 2.10) Imports: stats License: GPL (>= 2) MD5sum: 3354b9f55158cd912b72bb8ffe9676ad 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: Bioinformatics, Clustering Author: Brian Steinmeyer and William Shannon Maintainer: Brian Steinmeyer source.ver: src/contrib/MantelCorr_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MantelCorr_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MantelCorr_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MantelCorr_1.32.0.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: 1.0.0 Depends: R (>= 2.15.0), MASS,affy,limma,gcrma,ROC,class,e1071,caret,hgu133plus2.db,ROCR,AnnotationDbi,LungCancerACvsSCCGEO Suggests: parallel License: GPL-2 MD5sum: 989c1dea144f5cfa2786ba982a691e12 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/maPredictDSC_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/maPredictDSC_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/maPredictDSC_1.0.0.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: 1.40.0 Depends: R (>= 2.10.0), limma, methods Suggests: tkWidgets License: LGPL MD5sum: c82aa82073cdbc4cfb4839fb196d5082 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/marray_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/marray_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/marray_1.40.0.tgz vignettes: vignettes/marray/inst/doc/ExampleHTML.pdf, vignettes/marray/inst/doc/marray.pdf, 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/marrayPlots.pdf, vignettes/marray/inst/doc/widget1.pdf vignetteTitles: ExampleHTML.pdf, marray Overview, marrayClasses Overview, marrayClasses Tutorial (short), marrayInput Introduction, marray Normalization, marrayPlots Overview, widget1.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/marray/inst/doc/marray.R, 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 dependsOnMe: CGHbase, convert, dyebias, maigesPack, MineICA, nnNorm, OLIN, stepNorm, TurboNorm importsMe: arrayQuality, ChAMP, nnNorm, OLIN, OLINgui, piano, plrs, sigaR, stepNorm, timecourse suggestsMe: Agi4x44PreProcess, DEGraph, Mfuzz Package: maSigPro Version: 1.34.1 Depends: R (>= 2.3.1), stats, Biobase, MASS Imports: Biobase, graphics, grDevices, limma, Mfuzz, stats, utils, MASS License: GPL (>= 2) MD5sum: 2939d433d5eefa45fd8bbb42e98b48b1 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_1.34.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/maSigPro_1.34.1.zip win64.binary.ver: bin/windows64/contrib/3.0/maSigPro_1.34.1.zip mac.binary.ver: bin/macosx/contrib/3.0/maSigPro_1.34.1.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-tutorial.R, vignettes/maSigPro/inst/doc/maSigPro.R suggestsMe: oneChannelGUI Package: maskBAD Version: 1.6.0 Depends: R (>= 2.10), gcrma (>= 2.27.1), affy Suggests: hgu95av2probe License: GPL version 2 or newer MD5sum: 0ca6249694ba3494e2d35bb6ce4d4714 NeedsCompilation: no Title: Masking probes with binding affinity differences Description: Package includes functions to analyze and mask microarray expression data. Author: Michael Dannemann Maintainer: Michael Dannemann source.ver: src/contrib/maskBAD_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/maskBAD_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/maskBAD_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/maskBAD_1.6.0.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: 1.14.0 Depends: R (>= 2.10.0), methods Imports: graphics, grDevices, methods, stats, utils License: GPL (>=2) MD5sum: b924cc524ba82f85f484afb0103e34e9 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MassArray_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MassArray_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MassArray_1.14.0.tgz vignettes: vignettes/MassArray/inst/doc/conversion.pdf, vignettes/MassArray/inst/doc/MassArray.pdf vignetteTitles: conversion.pdf, 1. Primer hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MassArray/inst/doc/MassArray.R Package: MassSpecWavelet Version: 1.28.0 Depends: waveslim Suggests: xcms, caTools License: LGPL (>= 2) Archs: i386, x64 MD5sum: 7ddd1dfe0db276f2c87a00655d05c1fb 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MassSpecWavelet_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MassSpecWavelet_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MassSpecWavelet_1.28.0.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: 1.4.0 Depends: R (>= 2.8.0) License: Artistic-2.0 MD5sum: 15b20c1228682759e9565c094b7a6c0e 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, MultipleComparisons, Visualization Author: Luigi Marchionni , Anuj Gupta Maintainer: Luigi Marchionni , Anuj Gupta source.ver: src/contrib/matchBox_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/matchBox_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/matchBox_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/matchBox_1.4.0.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: 1.16.0 Depends: R (>= 2.9.0), tcltk, tcltk2 Imports: preprocessCore, stats, utils License: GPL (>= 2) MD5sum: 1a7791662622fa5e41e7fe5aa9ed3801 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MBCB_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MBCB_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MBCB_1.16.0.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: 1.16.0 Depends: oligoClasses, SNPchip Imports: Biobase Suggests: xtable License: GPL (>= 2) MD5sum: 907de5434aee3987489ecfbd82583b85 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, CopyNumberVariants, Bioinformatics 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mBPCR_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mBPCR_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mBPCR_1.16.0.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: 1.10.0 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: 7e5c4183a2e25ececc1d1adb609ceec5 NeedsCompilation: no Title: Microbial Community Analysis GUI Description: Microbial community analysis GUI for R using gWidgets. biocViews: GUI, Visualization, Bioinformatics, 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mcaGUI_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mcaGUI_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mcaGUI_1.10.0.tgz vignettes: vignettes/mcaGUI/inst/doc/An_Introduction_and_User_Guide_for_mcaGUI.pdf vignetteTitles: An_Introduction_and_User_Guide_for_mcaGUI.pdf hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: MCRestimate Version: 2.18.0 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: df3eda8e6be049539f7ac42596790b03 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: Bioinformatics, 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_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MCRestimate_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MCRestimate_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MCRestimate_2.18.0.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: 1.24.0 Depends: R (>= 2.2.1), cluster, MASS License: LGPL (>= 2) MD5sum: 45bb701a55de42aa2c5ca6c7659ca25d 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mdqc_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mdqc_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mdqc_1.24.0.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: 1.34.0 License: LGPL MD5sum: bcf5b802bb68b61e9671a930d9743a60 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: Bioinformatics Author: Beiying Ding Maintainer: Beiying Ding source.ver: src/contrib/MeasurementError.cor_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MeasurementError.cor_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MeasurementError.cor_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MeasurementError.cor_1.34.0.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: 1.12.0 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: ffdd00362364cd294fee6a6828fc25e2 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: Sequencing, DNAMethylation, CpGIsland, DifferentialExpression, HighThroughputSequencing, ChIPseq, Preprocessing, QualityControl, Visualization Author: Lukas Chavez, Matthias Lienhard, Joern Dietrich Maintainer: Lukas Chavez source.ver: src/contrib/MEDIPS_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MEDIPS_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MEDIPS_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MEDIPS_1.12.0.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: 1.22.0 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: cd435185ec922553146c3cb352368be6 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MEDME_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MEDME_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MEDME_1.22.0.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: 2.34.0 Depends: R (>= 2.10.0), survival, Biobase, MASS, methods License: GPL (>= 2) MD5sum: c736e21bae8ec6b2a3e8b1e24c7bc509 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_2.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MergeMaid_2.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MergeMaid_2.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MergeMaid_2.34.0.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: metaArray Version: 1.40.0 Imports: Biobase, MergeMaid, graphics, stats License: LGPL-2 Archs: i386, x64 MD5sum: 4eb6d61a5bd40ed275bda9e67ce83ddf 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, Bioinformatics, DifferentialExpression Author: Debashis Ghosh Hyungwon Choi Maintainer: Hyungwon Choi source.ver: src/contrib/metaArray_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/metaArray_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/metaArray_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/metaArray_1.40.0.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: 1.4.2 Depends: R(>= 3.0), Biobase, limma, matrixStats, methods, RColorBrewer, gplots Suggests: annotate, knitr License: Artistic-2.0 MD5sum: d9d6e793dd465f49ea12e6a1bf007524 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: Bioinformatics, 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_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/metagenomeSeq_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/metagenomeSeq_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/metagenomeSeq_1.4.2.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: 1.20.0 Depends: R (>= 2.10), methods Suggests: affyPLM License: GPL-3 Archs: i386, x64 MD5sum: 16a60b982532ab5adb3858d6872cb0dd 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, Bioinformatics, DifferentialExpression Author: John R. Stevens, Gabriel Nicholas Maintainer: John R. Stevens source.ver: src/contrib/metahdep_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/metahdep_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/metahdep_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/metahdep_1.20.0.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: metaSeq Version: 1.2.2 Depends: R (>= 2.13.0), NOISeq, snow License: Artistic-2.0 MD5sum: 0bfb2ae672ed8fa6e019647ea527f697 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: Bioinformatics, RNAseq, DifferentialExpression, HighThroughputSequencing Author: Koki Tsuyuzaki, Itoshi Nikaido Maintainer: Koki Tsuyuzaki source.ver: src/contrib/metaSeq_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/metaSeq_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/metaSeq_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/metaSeq_1.2.2.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: methVisual Version: 1.14.0 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: 676eec8464fd41f7c765b4724f0a020a 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: Bioinformatics, DNAMethylation, Clustering, Classification Author: A. Zackay, C. Steinhoff Maintainer: Arie Zackay source.ver: src/contrib/methVisual_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/methVisual_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/methVisual_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/methVisual_1.14.0.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: 1.4.2 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: 730a6f722bdc8895b1509155cc9f4fe0 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_1.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/methyAnalysis_1.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/methyAnalysis_1.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/methyAnalysis_1.4.2.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: 1.0.0 Depends: R (>= 2.12.1), edgeR, statmod License: GPL-3 Archs: i386, x64 MD5sum: 7c9f2672248fd7e80f4bdbb6fbba0549 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/methylMnM_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/methylMnM_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/methylMnM_1.0.0.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: 1.2.2 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: 1a72203da7e992f417a812ba424139e1 NeedsCompilation: no Title: Segmentation of Bis-seq data Description: This is a package for the discovery of regulatory regions from Bis-seq data biocViews: HighThroughputSequencing, Methylseq, DNAMethylation Author: Lukas Burger, Dimos Gaidatzis, Dirk Schubeler and Michael Stadler Maintainer: Lukas Burger source.ver: src/contrib/MethylSeekR_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/MethylSeekR_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/MethylSeekR_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/MethylSeekR_1.2.2.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: 2.8.0 Depends: Biobase, methods, R (>= 2.13), scales, reshape2, ggplot2, matrixStats Imports: Biobase, graphics, lattice, annotate, genefilter, AnnotationDbi, minfi, stats4, BiocGenerics Suggests: lumi, lattice, limma, xtable, IlluminaHumanMethylation27k.db (>= 1.4.4), IlluminaHumanMethylation450k.db, SQN, GenomicRanges, MASS, matrixStats, parallel, rtracklayer, Biostrings, methyAnalysis, FDb.InfiniumMethylation.hg19 License: GPL-2 MD5sum: 9dc8ec21b8aa9f4834a946822f79e643 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 source.ver: src/contrib/methylumi_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/methylumi_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/methylumi_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/methylumi_2.8.0.tgz vignettes: vignettes/methylumi/inst/doc/methylumi.pdf vignetteTitles: An Introduction to the methylumi package hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/methylumi/inst/doc/methylumi.R dependsOnMe: wateRmelon importsMe: ffpe, lumi, methyAnalysis Package: Mfuzz Version: 2.20.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), e1071 Imports: tcltk, tkWidgets Suggests: marray License: GPL-2 MD5sum: aa3e56308dd75753b2a66cc8c2319f38 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_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Mfuzz_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Mfuzz_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Mfuzz_2.20.0.tgz vignettes: vignettes/Mfuzz/inst/doc/Mfuzz.pdf, vignettes/Mfuzz/inst/doc/MfuzzguiScreenshot.pdf, vignettes/Mfuzz/inst/doc/yeasttable3.pdf vignetteTitles: Introduction to Mfuzz, MfuzzguiScreenshot.pdf, yeasttable3.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Mfuzz/inst/doc/Mfuzz.R dependsOnMe: cycle importsMe: maSigPro Package: mgsa Version: 1.10.0 Depends: R (>= 2.14.0), methods, gplots Imports: graphics, stats, utils Suggests: DBI, RSQLite, GO.db License: Artistic-2.0 Archs: i386, x64 MD5sum: ce4f4af8a20577a18f2cda647a01f430 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mgsa_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mgsa_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mgsa_1.10.0.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: 1.16.0 Depends: R (>= 2.3.0), Biobase Imports: Biobase License: GPL (>= 2) MD5sum: e21c867126e3d34a4fbf1e143946c69d 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_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MiChip_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MiChip_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MiChip_1.16.0.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: 1.20.0 Depends: R (>= 2.10) Imports: Biostrings (>= 2.11.32) Suggests: Biostrings (>= 2.11.32) Enhances: Rlibstree License: Artistic-2.0 MD5sum: fc9647dd7794e6f5adf15100a7eb4ec4 NeedsCompilation: no Title: Data and functions for dealing with microRNAs Description: Different data resources for microRNAs and some functions for manipulating them. biocViews: Infrastructure, SequenceAnnotation, SequenceMatching Author: R. Gentleman, S. Falcon Maintainer: "James F. Reid" source.ver: src/contrib/microRNA_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/microRNA_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/microRNA_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/microRNA_1.20.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: Roleswitch suggestsMe: MmPalateMiRNA, rtracklayer Package: MineICA Version: 1.2.2 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: 119321ecd43ac1922b8bf3db76aeb14e 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. Author: Anne Biton Maintainer: Anne Biton source.ver: src/contrib/MineICA_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/MineICA_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/MineICA_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/MineICA_1.2.2.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: 3.16.0 Depends: infotheo License: CC BY-NC-SA 3.0 Archs: i386, x64 MD5sum: 6f23d1796614099ffe13e157b0cf5e05 NeedsCompilation: yes Title: Mutual Information NETworks Description: This package implements various algorithms for inferring mutual information networks from data. biocViews: Microarray, GraphsAndNetworks, NetworkAnalysis, NetworkInference Author: Patrick E. Meyer, Frederic Lafitte, Gianluca Bontempi Maintainer: Patrick E. Meyer URL: http://minet.meyerp.com source.ver: src/contrib/minet_3.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/minet_3.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/minet_3.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/minet_3.16.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: BUS, geNetClassifier, netresponse importsMe: RTN suggestsMe: CNORfeeder, predictionet Package: minfi Version: 1.8.9 Depends: methods, BiocGenerics (>= 0.3.2), Biobase (>= 2.17.8), lattice, reshape, GenomicRanges, Biostrings, utils, bumphunter (>= 1.1.9) Imports: IRanges, beanplot, RColorBrewer, nor1mix, siggenes, limma, preprocessCore, illuminaio, matrixStats, mclust, genefilter, nlme 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: a6483d427a80a1af21b73f8e6b5a1537 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] Maintainer: Kasper Daniel Hansen source.ver: src/contrib/minfi_1.8.9.tar.gz win.binary.ver: bin/windows/contrib/3.0/minfi_1.8.9.zip win64.binary.ver: bin/windows64/contrib/3.0/minfi_1.8.9.zip mac.binary.ver: bin/macosx/contrib/3.0/minfi_1.8.9.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 importsMe: methylumi Package: MinimumDistance Version: 1.6.0 Depends: R (>= 2.14), BiocGenerics (>= 0.3.2), IRanges (>= 1.13.30) Imports: methods, DNAcopy, utils, msm, lattice, BiocGenerics, VanillaICE (>= 1.21.24), ff, Biobase (>= 2.17.8), foreach, oligoClasses (>= 1.21.12), GenomicRanges, matrixStats Suggests: human610quadv1bCrlmm (>= 1.0.3), SNPchip, RUnit Enhances: snow, doSNOW License: Artistic-2.0 MD5sum: 0145be1e5b981bc936da3716f590dbcf 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, Bioinformatics, CopyNumberVariants Author: Robert B Scharpf and Ingo Ruczinski Maintainer: Robert B Scharpf source.ver: src/contrib/MinimumDistance_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MinimumDistance_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MinimumDistance_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MinimumDistance_1.6.0.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: 1.34.0 Depends: R (>= 2.4) Imports: Biobase, e1071, MASS, stats License: GPL (>= 2) MD5sum: be8470fdb180ab0e6464bd204cd07111 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MiPP_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MiPP_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MiPP_1.34.0.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: 1.4.0 Depends: R (>= 2.12.1), Biobase(>= 2.16.0) Imports: AnnotationDbi, BiocGenerics Suggests: seqinr (>= 3.0.3), biomaRt (>= 2.6.0), GenomicFeatures (>= 1.8.1), Biostrings (>= 2.24.1), BSgenome.Hsapiens.UCSC.hg19, BSgenome.Mmusculus.UCSC.mm9, miRNATarget, humanStemCell, IRanges , GenomicRanges (>= 1.8.3), BSgenome, beadarrayExampleData License: GPL MD5sum: b39cbce34fb21e950f758c95d63d707c 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, HighThroughputSequencingData, Sequencing, SAGE Author: Y-h. Taguchi Maintainer: Y-h. Taguchi source.ver: src/contrib/MiRaGE_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MiRaGE_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MiRaGE_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MiRaGE_1.4.0.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: 1.22.0 Depends: methods, R(>= 2.7.0) License: LGPL-2.1 MD5sum: 56918b6026cad47689b5fc6fb7647098 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/miRNApath_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/miRNApath_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/miRNApath_1.22.0.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: mitoODE Version: 1.0.0 Depends: R (>= 2.14.0), minpack.lm, MASS, parallel, mitoODEdata, KernSmooth License: LGPL Archs: i386, x64 MD5sum: 2cdb634230aae59d97ad1991f48c3ebf NeedsCompilation: yes Title: Implementation of the differential equation model described in "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" (submitted). 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 the paper "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" (submitted). biocViews: ExperimentData, TimeCourse, CellBasedAssays, Preprocessing Author: Gregoire Pau Maintainer: Gregoire Pau SystemRequirements: source.ver: src/contrib/mitoODE_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mitoODE_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mitoODE_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mitoODE_1.0.0.tgz vignettes: vignettes/mitoODE/inst/doc/mitoODE-introduction.pdf, vignettes/mitoODE/inst/doc/model.pdf vignetteTitles: mitoODE, model.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mitoODE/inst/doc/mitoODE-introduction.R Package: MLInterfaces Version: 1.42.0 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: 29992d2d8641defd5c471e6a95c09d01 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: Bioinformatics, 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_1.42.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MLInterfaces_1.42.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MLInterfaces_1.42.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MLInterfaces_1.42.0.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: 1.10.0 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: 6a072fa0ce939b0e5591dbf3247d9cc7 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MLP_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MLP_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MLP_1.10.0.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: MMDiff Version: 1.2.1 Depends: R (>= 2.14.0),GenomicRanges,parallel,DiffBind,GMD,Rsamtools Imports: GenomicRanges,IRanges,Biobase Suggests: MMDiffBamSubset License: Artistic-2.0 MD5sum: 1f145ea78fbd40881d650bb30121ce6e 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, MultipleComparisons Author: Gabriele Schweikert Maintainer: Gabriele Schweikert source.ver: src/contrib/MMDiff_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/MMDiff_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/MMDiff_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/MMDiff_1.2.1.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: MmPalateMiRNA Version: 1.12.0 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: 9db37b2c04e5b169f60df6044bcd9acd 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, Bioinformatics, QualityControl, Preprocessing, DifferentialExpression, MultipleComparisons, 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MmPalateMiRNA_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MmPalateMiRNA_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MmPalateMiRNA_1.12.0.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: 1.10.1 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: d8254e017a1e720eebed94d210500b38 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_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/mosaics_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.0/mosaics_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.0/mosaics_1.10.1.tgz vignettes: vignettes/mosaics/inst/doc/Figure4a.pdf, vignettes/mosaics/inst/doc/Figure4b.pdf, vignettes/mosaics/inst/doc/Figure5a.pdf, vignettes/mosaics/inst/doc/Figure5b.pdf, vignettes/mosaics/inst/doc/Figure5c.pdf, vignettes/mosaics/inst/doc/Figure5d.pdf, vignettes/mosaics/inst/doc/GOF_matchLow.pdf, vignettes/mosaics/inst/doc/GOF_rMOM.pdf, vignettes/mosaics/inst/doc/mosaics-example.pdf vignetteTitles: Figure4a.pdf, Figure4b.pdf, Figure5a.pdf, Figure5b.pdf, Figure5c.pdf, Figure5d.pdf, GOF_matchLow.pdf, GOF_rMOM.pdf, MOSAiCS hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/mosaics/inst/doc/mosaics-example.R dependsOnMe: jmosaics Package: MotifDb Version: 1.4.1 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: c7af912034e2cf05df32c9b9e6f40bb6 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_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/MotifDb_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/MotifDb_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/MotifDb_1.4.1.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 dependsOnMe: rTRMui suggestsMe: motifStack, PWMEnrich, rTRM, vtpnet Package: motifRG Version: 1.6.0 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: c2514227e288dd7dc519b80c35b94a10 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/motifRG_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/motifRG_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/motifRG_1.6.0.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: 1.6.5 Depends: R (>= 2.15.1), methods, grImport, grid, MotIV, ade4 Imports: XML Suggests: RUnit, BiocGenerics, MotifDb, RColorBrewer, BiocStyle License: GPL (>= 2) MD5sum: c1b6d4cc9e034c1de81da0fa9bb61a4e 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_1.6.5.tar.gz win.binary.ver: bin/windows/contrib/3.0/motifStack_1.6.5.zip win64.binary.ver: bin/windows64/contrib/3.0/motifStack_1.6.5.zip mac.binary.ver: bin/macosx/contrib/3.0/motifStack_1.6.5.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: 1.18.0 Depends: R (>= 2.10), BiocGenerics (>= 0.1.0) Imports: graphics, grid, methods, BiocGenerics, IRanges (>= 1.13.5), Biostrings (>= 1.24.0), lattice, rGADEM, stats, utils Suggests: rtracklayer License: GPL-2 Archs: i386, x64 MD5sum: bd611f181a079b15cb2d8c1cbbf9e80d 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MotIV_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MotIV_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MotIV_1.18.0.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: 1.0.0 Depends: R (>= 3.0.1), MSnbase Imports: MASS, gplots, RColorBrewer License: GPL-2 MD5sum: 1044270c465951fedf3be156b1b7f528 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/msmsEDA_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/msmsEDA_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/msmsEDA_1.0.0.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: 1.0.0 Depends: R (>= 3.0.1), MSnbase, msmsEDA Imports: edgeR, qvalue License: GPL-2 MD5sum: 95f71129668b1935262aca447722a080 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/msmsTests_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/msmsTests_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/msmsTests_1.0.0.tgz vignettes: vignettes/msmsTests/inst/doc/msmsTests-Vignette.pdf, vignettes/msmsTests/inst/doc/msmsTests-Vignette2.pdf vignetteTitles: msmsTests: post test filters to improve reproducibility, msmsTests: controlling batch effects by blocking hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/msmsTests/inst/doc/msmsTests-Vignette.R, vignettes/msmsTests/inst/doc/msmsTests-Vignette2.R Package: MSnbase Version: 1.10.4 Depends: R (>= 2.10), methods, BiocGenerics (>= 0.7.1), Biobase (>= 2.15.2), ggplot2, mzR Imports: plyr, IRanges, preprocessCore, vsn, grid, reshape2, stats4, affy, impute Suggests: testthat, zoo, knitr (>= 1.1.0), rols, Rdisop, pRolocdata, msdata Enhances: foreach, doMC, parallel License: Artistic-2.0 MD5sum: 5924960414d5733729b4c91a985fda76 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, Bioinformatics, Proteomics, MassSpectrometry, QualityControl Author: Laurent Gatto with contributions from Guangchuang Yu Maintainer: Laurent Gatto VignetteBuilder: knitr source.ver: src/contrib/MSnbase_1.10.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/MSnbase_1.10.4.zip win64.binary.ver: bin/windows64/contrib/3.0/MSnbase_1.10.4.zip mac.binary.ver: bin/macosx/contrib/3.0/MSnbase_1.10.4.tgz vignettes: vignettes/MSnbase/inst/doc/itraqchem.pdf, vignettes/MSnbase/inst/doc/MSnbase-demo.pdf, vignettes/MSnbase/inst/doc/MSnbase-development.pdf, vignettes/MSnbase/inst/doc/MSnbase-io.pdf, vignettes/MSnbase/inst/doc/plotMzDelta-pride12011.pdf vignetteTitles: itraqchem.pdf, Base Functions and Classes for MS-based Proteomics, MSnbase development, MSnbase IO capabilities, plotMzDelta-pride12011.pdf 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 Package: MSstats Version: 2.0.1 Depends: R (>= 3.0), Rcpp, MSnbase Imports: lme4,marray,limma,gplots,ggplot2 License: Artistic-2.0 MD5sum: 86bd5e13d4b3cd1154dd6eb88da48e1c NeedsCompilation: no Title: Protein Significance Analysis in LC-MS, SRM and DIA for Label-free or Label-based Proteomics Experiments Description: A set of tools for protein significance analysis in label-free or LC-MS, SRM and DIA experiments. Author: Meena Choi , Ching-Yun Chang , Olga Vitek Maintainer: Meena Choi source.ver: src/contrib/MSstats_2.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/MSstats_2.0.1.zip win64.binary.ver: bin/windows64/contrib/3.0/MSstats_2.0.1.zip mac.binary.ver: bin/macosx/contrib/3.0/MSstats_2.0.1.tgz vignettes: vignettes/MSstats/inst/doc/Comparison1.pdf, vignettes/MSstats/inst/doc/Comparison2.pdf, vignettes/MSstats/inst/doc/Condition1.pdf, vignettes/MSstats/inst/doc/Condition2.pdf, vignettes/MSstats/inst/doc/DIA_constant_QQPlot4.pdf, vignettes/MSstats/inst/doc/DIA_constant_ResidualPlot4.pdf, vignettes/MSstats/inst/doc/DIA_ProfilePlot_269.pdf, vignettes/MSstats/inst/doc/DIA_ProfilePlot_377.pdf, vignettes/MSstats/inst/doc/Heatmap45Yeast1.pdf, vignettes/MSstats/inst/doc/Heatmap45Yeast2.pdf, vignettes/MSstats/inst/doc/LCMS_constant_ResidualPlot.pdf, vignettes/MSstats/inst/doc/LCMS_Heatmap.pdf, vignettes/MSstats/inst/doc/LCMS_ProfilePlot.pdf, vignettes/MSstats/inst/doc/MSstats.pdf, vignettes/MSstats/inst/doc/MSstatsOverview.pdf, vignettes/MSstats/inst/doc/power.pdf, vignettes/MSstats/inst/doc/ProfilePlot1.pdf, vignettes/MSstats/inst/doc/ProfilePlot2.pdf, vignettes/MSstats/inst/doc/QCPlot_all_before.pdf, vignettes/MSstats/inst/doc/QCPlot_all.pdf, vignettes/MSstats/inst/doc/QQPlot2.pdf, vignettes/MSstats/inst/doc/ResidualPlot2.pdf, vignettes/MSstats/inst/doc/SampleSizeReplicateYeast.pdf, vignettes/MSstats/inst/doc/SRM_QQPlot_perFeature_heavy.pdf, vignettes/MSstats/inst/doc/SRM_QQPlot_perFeature_light.pdf, vignettes/MSstats/inst/doc/Volcano45Yeast1.pdf, vignettes/MSstats/inst/doc/Volcano45Yeast2.pdf, vignettes/MSstats/inst/doc/VolcanoYeast1.pdf, vignettes/MSstats/inst/doc/VolcanoYeast2.pdf vignetteTitles: Comparison1.pdf, Comparison2.pdf, Condition1.pdf, Condition2.pdf, DIA_constant_QQPlot4.pdf, DIA_constant_ResidualPlot4.pdf, DIA_ProfilePlot_269.pdf, DIA_ProfilePlot_377.pdf, Heatmap45Yeast1.pdf, Heatmap45Yeast2.pdf, LCMS_constant_ResidualPlot.pdf, LCMS_Heatmap.pdf, LCMS_ProfilePlot.pdf, Protein quantification in LC-MS,, SRM,, DIA experiments, MSstatsOverview.pdf, power.pdf, ProfilePlot1.pdf, ProfilePlot2.pdf, QCPlot_all_before.pdf, QCPlot_all.pdf, QQPlot2.pdf, ResidualPlot2.pdf, SampleSizeReplicateYeast.pdf, SRM_QQPlot_perFeature_heavy.pdf, SRM_QQPlot_perFeature_light.pdf, Volcano45Yeast1.pdf, Volcano45Yeast2.pdf, VolcanoYeast1.pdf, VolcanoYeast2.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/MSstats/inst/doc/MSstats.R Package: Mulcom Version: 1.12.0 Depends: R (>= 2.10), fields, Biobase Imports: graphics, grDevices, stats, methods License: GPL-2 Archs: i386, x64 MD5sum: 3c244ce173d6c26953abd61c83530710 NeedsCompilation: yes Title: Calculates Mulcom test Description: Identification of differentially expressed genes and false discovery rate (FDR) calculation by Multiple Comparison test biocViews: Statistics, MultipleComparisons, Microarray, DifferentialExpression, GeneExpression Author: Claudio Isella Maintainer: Claudio Isella source.ver: src/contrib/Mulcom_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Mulcom_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Mulcom_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Mulcom_1.12.0.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: 1.22.0 Depends: R (>= 2.3.0) Imports: Biobase, utils License: GPL (>= 2) Archs: i386, x64 MD5sum: e164516e5f9f095c721450f9c19934f1 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/multiscan_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/multiscan_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/multiscan_1.22.0.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: 2.18.0 Depends: R (>= 2.10), methods, Biobase Imports: survival, MASS, stats4 Suggests: snow License: LGPL Archs: i386, x64 MD5sum: 265ed65e1e7b6c1796a5bbb22519fd18 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, MultipleComparisons Author: Katherine S. Pollard, Houston N. Gilbert, Yongchao Ge, Sandra Taylor, Sandrine Dudoit Maintainer: Katherine S. Pollard source.ver: src/contrib/multtest_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/multtest_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/multtest_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/multtest_2.18.0.tgz vignettes: vignettes/multtest/inst/doc/MTP.pdf, vignettes/multtest/inst/doc/MTPALL.pdf, vignettes/multtest/inst/doc/multtest.pdf vignetteTitles: MTP.pdf, MTPALL.pdf, multtest.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: a4Base, aCGH, BicARE, ChIPpeakAnno, 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, GOstats, GSEAlm, maigesPack, MmPalateMiRNA, oneChannelGUI, pcot2, topGO, xcms Package: MVCClass Version: 1.36.0 Depends: R (>= 2.1.0), methods License: LGPL MD5sum: 2aaa8798d7d2e1c2dc21194a5615eeaa NeedsCompilation: no Title: Model-View-Controller (MVC) Classes Description: Creates classes used in model-view-controller (MVC) design biocViews: Visualization, Infrastructure, GraphsAndNetworks Author: Elizabeth Whalen Maintainer: Elizabeth Whalen source.ver: src/contrib/MVCClass_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/MVCClass_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/MVCClass_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/MVCClass_1.36.0.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: 1.0.0 Depends: methods, XML Imports: plyr License: GPL (>= 2) MD5sum: d85ea9c29da82aaf1bc6ecea7213bba3 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 Dybdal Pedersen, Vladislav A Petyuk with contributions from Laurent Gatto. Maintainer: Thomas Dybdal Pedersen VignetteBuilder: knitr source.ver: src/contrib/mzID_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/mzID_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/mzID_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/mzID_1.0.0.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 Package: mzR Version: 1.8.1 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: 2c44daa7fa6092ea455e0b8986af6cd0 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, Bioinformatics, DataImport, Proteomics, Metabolomics, MassSpectrometry Author: Bernd Fischer, Steffen Neumann, Laurent Gatto Maintainer: Bernd Fischer , Steffen Neumann , Laurent Gatto SystemRequirements: GNU make, NetCDF, zlib source.ver: src/contrib/mzR_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/mzR_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/mzR_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/mzR_1.8.1.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: 1.6.0 Depends: R (>= 2.10.0), splines Imports: GenomicRanges, IRanges, fda, CSAR Suggests: rtracklayer, GenomicRanges, CSAR License: Artistic-2.0 Archs: i386, x64 MD5sum: 98910c1560cdbf2d79e444858fe35bcf NeedsCompilation: yes Title: Analysis of Variation in ChIP-seq using Functional PCA Statistics Description: The double aim of the package is to apply a functional version of principal component analysis (FPCA) to: (1) Process data in wiggle track format (WIG) commonly produced by ChIP-seq peak finders by applying FPCA over a set of selected candidate enriched regions. 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 the user to discriminate between binding regions in close proximity to each other and to narrow 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) Analyze differential variation when multiple ChIP-seq samples need to compared. The function 'narrowpeaksDiff' quantifies differences between the tag-enrichment, and uses non-parametric tests on the FPC scores for testing differences between conditions. biocViews: Visualization, ChIPseq, Transcription, Genetics Author: Pedro Madrigal , with contributions from Pawel Krajewski Maintainer: Pedro Madrigal source.ver: src/contrib/NarrowPeaks_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/NarrowPeaks_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NarrowPeaks_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/NarrowPeaks_1.6.0.tgz vignettes: vignettes/NarrowPeaks/inst/doc/NarrowPeaks.pdf, vignettes/NarrowPeaks/inst/doc/NarrowPeaksDiff.pdf vignetteTitles: NarrowPeaks Vignette I. Intra-sample variability: Splitting and narrowing down ChIP-seq peaks in a single experiment., NarrowPeaks Vignette II. Inter-sample variability: Analysis of variation in differential binding across ChIP-seq samples. hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NarrowPeaks/inst/doc/NarrowPeaks.R, vignettes/NarrowPeaks/inst/doc/NarrowPeaksDiff.R Package: ncdfFlow Version: 2.8.22 Depends: R (>= 2.14.0), flowCore, flowViz Imports: Biobase,flowCore,flowViz,methods,zlibbioc License: Artistic-2.0 Archs: i386, x64 MD5sum: a2a9b7da9cf5c2d6a77525118d21ec68 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_2.8.22.tar.gz win.binary.ver: bin/windows/contrib/3.0/ncdfFlow_2.8.22.zip win64.binary.ver: bin/windows64/contrib/3.0/ncdfFlow_2.8.22.zip mac.binary.ver: bin/macosx/contrib/3.0/ncdfFlow_2.8.22.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: 1.10.0 Depends: graph, R (>= 2.10.0) Imports: graph, KEGGgraph, methods, RBGL, RCytoscape, R.methodsS3 Suggests: Rgraphviz Enhances: DEGraph License: GPL-3 MD5sum: d253c2d988490447c01599451b112770 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, GraphsAndNetworks Author: Laurent Jacob Maintainer: Laurent Jacob source.ver: src/contrib/NCIgraph_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/NCIgraph_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NCIgraph_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/NCIgraph_1.10.0.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: 1.0.0 Depends: tcltk Imports: hwriter Suggests: AnnotationDbi, org.Hs.eg.db, KEGG.db, GO.db, reactome.db, RUnit, GOstats,hwriter License: GPL-2 MD5sum: bf2046ccb9ed95c82ce45bd9e0bfda88 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 Maintainer: Setia Pramana source.ver: src/contrib/neaGUI_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/neaGUI_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/neaGUI_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/neaGUI_1.0.0.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: 2.36.0 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: 83bc5a06c920d71bb64b4ceda795c0b6 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, Bioinformatics, GraphsAndNetworks, 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_2.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/nem_2.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/nem_2.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/nem_2.36.0.tgz vignettes: vignettes/nem/inst/doc/markowetz-thesis-2006.pdf, vignettes/nem/inst/doc/nem.pdf vignetteTitles: markowetz-thesis-2006.pdf, 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 Package: netresponse Version: 1.14.0 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: fa26e236769d33af3659c20f30b5cfe3 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, NetworkAnalysis, GraphsAndNetworks, DifferentialExpression, Microarray, Transcription Author: Leo Lahti, Olli-Pekka Huovilainen, Antonio Gusmao and Juuso Parkkinen Maintainer: Leo Lahti URL: http://netpro.r-forge.r-project.org/ source.ver: src/contrib/netresponse_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/netresponse_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/netresponse_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/netresponse_1.14.0.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: 1.2.1 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: 930fdc3cf3ad5b3f4386bbb8a1a75a09 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. Author: Jing Wang Maintainer: Bing Zhang source.ver: src/contrib/NetSAM_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/NetSAM_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/NetSAM_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/NetSAM_1.2.1.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: 1.4.0 Depends: R (>= 2.15.0), stats, utils, BMA License: GPL (>= 2) MD5sum: 4e51c2782d76eb6ee440ae921689bfe5 NeedsCompilation: no 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, Ka Yee Yeung, Adrian Raftery (with contributions from Kenneth Lo and Chad Young) Maintainer: Chris Fraley source.ver: src/contrib/networkBMA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/networkBMA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/networkBMA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/networkBMA_1.4.0.tgz vignettes: vignettes/networkBMA/inst/doc/networkBMA.pdf, vignettes/networkBMA/inst/doc/prc.pdf, vignettes/networkBMA/inst/doc/roc.pdf vignetteTitles: networkBMA, prc.pdf, roc.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: TRUE Rfiles: vignettes/networkBMA/inst/doc/networkBMA.R Package: nnNorm Version: 2.26.0 Depends: R(>= 2.2.0), marray Imports: graphics, grDevices, marray, methods, nnet, stats License: LGPL MD5sum: d2f85197eb97eccb166acb55058c1444 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_2.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/nnNorm_2.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/nnNorm_2.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/nnNorm_2.26.0.tgz vignettes: vignettes/nnNorm/inst/doc/nnNorm.pdf, vignettes/nnNorm/inst/doc/nnNormGuide.pdf vignetteTitles: nnNorm Tutorial, nnNormGuide.pdf 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: 2db41ff26ecb2214cccd2d83c7fbd388 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: Bioinformatics, RNAseq, DifferentialExpression, Visualization, HighThroughputSequencing 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/3.0/NOISeq_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NOISeq_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/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 Package: NormqPCR Version: 1.8.0 Depends: R(>= 2.14.0), stats, RColorBrewer, Biobase, methods, ReadqPCR, qpcR Imports: ReadqPCR License: LGPL-3 MD5sum: ff161819b179370b5b7b9f8ab989ef8d 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/NormqPCR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NormqPCR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/NormqPCR_1.8.0.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: NTW Version: 1.12.0 Depends: R (>= 2.3.0) Imports: mvtnorm, stats, utils License: GPL-2 MD5sum: 4bb73be09e703a47c93b168e705a15af 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/NTW_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NTW_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/NTW_1.12.0.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: 1.10.0 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: 58317e67e549990cae71e5108f4eca33 NeedsCompilation: no Title: Nucleosome positioning package for R Description: Nucleosome positioning for Tiling Arrays and Next Generation Sequencing Experiments biocViews: ChIPseq, Microarray, Sequencing, Genetics, HighThroughputSequencing Author: Oscar Flores, David Rossell Maintainer: Oscar Flores source.ver: src/contrib/nucleR_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/nucleR_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/nucleR_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/nucleR_1.10.0.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: 1.28.0 Imports: stats License: GPL-2 MD5sum: 9532e37cf224631d2f75e043696b6be2 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/nudge_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/nudge_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/nudge_1.28.0.tgz vignettes: vignettes/nudge/inst/doc/nudge.vignette.pdf, vignettes/nudge/inst/doc/nvignplot1.pdf, vignettes/nudge/inst/doc/nvignplot2.pdf, vignettes/nudge/inst/doc/nvignplot3.pdf, vignettes/nudge/inst/doc/nvignplot4.pdf vignetteTitles: nudge Overview, nvignplot1.pdf, nvignplot2.pdf, nvignplot3.pdf, nvignplot4.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/nudge/inst/doc/nudge.vignette.R Package: NuPoP Version: 1.12.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: 4a95b46a5bb39244e2cd2821d93f0946 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/NuPoP_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/NuPoP_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/NuPoP_1.12.0.tgz vignettes: vignettes/NuPoP/inst/doc/NuPoP-intro.pdf, vignettes/NuPoP/inst/doc/NuPoP-manual.pdf vignetteTitles: An R package for Nucleosome positioning prediction, NuPoP-manual.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/NuPoP/inst/doc/NuPoP-intro.R Package: occugene Version: 1.22.0 Depends: R (>= 2.0.0) License: GPL (>= 2) MD5sum: fd47620071bc626e42fb8308b878b169 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: Bioinformatics,Annotation,Pathways Author: Oliver Will Maintainer: Oliver Will source.ver: src/contrib/occugene_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/occugene_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/occugene_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/occugene_1.22.0.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: 1.36.0 Depends: R (>= 2.1.0), akima Imports: multtest (>= 1.7.3), graphics, grDevices, stats License: LGPL MD5sum: 9979823ea49697c5eae74f93a5c1f45c 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, Bioinformatics, DifferentialExpression, MultipleComparisons Author: Yudi Pawitan and Alexander Ploner Maintainer: Alexander Ploner source.ver: src/contrib/OCplus_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OCplus_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OCplus_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OCplus_1.36.0.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: 1.26.6 Depends: R (>= 2.15.0), BiocGenerics (>= 0.3.2), oligoClasses (>= 1.19.43), 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: cf7c044150911b0c76d45abb16435bb6 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, Bioinformatics, 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_1.26.6.tar.gz win.binary.ver: bin/windows/contrib/3.0/oligo_1.26.6.zip win64.binary.ver: bin/windows64/contrib/3.0/oligo_1.26.6.zip mac.binary.ver: bin/macosx/contrib/3.0/oligo_1.26.6.tgz vignettes: vignettes/oligo/inst/doc/ hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/oligo/inst/doc/primer.R dependsOnMe: ITALICS, pdInfoBuilder, SCAN.UPC, waveTiling importsMe: charm, cn.farms, frma, ITALICS suggestsMe: BiocGenerics, fastseg, frmaTools Package: oligoClasses Version: 1.24.0 Depends: R (>= 2.14), BiocGenerics (>= 0.3.2) Imports: BiocGenerics, 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: 4b1728c0c2e401dc911794adef35cabd 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/oligoClasses_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/oligoClasses_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/oligoClasses_1.24.0.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: 1.40.0 Depends: R (>= 2.10), methods, locfit, marray Imports: graphics, grDevices, limma, marray, methods, stats Suggests: convert License: GPL-2 MD5sum: be26e02c6cbf07cba0f196f613a18371 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OLIN_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OLIN_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OLIN_1.40.0.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: 1.36.0 Depends: R (>= 2.0.0), OLIN (>= 1.4.0) Imports: graphics, marray, OLIN, tcltk, tkWidgets, widgetTools License: GPL-2 MD5sum: eb9d62a0c7f2d079cca21b8a9a58afde 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OLINgui_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OLINgui_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OLINgui_1.36.0.tgz vignettes: vignettes/OLINgui/inst/doc/OLINgui.pdf, vignettes/OLINgui/inst/doc/OLINguiScreenshot.pdf vignetteTitles: Introduction to OLINgui, OLINguiScreenshot.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OLINgui/inst/doc/OLINgui.R Package: omicade4 Version: 1.2.2 Depends: R (>= 3.0.0), ade4 Imports: made4 Suggests: BiocStyle License: GPL-2 MD5sum: aae22e6def1b52c0fb55cb35cb4b1f77 NeedsCompilation: no Title: Multiple co-inertia analysis of omics datasets Description: Multiple co-inertia analysis of omics datasets biocViews: Software, Bioinformatics, Clustering, Classification, Multiple Comparisons Author: Chen Meng, Aedin Culhane, Amin M. Gholami. Maintainer: Chen Meng source.ver: src/contrib/omicade4_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/omicade4_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/omicade4_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/omicade4_1.2.2.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: 1.0.0 Depends: R (>= 2.14.0),methods,GenomicRanges Suggests: knitr License: GPL-2 MD5sum: 05cf78380008e58682913701453a75d6 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,Statistics,Annotation Author: Ying Hu Chunhua Yan Maintainer: Ying Hu VignetteBuilder: knitr source.ver: src/contrib/OmicCircos_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OmicCircos_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OmicCircos_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OmicCircos_1.0.0.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: 1.28.6 Depends: Biobase, affylmGUI, 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: 0f0c8f16fe0249bcaa98313398939636 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: HighThroughputSequencing, RNAseq, Microarray, OneChannel, DataImport, QualityControl, Preprocessing, Statistics, DifferentialExpression, GUI, MultipleComparisons 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_1.28.6.tar.gz win.binary.ver: bin/windows/contrib/3.0/oneChannelGUI_1.28.6.zip win64.binary.ver: bin/windows64/contrib/3.0/oneChannelGUI_1.28.6.zip mac.binary.ver: bin/macosx/contrib/3.0/oneChannelGUI_1.28.6.tgz vignettes: vignettes/oneChannelGUI/inst/doc/Exon-level.analysis.pdf, vignettes/oneChannelGUI/inst/doc/fignew42.pdf, vignettes/oneChannelGUI/inst/doc/gene-level.analysis.pdf, vignettes/oneChannelGUI/inst/doc/install.pdf, vignettes/oneChannelGUI/inst/doc/RNAseq.pdf, vignettes/oneChannelGUI/inst/doc/standAloneFunctions.pdf vignetteTitles: oneChannelGUI microarray exon-level data analysis overview, fignew42.pdf, oneChannelGUI microarray gene-level data analysis overview, oneChannelGUI Installation, oneChannelGUI miRNA and RNA-seq data analysis overview, oneChannelGUI Stand Alone Functions 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: 1.14.0 Depends: rJava, methods License: Apache License 2.0 MD5sum: 717e7079e8ff476dabd3eecedce0b381 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ontoCAT_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ontoCAT_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ontoCAT_1.14.0.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: 1.0.14 Depends: methods,flowWorkspace Imports: Biobase,gtools,flowCore,flowStats,flowClust,MASS,clue,plyr,RBGL,Rgraphviz,graph,data.table,ks,RColorBrewer,lattice,rrcov,R.utils Suggests: flowWorkspaceData, knitr, testthat, utils, tools Enhances: flowDensity License: Artistic-2.0 Archs: i386, x64 MD5sum: 1ff984683c6ddfcfa01c9dd691c99f49 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_1.0.14.tar.gz win.binary.ver: bin/windows/contrib/3.0/openCyto_1.0.14.zip win64.binary.ver: bin/windows64/contrib/3.0/openCyto_1.0.14.zip mac.binary.ver: bin/macosx/contrib/3.0/openCyto_1.0.14.tgz vignettes: vignettes/openCyto/inst/doc/ hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/openCyto/inst/doc/openCytoVignette.R htmlDocs: vignettes/openCyto/inst/doc/openCytoVignette.html htmlTitles: "An Introduction to the openCyto package" Package: OrderedList Version: 1.34.0 Depends: R (>= 2.1.0), Biobase (>= 1.5.12), twilight (>= 1.9.2), methods Imports: Biobase, graphics, methods, stats, twilight License: GPL (>= 2) MD5sum: 0d07778c07df98f919969fe8f12a258c 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, MultipleComparisons Author: Xinan Yang, Stefanie Scheid, Claudio Lottaz Maintainer: Claudio Lottaz URL: http://compdiag.molgen.mpg.de/software/index.shtml source.ver: src/contrib/OrderedList_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OrderedList_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OrderedList_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OrderedList_1.34.0.tgz vignettes: vignettes/OrderedList/inst/doc/bcb_logo.pdf, vignettes/OrderedList/inst/doc/tr_2006_01.pdf vignetteTitles: bcb_logo.pdf, 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: 1.4.0 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: 76755b127b1800d08a0562353c8722b0 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OrganismDbi_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OrganismDbi_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OrganismDbi_1.4.0.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: 1.10.0 Depends: methods,stats Suggests: xtable, Biobase License: Artistic-2.0 MD5sum: efabbab64fd78218003321dc66ebed76 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: Bioinformatics, DataRepresentation, Visualization, Design, QualityControl Author: Li Yan Maintainer: Li Yan URL: http://www.biomedcentral.com/1471-2164/13/689 source.ver: src/contrib/OSAT_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OSAT_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OSAT_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OSAT_1.10.0.tgz vignettes: vignettes/OSAT/inst/doc/gSetupBlock.pdf, vignettes/OSAT/inst/doc/gSetupOptimal.pdf, vignettes/OSAT/inst/doc/Meth450_Tracking_Sheet_onepage.pdf, vignettes/OSAT/inst/doc/OSAT.pdf, vignettes/OSAT/inst/doc/paired.pdf, vignettes/OSAT/inst/doc/random.pdf vignetteTitles: gSetupBlock.pdf, gSetupOptimal.pdf, Meth450_Tracking_Sheet_onepage.pdf, An introduction to OSAT, paired.pdf, random.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/OSAT/inst/doc/OSAT.R Package: OTUbase Version: 1.12.0 Depends: R (>= 2.9.0), methods, ShortRead (>= 1.4.0), Biobase, vegan Imports: Biostrings, ShortRead, IRanges License: Artistic-2.0 MD5sum: a8a7e306270b9e823d6575fd440db5be NeedsCompilation: no Title: Provides structure and functions for the analysis of OTU data Description: Provides a platform for Operational Taxonomic Unit based analysis biocViews: Bioinformatics, HighThroughputSequencingData, DataImport Author: Daniel Beck, Matt Settles, and James A. Foster Maintainer: Daniel Beck source.ver: src/contrib/OTUbase_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OTUbase_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OTUbase_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OTUbase_1.12.0.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: 1.26.0 Depends: R (>= 2.3.0), Biobase, quantreg License: GPL (>= 2) MD5sum: 538504f3858ad26447ef92d66fd41dc2 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, Bioinformatics Author: HyungJun Cho Maintainer: Sukwoo Kim URL: http://www.korea.ac.kr/~stat2242/ source.ver: src/contrib/OutlierD_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/OutlierD_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/OutlierD_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/OutlierD_1.26.0.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: 1.4.0 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: c8cfea182aff782d9a4af639fccc7420 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, Bioinformatics Author: Adi Laurentiu Tarca Maintainer: Adi Laurentiu Tarca source.ver: src/contrib/PADOG_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PADOG_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PADOG_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PADOG_1.4.0.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: 1.0.0 Depends: R (>= 2.10), Rgraphviz Imports: Rgraphviz Suggests: multcomp, reshape, rpart, plyr, xtable License: GPL (>=3.0) MD5sum: 9db824f678051223b0c38abb9752b35f 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: GraphsAndNetworks Author: Michal Burda Maintainer: Michal Burda source.ver: src/contrib/paircompviz_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/paircompviz_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/paircompviz_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/paircompviz_1.0.0.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: 1.26.0 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: 57d7f75d2cf4c82ff2ba3eed8d5bd6f7 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PAnnBuilder_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PAnnBuilder_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PAnnBuilder_1.26.0.tgz vignettes: vignettes/PAnnBuilder/inst/doc/fulltext.pdf, vignettes/PAnnBuilder/inst/doc/PAnnBuilder.pdf vignetteTitles: fulltext.pdf, Using the PAnnBuilder Package hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAnnBuilder/inst/doc/PAnnBuilder.R Package: panp Version: 1.32.0 Depends: R (>= 2.10), affy (>= 1.23.4), Biobase (>= 2.5.5) Imports: Biobase, methods, stats, utils Suggests: gcrma License: GPL (>= 2) MD5sum: 7ffd6d519c01dc3b0d85cabd15bdf2dd 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/panp_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/panp_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/panp_1.32.0.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: 1.8.0 Depends: R (>= 2.14), igraph Imports: graphics, grDevices, MASS, methods, pvclust, stats, utils Suggests: snow, RedeR License: Artistic-2.0 MD5sum: cf3535bef0a7cc20e91ce7b2960a6043 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, NetworkVisualization, GraphsAndNetworks, Clustering, CellBasedAssays Author: Xin Wang Maintainer: Xin Wang source.ver: src/contrib/PANR_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PANR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PANR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PANR_1.8.0.tgz vignettes: vignettes/PANR/inst/doc/fullPAN.pdf, vignettes/PANR/inst/doc/PANR-Vignette.pdf, vignettes/PANR/inst/doc/pvmodule.pdf, vignettes/PANR/inst/doc/sigmod.pdf vignetteTitles: fullPAN.pdf, Main vignette:Posterior association network and enriched functional gene modules inferred from rich phenotypes of gene perturbations, pvmodule.pdf, sigmod.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PANR/inst/doc/PANR-Vignette.R suggestsMe: RedeR Package: PAPi Version: 1.2.0 Depends: R (>= 2.15.2), svDialogs, KEGGREST License: GPL(>= 2) MD5sum: 902775a455933ebdbe6e491d6a149e2a 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PAPi_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PAPi_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PAPi_1.2.0.tgz vignettes: vignettes/PAPi/inst/doc/PAPi.pdf, vignettes/PAPi/inst/doc/PAPiPackage.pdf vignetteTitles: PAPi.pdf, Applying PAPi hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PAPi/inst/doc/PAPiPackage.R Package: parody Version: 1.20.0 Depends: R (>= 2.5.0), methods, tools, utils License: Artistic-2.0 MD5sum: 97a92fa5e1d167cdf5d35efd60da4883 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: Bioinformatics, MultipleComparisons Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/parody_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/parody_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/parody_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/parody_1.20.0.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: 1.0.0 Imports: R.oo, princurve License: Artistic-1.0 MD5sum: 4e1cd5fc66d3bac7f57ce7b936e10017 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: Bioinformatics, NetworkAnalysis Author: Yotam Drier Maintainer: Assif Yitzhaky source.ver: src/contrib/pathifier_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pathifier_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pathifier_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pathifier_1.0.0.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: 1.2.0 Depends: R (>= 1.14.0) Suggests: PathNetData, RUnit, BiocGenerics License: GPL-3 MD5sum: adbe5326ce55ad994f3bee40367eda8a 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, MultipleComparisons Author: Bhaskar Dutta , Anders Wallqvist , and Jaques Reifman Maintainer: Jason B. Smith source.ver: src/contrib/PathNet_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PathNet_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PathNet_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PathNet_1.2.0.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: 1.30.0 Depends: graph, Rgraphviz, RColorBrewer, cMAP, AnnotationDbi, methods Suggests: ALL, hgu95av2.db License: LGPL MD5sum: 3589c841e98a133a86385fa03059eaf7 NeedsCompilation: no Title: Render molecular pathways Description: build graphs from pathway databases, render them by Rgraphviz biocViews: GraphsAndNetworks, Pathways, NetworkVisualization Author: Li Long Maintainer: Li Long URL: http://www.bioconductor.org source.ver: src/contrib/pathRender_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pathRender_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pathRender_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pathRender_1.30.0.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: 1.2.4 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: 48100805da8d590d07328f53e5cfe9fe 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, GraphsAndNetworks, NetworkVisualization, GeneSetEnrichment, DifferentialExpression, GeneExpression, Microarray, RNAseq, Genetics, Metabolomics, Proteomics, Bioinformatics Author: Weijun Luo Maintainer: Weijun Luo URL: http://pathview.r-forge.r-project.org/ source.ver: src/contrib/pathview_1.2.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/pathview_1.2.4.zip win64.binary.ver: bin/windows64/contrib/3.0/pathview_1.2.4.zip mac.binary.ver: bin/macosx/contrib/3.0/pathview_1.2.4.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: 1.6.0 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: c79a16b44da43daa4c476034375b59dd 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pcaGoPromoter_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pcaGoPromoter_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pcaGoPromoter_1.6.0.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: 1.52.1 Depends: Biobase, methods, Rcpp (>= 0.8.7) Imports: BiocGenerics, MASS LinkingTo: Rcpp Suggests: matrixStats, lattice License: GPL (>= 3) Archs: i386, x64 MD5sum: d924f137acc4eb10ce1e4d0f45844836 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: Bioinformatics Author: Wolfram Stacklies, Henning Redestig, Kevin Wright Maintainer: Henning Redestig SystemRequirements: Rcpp source.ver: src/contrib/pcaMethods_1.52.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/pcaMethods_1.52.1.zip win64.binary.ver: bin/windows64/contrib/3.0/pcaMethods_1.52.1.zip mac.binary.ver: bin/macosx/contrib/3.0/pcaMethods_1.52.1.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: FALSE Rfiles: vignettes/pcaMethods/inst/doc/missingValues.R, vignettes/pcaMethods/inst/doc/outliers.R, vignettes/pcaMethods/inst/doc/pcaMethods.R dependsOnMe: DeconRNASeq Package: pcot2 Version: 1.30.0 Depends: R (>= 2.0.0), grDevices, Biobase, amap Suggests: multtest, hu6800.db, KEGG.db, mvtnorm License: GPL (>= 2) MD5sum: ab2f96cf23a33c1b965d66bebab8cffb 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pcot2_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pcot2_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pcot2_1.30.0.tgz vignettes: vignettes/pcot2/inst/doc/HowToUseGeneLocator.pdf, vignettes/pcot2/inst/doc/pcot2.pdf vignetteTitles: HowToUseGeneLocator.pdf, PCOT2 Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pcot2/inst/doc/pcot2.R Package: PCpheno Version: 1.24.0 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: 256fa116a1d3ad667c3c8936cf5e01e6 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: GraphsAndNetworks, Proteomics, NetworkAnalysis Author: Nolwenn Le Meur and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/PCpheno_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PCpheno_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PCpheno_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PCpheno_1.24.0.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: 1.26.0 Depends: R (>= 2.15.0), methods, Biobase (>= 2.17.7), RSQLite (>= 0.11.1), affxparser (>= 1.29.12), oligo (>= 1.21.5) Imports: Biostrings (>= 2.25.12), IRanges (>= 1.15.44) License: Artistic-2.0 Archs: i386, x64 MD5sum: c0e542866c1d8c4f2d9fa449f36a7202 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_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pdInfoBuilder_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pdInfoBuilder_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pdInfoBuilder_1.26.0.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: 1.34.0 Depends: Biobase (>= 1.4.22), R (>= 1.9.0), fibroEset, mda License: Artistic-2.0 MD5sum: 521ce38107222a2ca93ffb50306f5922 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pdmclass_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pdmclass_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pdmclass_1.34.0.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: PGSEA Version: 1.36.0 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: 26d8d8b71f8a7fe96c6d0da7f66b8d7d 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PGSEA_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PGSEA_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PGSEA_1.36.0.tgz vignettes: vignettes/PGSEA/inst/doc/PGSEA.pdf, vignettes/PGSEA/inst/doc/PGSEA2.pdf vignetteTitles: HOWTO: PGSEA, HOWTO: PGSEA Example Workflow hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/PGSEA/inst/doc/PGSEA.R, vignettes/PGSEA/inst/doc/PGSEA2.R dependsOnMe: GeneExpressionSignature Package: pgUtils Version: 1.34.0 Depends: R (>= 1.8.0), methods, RPostgreSQL (>= 0.1) Imports: methods, RPostgreSQL (>= 0.1) License: LGPL (>= 2) MD5sum: dc60f8c385768c9317ad159a6c41e8d3 NeedsCompilation: no Title: Utility functions for PostgreSQL databases Description: Functions for creating PostgreSQL database tables, with auto incrementing primary keys, selection of foreign keys to allow referential integrity and a logging mechanism. biocViews: Infrastructure Author: Johannes Rainer Maintainer: Johannes Rainer source.ver: src/contrib/pgUtils_1.34.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/pgUtils_1.34.0.tgz vignettes: vignettes/pgUtils/inst/doc/pgUtils.pdf vignetteTitles: pgUtils.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: maDB Package: phenoDist Version: 1.10.0 Depends: R (>= 2.9.0), imageHTS, e1071 Suggests: GOstats, MASS License: LGPL-2.1 MD5sum: 1b4b975ba2b2f665d82656011f4932ff 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, Bioinformatics 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/phenoDist_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/phenoDist_1.10.0.zip 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: 1.10.0 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: 039fd38b9cb939edd9ff5ab4dfe1c337 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, Bioinformatics, DifferentialExpression, MultipleComparisons, Clustering, Classification Author: Evarist Planet Maintainer: Evarist Planet source.ver: src/contrib/phenoTest_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/phenoTest_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/phenoTest_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/phenoTest_1.10.0.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: phyloseq Version: 1.6.1 Depends: R (>= 3.0.0), methods, ade4 (>= 1.5.2), picante (>= 1.5.2) Imports: ape (>= 3.0.8), biom (>= 0.3.9), Biostrings (>= 2.28.0), cluster (>= 1.14.4), foreach (>= 1.4), ggplot2 (>= 0.9.3.1), igraph (>= 0.6.5.2), multtest (>= 2.16.0), plyr (>= 1.8), reshape2 (>= 1.2.2), scales (>= 0.2.3), vegan (>= 2.0.7) Suggests: genefilter (>= 1.42.0), testthat (>= 0.7.1) Enhances: doParallel (>= 1.0.1) License: AGPL-3 MD5sum: 5b16b0c56b52a575f06a7e62c6623899 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 source.ver: src/contrib/phyloseq_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/phyloseq_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.0/phyloseq_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.0/phyloseq_1.6.1.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_basics.R Package: piano Version: 1.2.12 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: 4638aa3686a2a20b55bb0b742a4d4be0 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_1.2.12.tar.gz win.binary.ver: bin/windows/contrib/3.0/piano_1.2.12.zip win64.binary.ver: bin/windows64/contrib/3.0/piano_1.2.12.zip mac.binary.ver: bin/macosx/contrib/3.0/piano_1.2.12.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: 1.34.0 Imports: graphics, grDevices, MASS, stats, utils License: GPL (>= 2) MD5sum: 5d9cdbbbd41f0e7723d700f5d0ba18d6 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pickgene_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pickgene_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pickgene_1.34.0.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: 2.6.0 Depends: R (>= 2.14.0), BiocGenerics (>= 0.1.3) Imports: methods, stats4, IRanges, GenomicRanges, graphics, grDevices, stats, Rsamtools Suggests: ShortRead, rtracklayer, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: b1ce20535f71de1cb02890455744f524 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_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PICS_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PICS_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PICS_2.6.0.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: 2.6.0 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: abdaef006e68827964c1e85874306474 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, Statistics, Visualization, Sequencing Author: Xuekui Zhang , Raphael Gottardo , Sangsoon Woo, Maintainer: Renan Sauteraud source.ver: src/contrib/PING_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PING_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PING_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PING_2.6.0.tgz vignettes: vignettes/PING/inst/doc/PING-PE.pdf, vignettes/PING/inst/doc/PING.pdf vignetteTitles: Using PING with paired-end sequencing data, The PING users guide 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: 1.14.0 Depends: mvtnorm, methods, graphics, Matrix, dmt License: FreeBSD MD5sum: bbb88756f6708a0728ee0c01f19fd718 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pint_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pint_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pint_1.14.0.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: 1.28.0 Depends: methods, graph, RBGL Imports: graph, RBGL Suggests: Biobase, Rgraphviz, RCurl, BiocInstaller License: GPL-2 MD5sum: ffbb37b3012df0f4dce0b82ea7160cb0 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, GraphsAndNetworks Author: Seth Falcon Maintainer: Seth Falcon source.ver: src/contrib/pkgDepTools_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pkgDepTools_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pkgDepTools_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pkgDepTools_1.28.0.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: 1.20.0 Depends: R (>= 2.10), flowCore, flowViz, lattice, latticeExtra Imports: Biobase, flowCore, graphics, grDevices, lattice, MASS, methods, robustbase, stats, utils Suggests: gplots License: Artistic-2.0 MD5sum: 4919c5b37b5c1ed395860c7a483c3ef3 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plateCore_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plateCore_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plateCore_1.20.0.tgz vignettes: vignettes/plateCore/inst/doc/expDens.pdf, vignettes/plateCore/inst/doc/plateCoreVig.pdf vignetteTitles: expDens.pdf, 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: 1.0.0 Depends: R (>= 3.0.0) Imports: Streamer, DBI, RSQLite, methods, IRanges, reshape2, batch Suggests: RUnit, BiocGenerics License: GPL-3 MD5sum: af095fa25e383176286bdd8a6b3c58b0 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plethy_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plethy_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plethy_1.0.0.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: 1.34.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), MASS Imports: utils License: GPL-2 MD5sum: ac9c1a2c66835bc8df5d70a058448bf1 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plgem_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plgem_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plgem_1.34.0.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: 1.32.0 Depends: R (>= 2.0), methods Imports: affy, Biobase, methods License: GPL (>= 2) Archs: i386, x64 MD5sum: 947e20133d321a075ba6f27faab6e892 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plier_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plier_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plier_1.32.0.tgz hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE suggestsMe: piano, virtualArray Package: PLPE Version: 1.22.0 Depends: R (>= 2.6.2), Biobase (>= 2.5.5), LPE, MASS, methods License: GPL (>= 2) MD5sum: 6e025db30c342d7eb02925a57badba1a 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PLPE_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PLPE_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PLPE_1.22.0.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: 1.2.0 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: b0574bb95bb10fa5ae8c9ef48fe80be2 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). Author: Gwenael G.R. Leday Maintainer: Gwenael G.R. Leday to source.ver: src/contrib/plrs_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plrs_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plrs_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plrs_1.2.0.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: 1.22.0 Depends: R (>= 2.10), affy (>= 1.23.4) Imports: MASS, affy, graphics, splines, stats Suggests: limma License: GPL-2 Archs: i386, x64 MD5sum: 1709a37b49d7e836fe397c3b4dfae74d 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, Bioinformatics, DifferentialExpression Author: Magnus Astrand Maintainer: Magnus Astrand source.ver: src/contrib/plw_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/plw_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/plw_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/plw_1.22.0.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: 1.28.0 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: 8c517b0df5deeffe103345370a59fed7 NeedsCompilation: no Title: Protein-Protein Interaction Statistical Package Description: Tools for the analysis of protein interaction data. biocViews: Proteomics, GraphsAndNetworks, NetworkAnalysis Author: T. Chiang and D. Scholtens with contributions from W. Huber and L. Wang Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ppiStats_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ppiStats_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ppiStats_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ppiStats_1.28.0.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: 1.38.0 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: 12f8c8ed73409c482b5647830cf4c396 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/prada_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/prada_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/prada_1.38.0.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: 1.2.1 Depends: R (>= 2.14.0), Rsamtools (>= 1.13.1), affy Imports: parallel, methods, stats, GenomicRanges (>= 1.13.3), IRanges Suggests: prebsdata, hgu133plus2cdf, hgu133plus2probe License: Artistic-2.0 MD5sum: e532e44b8fc9a4e7c9a8b5c3e8518bb4 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, Bioinformatics, GeneExpression, Preprocessing Author: Karolis Uziela and Antti Honkela Maintainer: Karolis Uziela source.ver: src/contrib/prebs_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/prebs_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/prebs_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/prebs_1.2.1.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: 1.8.0 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: e265d0d81784a7eefe0cb50f131ea944 NeedsCompilation: no Title: Position RElated Data Anlysis Description: Package for the position related analysis of quantitative functional genomics data. biocViews: Software, CopyNumberVariants, GeneExpression, Genetics Author: Francesco Ferrari Maintainer: Francesco Ferrari source.ver: src/contrib/PREDA_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PREDA_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PREDA_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PREDA_1.8.0.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: 1.8.0 Depends: igraph, catnet Imports: penalized, RBGL, MASS Suggests: network, minet, knitr License: Artistic-2.0 MD5sum: 91d38830ad348a25af3d2243888e35e6 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: GraphsAndNetworks, 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_1.8.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/predictionet_1.8.0.tgz vignettes: vignettes/predictionet/inst/doc/predictionet-boxplotr2pwcvfig2.pdf, vignettes/predictionet/inst/doc/predictionet-boxplotstabpwcvfig2.pdf, vignettes/predictionet/inst/doc/predictionet-cytoscape.pdf, vignettes/predictionet/inst/doc/predictionet-edgecoldiffig.pdf, vignettes/predictionet/inst/doc/predictionet-edgestabfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabmccfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabmcctestfig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabr2fig.pdf, vignettes/predictionet/inst/doc/predictionet-genepredabr2testfig.pdf, vignettes/predictionet/inst/doc/predictionet-pn_webapp_ras.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvpriorsweightfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2fig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2predfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regnetcvtopo1topo2stabfig2.pdf, vignettes/predictionet/inst/doc/predictionet-regrnet_design.pdf, vignettes/predictionet/inst/doc/predictionet-regrnetopofig.pdf, vignettes/predictionet/inst/doc/predictionet.pdf vignetteTitles: predictionet-boxplotr2pwcvfig2.pdf, predictionet-boxplotstabpwcvfig2.pdf, predictionet-cytoscape.pdf, predictionet-edgecoldiffig.pdf, predictionet-edgestabfig.pdf, predictionet-genepredabmccfig.pdf, predictionet-genepredabmcctestfig.pdf, predictionet-genepredabr2fig.pdf, predictionet-genepredabr2testfig.pdf, predictionet-pn_webapp_ras.pdf, predictionet-regnetcvpriorsweightfig2.pdf, predictionet-regnetcvtopo1topo2fig2.pdf, predictionet-regnetcvtopo1topo2predfig2.pdf, predictionet-regnetcvtopo1topo2stabfig2.pdf, predictionet-regrnet_design.pdf, predictionet-regrnetopofig.pdf, predictionet hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/predictionet/inst/doc/predictionet.R Package: preprocessCore Version: 1.24.0 Depends: methods Imports: stats License: LGPL (>= 2) Archs: i386, x64 MD5sum: 24f786a32f51874968b0812f83f8854d 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/preprocessCore_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/preprocessCore_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/preprocessCore_1.24.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: affyPLM, cqn, crlmm, RefPlus, virtualArray importsMe: affy, AffyTiling, ChAMP, charm, cn.farms, ExiMiR, frma, frmaTools, lumi, MBCB, minfi, MSnbase, oligo, waveTiling suggestsMe: oneChannelGUI Package: PROcess Version: 1.38.0 Depends: Icens Imports: graphics, grDevices, Icens, stats, utils License: Artistic-2.0 MD5sum: e8a8b55e3f82b09c299d24500250f56c 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_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PROcess_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PROcess_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PROcess_1.38.0.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: 1.12.0 Depends: R (>= 2.10.1), methods Imports: methods, stats, graphics, utils Suggests: Biostrings License: GPL (>= 2) MD5sum: b8822c8364ddf73eaaac0b965071c83c 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/ source.ver: src/contrib/procoil_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/procoil_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/procoil_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/procoil_1.12.0.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: 1.0.2 Depends: R (>= 2.10), methods, WGCNA, MSnbase Imports: BiocGenerics, GOstats Suggests: RUnit License: GPL (>= 2) MD5sum: ed88a39c4fd1c6e59b6b4d642c67ee4f 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: Bioinformatics, GraphsAndNetworks, Software, Proteomics Author: David L Gibbs Maintainer: David L Gibbs source.ver: src/contrib/ProCoNA_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/ProCoNA_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.0/ProCoNA_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.0/ProCoNA_1.0.2.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: 1.2.1 Depends: R (>= 2.15), MSnbase (>= 1.7.23), MLInterfaces (>= 1.37.1), methods, Rcpp (>= 0.10.3) Imports: mclust, 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: 6b4210b70b97585493289e47510dc532 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: Bioinformatics, 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_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/pRoloc_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/pRoloc_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/pRoloc_1.2.1.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: 1.14.0 Depends: R (>= 2.11.0), Biobase, GSEABase Imports: Biobase, GSEABase, stats License: GPL (>= 2) MD5sum: 0e74dff8689eb77350393ffb06222c15 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, Bioinformatics, MultipleComparisons, GeneExpression Author: Stan Pounds , Xueyuan Cao Maintainer: Stan Pounds , Xueyuan Cao source.ver: src/contrib/PROMISE_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/PROMISE_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/PROMISE_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/PROMISE_1.14.0.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: 1.0.0 Depends: R (>= 2.15),fdrtool,st,samr,Biobase,limma,Mulcom,impute,MASS,qvalue Suggests: made4,affy License: GPL (>= 2) MD5sum: 5fe45b000c416100c02547b2111443b6 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: Bioinformatics, DifferentialExpression, MultipleComparisons, Proteomics Author: Sebastien Artigaud Maintainer: Sebastien Artigaud source.ver: src/contrib/prot2D_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/prot2D_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/prot2D_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/prot2D_1.0.0.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: 1.2.0 Depends: R (>= 2.15.2) Imports: graphics, stats Suggests: testthat License: GPL-3 MD5sum: 21feb23b6b69a78420b57a9d2103f79e 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/proteinProfiles_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/proteinProfiles_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/proteinProfiles_1.2.0.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: 1.0.1 Depends: R (>= 2.15.0), methods, IRanges, biomaRt, BiocGenerics Imports: RCurl License: Apache License 2.0 MD5sum: e3b9ee7a80675668ae896e4b42d4e150 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. Author: Paul Shannon Maintainer: Paul Shannon source.ver: src/contrib/PSICQUIC_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/PSICQUIC_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.0/PSICQUIC_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.0/PSICQUIC_1.0.1.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 Package: puma Version: 3.4.0 Depends: R (>= 2.10), Biobase (>= 2.5.5), affy (>= 1.23.4), graphics, grDevices, methods, stats, utils, mclust Imports: Biobase (>= 2.5.5), affy (>= 1.23.4),affyio Suggests: pumadata, affydata, snow, limma, annotate, ROCR License: LGPL Archs: i386, x64 MD5sum: afd1a142a1871a0f2335beb521677e05 NeedsCompilation: yes Title: Propagating Uncertainty in Microarray Analysis Description: Most analyses of Affymetrix GeneChip data 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. 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 and data manipulation 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_3.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/puma_3.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/puma_3.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/puma_3.4.0.tgz vignettes: vignettes/puma/inst/doc/puma-014.pdf, vignettes/puma/inst/doc/puma-015.pdf, vignettes/puma/inst/doc/puma-016.pdf, vignettes/puma/inst/doc/puma-022.pdf, vignettes/puma/inst/doc/puma-023.pdf, vignettes/puma/inst/doc/puma-024.pdf, vignettes/puma/inst/doc/puma.pdf vignetteTitles: puma-014.pdf, puma-015.pdf, puma-016.pdf, puma-022.pdf, puma-023.pdf, puma-024.pdf, puma.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE importsMe: tigre suggestsMe: tigre Package: pvac Version: 1.10.0 Depends: R (>= 2.8.0) Imports: affy (>= 1.20.0), stats, Biobase Suggests: pbapply, affydata, ALLMLL, genefilter License: LGPL (>= 2.0) MD5sum: 1832840d4f7943269465f01daa49204b 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: Bioinformatics, Microarray, OneChannel, QualityControl Author: Jun Lu and Pierre R. Bushel Maintainer: Jun Lu , Pierre R. Bushel source.ver: src/contrib/pvac_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pvac_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pvac_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pvac_1.10.0.tgz vignettes: vignettes/pvac/inst/doc/density.pdf, vignettes/pvac/inst/doc/pvac.pdf vignetteTitles: density.pdf, 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: 1.2.0 Depends: R (>= 2.15.1) Imports: Matrix, Biobase, vsn, lme4 Suggests: golubEsets License: LGPL (>= 2.0) MD5sum: e5a3caa7ebd328f3f0607aa80eec4379 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: Bioinformatics, Microarray, BatchEffectAssessment Author: Pierre Bushel Maintainer: Jianying LI source.ver: src/contrib/pvca_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/pvca_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/pvca_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/pvca_1.2.0.tgz vignettes: vignettes/pvca/inst/doc/pvca.pdf, vignettes/pvca/inst/doc/pvcaEstimate.pdf vignetteTitles: Batch effect estimation in Microarray data, pvcaEstimate.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/pvca/inst/doc/pvca.R Package: PWMEnrich Version: 2.6.2 Depends: methods, grid, BiocGenerics, Biostrings, Imports: seqLogo, gdata, evd Suggests: MotifDb, BSgenome.Dmelanogaster.UCSC.dm3, PWMEnrich.Dmelanogaster.background, testthat, gtools, parallel License: GPL-3 MD5sum: 0f1cbc9a0d355f8bb3bc08a4c05d4bb8 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: Bioinformatics, SequenceMatching, GenomicSequence, Software Author: Robert Stojnic, Diego Diez Maintainer: Robert Stojnic source.ver: src/contrib/PWMEnrich_2.6.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/PWMEnrich_2.6.2.zip win64.binary.ver: bin/windows64/contrib/3.0/PWMEnrich_2.6.2.zip mac.binary.ver: bin/macosx/contrib/3.0/PWMEnrich_2.6.2.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: 1.0.0 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: 9cb41a33b7678d1fc7c0680999c3f351 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, Bioinformatics, QualityControl, Proteomics, Microarray, MassSpectrometry, Visualisation Author: Laurent Gatto Maintainer: Laurent Gatto URL: https://github.com/lgatto/qcmetrics VignetteBuilder: knitr source.ver: src/contrib/qcmetrics_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/qcmetrics_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/qcmetrics_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/qcmetrics_1.0.0.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: qpcrNorm Version: 1.20.0 Depends: methods, Biobase, limma, affy License: LGPL (>= 2) MD5sum: 707caaabc9d1f0f1bb5d1af63cea9b0d 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/qpcrNorm_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/qpcrNorm_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/qpcrNorm_1.20.0.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: 1.18.9 Depends: R (>= 3.0.0) Imports: methods, parallel, Matrix (>= 1.0), annotate, graph (>= 1.40.1), 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: ef94be795d8072e92cb3dcf8a8b24365 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, GraphsAndNetworks, GeneRegulation Author: R. Castelo and A. Roverato Maintainer: Robert Castelo URL: http://functionalgenomics.upf.edu/qpgraph source.ver: src/contrib/qpgraph_1.18.9.tar.gz win.binary.ver: bin/windows/contrib/3.0/qpgraph_1.18.9.zip win64.binary.ver: bin/windows64/contrib/3.0/qpgraph_1.18.9.zip mac.binary.ver: bin/macosx/contrib/3.0/qpgraph_1.18.9.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: 1.16.0 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: 49b5f803950f093969d5727ca1217892 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, HighThroughputSequencing Author: Vince Buffalo Maintainer: Vince Buffalo URL: http://github.com/vsbuffalo/qrqc source.ver: src/contrib/qrqc_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/qrqc_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/qrqc_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/qrqc_1.16.0.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: 1.6.21 Depends: R (>= 2.14.0),flowCore,flowViz,ncdfFlow,flowWorkspace (>= 3.8.37), data.table,reshape Imports: MASS,hwriter,RSVGTipsDevice,lattice,stats4,flowCore,flowViz,methods,flowWorkspace,latticeExtra,grDevices,tools, Biobase,XML License: Artistic-2.0 MD5sum: cebaea7472e441c5c572367cdaf059a9 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_1.6.21.tar.gz win.binary.ver: bin/windows/contrib/3.0/QUALIFIER_1.6.21.zip win64.binary.ver: bin/windows64/contrib/3.0/QUALIFIER_1.6.21.zip mac.binary.ver: bin/macosx/contrib/3.0/QUALIFIER_1.6.21.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: 1.28.0 Depends: R(>= 2.10.0), quantreg, grid License: GPL-2 MD5sum: 2d43e9bba962464de01959d4dbedbae0 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, CopyNumberVariants Author: Jan Oosting, Paul Eilers, Renee Menezes Maintainer: Jan Oosting source.ver: src/contrib/quantsmooth_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/quantsmooth_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/quantsmooth_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/quantsmooth_1.28.0.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: 1.2.2 Depends: R (>= 2.15.0), 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) LinkingTo: Rsamtools Suggests: Rsamtools, rtracklayer, Gviz, RUnit, BiocStyle License: GPL-2 Archs: i386, x64 MD5sum: fd8340d265ada62c649a13471dadb901 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, HighThroughputSequencing, ChIPseq, RNAseq, Methylseq Author: Anita Lerch, Dimos Gaiditzis and Michael Stadler Maintainer: Michael Stadler source.ver: src/contrib/QuasR_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/QuasR_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/QuasR_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/QuasR_1.2.2.tgz vignettes: vignettes/QuasR/inst/doc/QuasR-Overview.pdf vignetteTitles: An introduction to QuasR hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/QuasR/inst/doc/QuasR-Overview.R Package: qusage Version: 1.2.0 Depends: R (>= 2.10), limma (>= 3.14), methods Imports: utils, Biobase License: GPL (>= 2) MD5sum: 87a2e1a0a834b899cc71ada4587aac93 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: Enrichment, GeneSetEnrichment, Bioinformatics, Microarrays, 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/qusage_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/qusage_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/qusage_1.2.0.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: 1.36.0 Imports: graphics, grDevices, stats, tcltk License: LGPL MD5sum: 0bbc608c83ca94444ed1a902ecb9ed05 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: MultipleComparisons Author: Alan Dabney and John D. Storey , with assistance from Gregory R. Warnes Maintainer: John D. Storey source.ver: src/contrib/qvalue_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/qvalue_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/qvalue_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/qvalue_1.36.0.tgz vignettes: vignettes/qvalue/inst/doc/manual.pdf, vignettes/qvalue/inst/doc/pHist.pdf, vignettes/qvalue/inst/doc/qHist.pdf, vignettes/qvalue/inst/doc/qPlots.pdf, vignettes/qvalue/inst/doc/qvalue.pdf vignetteTitles: manual.pdf, pHist.pdf, qHist.pdf, qPlots.pdf, qvalue Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/qvalue/inst/doc/qvalue.R dependsOnMe: anota, CancerMutationAnalysis, DEGseq, DrugVsDisease, netresponse, SSPA, webbioc importsMe: anota, DOSE, msmsTests, ReactomePA, sRAP, synapter, trigger, webbioc suggestsMe: LBE, maanova, PREDA Package: r3Cseq Version: 1.8.0 Depends: GenomicRanges,Rsamtools,data.table,rtracklayer,VGAM,qvalue,RColorBrewer,sqldf,methods Suggests: BSgenome.Mmusculus.UCSC.mm9,BSgenome.Hsapiens.UCSC.hg18,BSgenome.Hsapiens.UCSC.hg19 License: GPL-3 MD5sum: fa5f5372e5e8271668e8517d39291993 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, HighThroughputSequencing Author: Supat Thongjuea, Bergen Center for Computational Science, Norway Maintainer: Supat Thongjuea URL: http://r3cseq.genereg.net source.ver: src/contrib/r3Cseq_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/r3Cseq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/r3Cseq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/r3Cseq_1.8.0.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: 1.12.0 Depends: R (>= 2.12.0), BiocGenerics, Biobase, Biostrings (>= 2.29.2), BSgenome.Scerevisiae.UCSC.sacCer2,TeachingDemos Imports: BiocGenerics (>= 0.1.3), Biobase (>= 2.15.1), biomaRt, Biostrings, BSgenome, IRanges (>= 1.19.5), XVector, methods, R2HTML, Rsamtools, ShortRead, VariantAnnotation, xtable, tools Suggests: rtracklayer, ShortRead, Rsamtools, BSgenome.Hsapiens.UCSC.hg19 License: LGPL-3 Archs: i386, x64 MD5sum: d7215618203a7cb1fe37fecb6b513214 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: HighThroughputSequencing, Infrastructure, DataImport, DataRepresentation, Visualization, QualityControl, ReportWriting Author: Hans-Ulrich Klein, Christoph Bartenhagen, Christian Ruckert Maintainer: Hans-Ulrich Klein source.ver: src/contrib/R453Plus1Toolbox_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/R453Plus1Toolbox_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/R453Plus1Toolbox_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/R453Plus1Toolbox_1.12.0.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: 1.36.0 Depends: R(>= 2.5.0) License: GPL (>= 2) Archs: i386, x64 MD5sum: 05bef34de16388e322678661c4eabef3 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rama_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rama_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rama_1.36.0.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: 1.8.1 Depends: gsubfn,methods Imports: igraph,RCurl,png,RCytoscape,graph License: Artistic-2.0 MD5sum: 24b172c641a540cf75bab63b54252d40 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, NetworkVisualization, GraphsAndNetworks, Classification, ConnectTools Author: Markus Schroeder, Daniel Gusenleitner, John Quackenbush, Aedin Culhane, Benjamin Haibe-Kains Maintainer: Markus Schroeder source.ver: src/contrib/RamiGO_1.8.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/RamiGO_1.8.1.zip win64.binary.ver: bin/windows64/contrib/3.0/RamiGO_1.8.1.zip mac.binary.ver: bin/macosx/contrib/3.0/RamiGO_1.8.1.tgz vignettes: vignettes/RamiGO/inst/doc/RamiGO.pdf vignetteTitles: RamiGO: An Introduction (HowTo) hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RamiGO/inst/doc/RamiGO.R Package: randPack Version: 1.8.0 Depends: methods Imports: Biobase License: Artistic 2.0 MD5sum: 6a8ee55bbe53f266af7d74ac052f7a37 NeedsCompilation: no Title: Randomization routines for Clinical Trials Description: A suite of classes and functions for randomizing patients in clinical trials. biocViews: Statistics Author: Vincent Carey and Robert Gentleman Maintainer: Robert Gentleman source.ver: src/contrib/randPack_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/randPack_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/randPack_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/randPack_1.8.0.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: 2.34.0 Depends: R (>= 1.9.0) Imports: graphics License: file LICENSE License_restricts_use: yes MD5sum: 36e489edc0da616ba424cb47e300fc42 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_2.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RankProd_2.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RankProd_2.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RankProd_2.34.0.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: RbcBook1 Version: 1.30.0 Depends: R (>= 2.10), Biobase, graph, rpart License: Artistic-2.0 MD5sum: d6287b11433a15f23cd4df5ef1b513be 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RbcBook1_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RbcBook1_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RbcBook1_1.30.0.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: 1.38.0 Depends: graph, methods Imports: methods Suggests: Rgraphviz, XML License: Artistic-2.0 Archs: i386, x64 MD5sum: f7d8dc8c3bede64e8d41d25b951f304e 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: GraphsAndNetworks, NetworkAnalysis Author: Vince Carey , Li Long , R. Gentleman Maintainer: Bioconductor Package Maintainer URL: http://www.bioconductor.org source.ver: src/contrib/RBGL_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RBGL_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RBGL_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RBGL_1.38.0.tgz vignettes: vignettes/RBGL/inst/doc/filedep.pdf, vignettes/RBGL/inst/doc/RBGL.pdf vignetteTitles: filedep.pdf, RBGL Overview hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RBGL/inst/doc/RBGL.R dependsOnMe: apComplex, BioNet, CellNOptR, joda, pkgDepTools, RDAVIDWebService, RpsiXML importsMe: biocViews, CAMERA, Category, clipper, DEGraph, flowWorkspace, GeneAnswers, GOSim, GOstats, NCIgraph, nem, OrganismDbi, pkgDepTools, predictionet, Streamer suggestsMe: BiocCaseStudies, DEGraph, graph, KEGGgraph, VariantTools Package: RBioinf Version: 1.22.0 Depends: graph, methods Suggests: Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: 1f91e27b15865e1178ce4ba0593c1b30 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RBioinf_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RBioinf_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RBioinf_1.22.0.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: 1.2.0 Imports: XML Suggests: Rgraphviz, RCurl, graph, RUnit, BiocGenerics License: GPL (>= 2) MD5sum: 07cf590d2a9da7ef7fbfec7992892416 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. Author: Frank Kramer Maintainer: Frank Kramer URL: https://github.com/frankkramer/rBiopaxParser source.ver: src/contrib/rBiopaxParser_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rBiopaxParser_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rBiopaxParser_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rBiopaxParser_1.2.0.tgz vignettes: vignettes/rBiopaxParser/inst/doc/biopax2classgraph.pdf, vignettes/rBiopaxParser/inst/doc/biopaxsimple.pdf, vignettes/rBiopaxParser/inst/doc/mergedpw.pdf, vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.pdf, vignettes/rBiopaxParser/inst/doc/segclock.pdf, vignettes/rBiopaxParser/inst/doc/wntplot.pdf vignetteTitles: biopax2classgraph.pdf, biopaxsimple.pdf, mergedpw.pdf, rBiopaxParser Vignette, segclock.pdf, wntplot.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rBiopaxParser/inst/doc/rBiopaxParserVignette.R Package: Rbowtie Version: 1.2.0 Suggests: parallel License: Artistic-1.0 | file LICENSE MD5sum: 525c7d2a1a16ca268d4a0ecf371bd9b9 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: HighThroughputSequencing Author: Florian Hahne, Anita Lerch, Michael B Stadler Maintainer: Michael Stadler source.ver: src/contrib/Rbowtie_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rbowtie_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rbowtie_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rbowtie_1.2.0.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: 2.20.0 Depends: R (>= 2.5.0), Biobase (>= 2.5.5), survival License: GPL (>= 2) MD5sum: 2e7976e8ec8dc0e8c4953cd861fc5228 NeedsCompilation: no Title: Robust likelihood-based survival modeling with microarray data Description: This package selects genes associated with survival. biocViews: Microarray, Bioinformatics 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_2.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rbsurv_2.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rbsurv_2.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rbsurv_2.20.0.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: 1.4.0 Depends: R (>= 2.14.0), methods, GenomicRanges, baySeq, Rsamtools Imports: graphics, IRanges, rgl Suggests: limma, biomaRt, RUnit, BiocGenerics License: GPL-2 MD5sum: 6c22204c9f391e18b03763c612675dec 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rcade_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rcade_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rcade_1.4.0.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: 1.8.0 License: GPL (>=3) MD5sum: c81df93d6c39747e623b9a5276e3d94b 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RCASPAR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RCASPAR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RCASPAR_1.8.0.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: 2.0.2 Depends: Rcpp (>= 0.9.13), R (>= 2.15.0), methods, ChemmineR LinkingTo: Rcpp Suggests: apcluster, kernlab License: GPL (>= 2.1) Archs: i386, x64 MD5sum: 46be0391d9af98a585a2dea59e9f46a8 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_2.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rchemcpp_2.0.2.zip win64.binary.ver: bin/windows64/contrib/3.0/Rchemcpp_2.0.2.zip mac.binary.ver: bin/macosx/contrib/3.0/Rchemcpp_2.0.2.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: 2.2.0 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: 16b9161395079104b784081246669153 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_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RchyOptimyx_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RchyOptimyx_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RchyOptimyx_2.2.0.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: RCytoscape Version: 1.12.0 Depends: R (>= 2.14.0), graph (>= 1.31.0), XMLRPC (>= 0.2.4) Imports: methods, XMLRPC, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: a2d49dbd8b8497b0f276697a3f4e3a32 NeedsCompilation: no Title: Display and manipulate graphs in Cytoscape Description: Interactvive viewing and exploration of graphs, connecting R to Cytoscape. biocViews: NetworkVisualization, GraphsAndNetworks, ConnectTools Author: Paul Shannon Maintainer: Paul Shannon URL: http://rcytoscape.systemsbiology.net source.ver: src/contrib/RCytoscape_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RCytoscape_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RCytoscape_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RCytoscape_1.12.0.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 Package: RDAVIDWebService Version: 1.0.0 Depends: R (>= 2.14.1), methods, rJava, ggplot2, GO.db, graph, Category, GOstats, RBGL Suggests: Rgraphviz License: GPL (>=2) MD5sum: 2f9894b9d24894af186fe41ef542cfbc 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: Bioinformatics, Visualization, AssayDomains, 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RDAVIDWebService_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RDAVIDWebService_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RDAVIDWebService_1.0.0.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 Package: Rdisop Version: 1.22.1 Depends: R (>= 2.0.0), RcppClassic LinkingTo: RcppClassic, Rcpp Suggests: RUnit License: GPL-2 Archs: i386, x64 MD5sum: 66b668878d1f7c99de40b71c489fe14b 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_1.22.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rdisop_1.22.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Rdisop_1.22.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Rdisop_1.22.1.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: 1.12.0 Depends: R (>= 2.9.0),rgl Imports: graphics, grDevices, methods, stats, MASS, rgl Suggests: golubEsets License: GPL (>= 2) MD5sum: 8e12c8dffdb864d7750b10345b2ff3a1 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,ClusterValidation,Microarray Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RDRToolbox_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RDRToolbox_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RDRToolbox_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RDRToolbox_1.12.0.tgz vignettes: vignettes/RDRToolbox/inst/doc/plot3D.pdf, vignettes/RDRToolbox/inst/doc/RDRToolbox-003.pdf, vignettes/RDRToolbox/inst/doc/SwissRoll.pdf, vignettes/RDRToolbox/inst/doc/vignette.pdf vignetteTitles: plot3D.pdf, RDRToolbox-003.pdf, SwissRoll.pdf, 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: 1.6.1 Imports: methods, AnnotationDbi, reactome.db, org.Hs.eg.db, DOSE, stats4, plyr, igraph, qvalue, graphics, graphite Suggests: clusterProfiler, GOSemSim, knitr License: GPL-2 MD5sum: afd3163f1a2a64df4213750faad23a44 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: Bioinformatics, Pathways, Visualization, Annotation Author: Guangchuang Yu Maintainer: Guangchuang Yu VignetteBuilder: knitr source.ver: src/contrib/ReactomePA_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/ReactomePA_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.0/ReactomePA_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.0/ReactomePA_1.6.1.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: clusterProfiler, DOSE Package: ReadqPCR Version: 1.8.0 Depends: R(>= 2.14.0), Biobase, methods, affy Imports: Biobase Suggests: qpcR License: LGPL-3 MD5sum: 01b020a4bef9bb7a920eb8efdfe7da45 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ReadqPCR_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ReadqPCR_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ReadqPCR_1.8.0.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 importsMe: NormqPCR Package: reb Version: 1.40.0 Depends: R (>= 2.0), Biobase, idiogram (>= 1.5.3) License: GPL-2 Archs: i386, x64 MD5sum: 388d82c85fedc848e1fedd68dba6635c NeedsCompilation: yes Title: Regional Expression Biases Description: A set of functions to dentify regional expression biases biocViews: Microarray, CopyNumberVariants, Visualization Author: Kyle A. Furge and Karl Dykema Maintainer: Karl J. Dykema source.ver: src/contrib/reb_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/reb_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/reb_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/reb_1.40.0.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: 1.10.1 Depends: R (>= 2.15), methods, igraph Imports: RCurl, XML, XMLRPC, rJava Suggests: PANR, pvclust License: GPL (>= 2) MD5sum: e1c9a088a0501fb5cee2f55ce9014640 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. It implements a callback engine by using a low-level R-to-Java interface to build and run common plugins. In this sense, RedeR takes advantage of R to run robust statistics, while the R-to-Java interface bridges the gap between network analysis and visualization. biocViews: GraphsAndNetworks, NetworkVisualization, Networks, Software, Visualization Author: Mauro Castro, Xin Wang, Florian Markowetz Maintainer: Mauro Castro URL: http://genomebiology.com/2012/13/4/R29 source.ver: src/contrib/RedeR_1.10.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/RedeR_1.10.1.zip win64.binary.ver: bin/windows64/contrib/3.0/RedeR_1.10.1.zip mac.binary.ver: bin/macosx/contrib/3.0/RedeR_1.10.1.tgz vignettes: vignettes/RedeR/inst/doc/fig1.pdf, vignettes/RedeR/inst/doc/fig2.pdf, vignettes/RedeR/inst/doc/fig3.pdf, vignettes/RedeR/inst/doc/fig4.pdf, vignettes/RedeR/inst/doc/fig5a.pdf, vignettes/RedeR/inst/doc/fig5b.pdf, vignettes/RedeR/inst/doc/fig5c.pdf, vignettes/RedeR/inst/doc/RedeR.pdf vignetteTitles: fig1.pdf, fig2.pdf, fig3.pdf, fig4.pdf, fig5a.pdf, fig5b.pdf, fig5c.pdf, 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: 1.8.0 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: ee3ac17d4578765e9c77578c49d4de70 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/REDseq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/REDseq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/REDseq_1.8.0.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: RefPlus Version: 1.32.0 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: 6ff6efa78bbf88e84c346625c53db3a5 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RefPlus_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RefPlus_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RefPlus_1.32.0.tgz vignettes: vignettes/RefPlus/inst/doc/An_Exploration_of_Extensions_to_the_RMA_Algorithm.pdf, vignettes/RefPlus/inst/doc/Extensions_to_RMA_Algorithm.pdf, vignettes/RefPlus/inst/doc/RefPlus.pdf vignetteTitles: An_Exploration_of_Extensions_to_the_RMA_Algorithm.pdf, Extensions_to_RMA_Algorithm.pdf, RefPlus Manual hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RefPlus/inst/doc/RefPlus.R Package: Repitools Version: 1.8.6 Depends: R (>= 3.0.0), methods, BiocGenerics (>= 0.8.0) Imports: IRanges (>= 1.20.0), GenomicRanges, 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: 4d282ce57c767fc70c285f1e0fa284c6 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_1.8.6.tar.gz win.binary.ver: bin/windows/contrib/3.0/Repitools_1.8.6.zip win64.binary.ver: bin/windows64/contrib/3.0/Repitools_1.8.6.zip mac.binary.ver: bin/macosx/contrib/3.0/Repitools_1.8.6.tgz vignettes: vignettes/Repitools/inst/doc/qc-cpgPlot.pdf, vignettes/Repitools/inst/doc/qc-enrPlot.pdf, vignettes/Repitools/inst/doc/Repitools_vignette.pdf, vignettes/Repitools/inst/doc/visualisations-binPlotsHeatmap.pdf, vignettes/Repitools/inst/doc/visualisations-binPlotsLine.pdf, vignettes/Repitools/inst/doc/visualisations-cluPlots3.pdf, vignettes/Repitools/inst/doc/visualisations-profPlots.pdf vignetteTitles: qc-cpgPlot.pdf, qc-enrPlot.pdf, Using Repitools for Epigenomic Sequencing Data, visualisations-binPlotsHeatmap.pdf, visualisations-binPlotsLine.pdf, visualisations-cluPlots3.pdf, visualisations-profPlots.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Repitools/inst/doc/Repitools_vignette.R Package: ReportingTools Version: 2.2.0 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, ggplot2, ggbio, DESeq2, IRanges Suggests: RUnit, ggplot2, ggbio, ALL, hgu95av2.db, org.Mm.eg.db, knitr License: Artistic-2.0 MD5sum: e97be8a67fdfa714b6860c2dd2bdcdf3 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. biocViews: Bioinformatics, Software, Visualization, Microarray, RNAseq, GO Author: Jason A. Hackney, Melanie Huntley, Jessica L. Larson, Christina Chaivorapol, Gabriel Becker, and Josh Kaminker Maintainer: Jason A. Hackney , Gabriel Becker VignetteBuilder: utils, knitr source.ver: src/contrib/ReportingTools_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ReportingTools_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ReportingTools_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ReportingTools_2.2.0.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 suggestsMe: GSEABase Package: ReQON Version: 1.8.0 Depends: R (>= 2.15.0), Rsamtools, seqbias Imports: rJava, graphics, stats, utils, grDevices License: GPL-2 MD5sum: 33c3e3273235b6dba9f25cce9029ec24 NeedsCompilation: no Title: Recalibrating Quality Of Nucleotides Description: Algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format. biocViews: Sequencing, HighThroughputSequencing, Preprocessing, QualityControl Author: Christopher Cabanski, Keary Cavin, Chris Bizon Maintainer: Christopher Cabanski SystemRequirements: Java version >= 1.6 source.ver: src/contrib/ReQON_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ReQON_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ReQON_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ReQON_1.8.0.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: 1.36.0 Depends: R (>= 1.9.0), Biobase, AnnotationDbi (>= 1.4.0) Suggests: human.db0, mouse.db0, rat.db0 License: LGPL MD5sum: 646d4e1b1dcbf6c033653fb359a4b3c1 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Resourcerer_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Resourcerer_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Resourcerer_1.36.0.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: 1.0.0 Depends: Rsamtools, GenomicRanges, IRanges, data.table, methods, parallel Suggests: BiocStyle License: GPL (>=2 ) Archs: i386, x64 MD5sum: 85c34616afb0e444d42be57fd3cc322d 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: Bioinformatics, 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rfPred_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rfPred_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rfPred_1.0.0.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: 2.10.0 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: 484ad809b3c2633dc6559faf845a363d 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_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rGADEM_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rGADEM_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rGADEM_2.10.0.tgz vignettes: vignettes/rGADEM/inst/doc/rGADEM.pdf vignetteTitles: The rGADEM users guide hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/rGADEM/inst/doc/rGADEM.R importsMe: MotIV Package: RGalaxy Version: 1.6.0 Depends: XML, methods, tools, optparse, digest, Imports: BiocGenerics, Biobase, roxygen2 Suggests: RUnit, hgu95av2.db, knitr, formatR, Rserve Enhances: RSclient License: Artistic-2.0 MD5sum: c19da7d923e6d2217148008d5e8c4f1b 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: The Bioconductor Dev Team Maintainer: Bioconductor Package Maintainer VignetteBuilder: knitr source.ver: src/contrib/RGalaxy_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RGalaxy_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RGalaxy_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RGalaxy_1.6.0.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: 2.6.0 Depends: R (>= 2.6.0), methods, utils, graph, grid Imports: stats4, graphics, grDevices Suggests: RUnit, BiocGenerics, XML License: EPL Archs: i386, x64 MD5sum: 8d7c6d1816ddcdc403c32a972046ebd7 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: GraphsAndNetworks, NetworkVisualization Author: Jeff Gentry, Li Long, Robert Gentleman, Seth Falcon, Florian Hahne, Deepayan Sarkar, Kasper Daniel Hansen Maintainer: Kasper Daniel Hansen SystemRequirements: optionally Graphviz (>= 2.16) source.ver: src/contrib/Rgraphviz_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rgraphviz_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rgraphviz_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rgraphviz_2.6.0.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: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rgraphviz/inst/doc/newRgraphvizInterface.R, vignettes/Rgraphviz/inst/doc/Rgraphviz.R dependsOnMe: biocGraph, BioMVCClass, CellNOptR, flowMerge, GOFunction, hyperdraw, MineICA, nem, netresponse, paircompviz, pathRender, ROntoTools, SplicingGraphs, TDARACNE importsMe: apComplex, biocGraph, DEGraph, GOFunction, nem, paircompviz, pathview, qpgraph, RchyOptimyx, SplicingGraphs suggestsMe: altcdfenvs, annotate, BiocCaseStudies, Category, CNORfeeder, CNORfuzzy, ddgraph, DEGraph, flowCore, flowMerge, 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: 2.6.0 Depends: methods Imports: zlibbioc Suggests: bit64,BiocStyle License: Artistic-2.0 Archs: i386, x64 MD5sum: d654434180e19bab6c2a5a2d0993b923 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 Author: Bernd Fischer, Gregoire Pau Maintainer: Bernd Fischer SystemRequirements: GNU make source.ver: src/contrib/rhdf5_2.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rhdf5_2.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rhdf5_2.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rhdf5_2.6.0.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 importsMe: h5vc Package: rHVDM Version: 1.28.0 Depends: R (>= 2.10), R2HTML (>= 1.5), affy (>= 1.23.4), minpack.lm (>= 1.0-5), Biobase (>= 2.5.5) License: GPL-2 MD5sum: 788d48d62e02be778af337db4dcfc2a8 NeedsCompilation: no Title: Hidden Variable Dynamic Modeling Description: A R implementation of HVDM (Genome Biol 2006, V7(3) R25) biocViews: Microarray, GraphsAndNetworks, Transcription, Classification, NetworkInference Author: Martino Barenco Maintainer: Martino Barenco source.ver: src/contrib/rHVDM_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rHVDM_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rHVDM_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rHVDM_1.28.0.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: 1.26.1 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: 4e73b8d528715f19067e89ad767a4b24 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_1.26.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Ringo_1.26.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Ringo_1.26.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Ringo_1.26.1.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: 1.2.0 Depends: R (>= 2.15), methods, IRanges, GenomicRanges, rtracklayer, Rsamtools Suggests: biomaRt, ChIPpeakAnno, parallel, GenomicFeatures License: GPL-2 MD5sum: 0ba7993c762d2303b398e0029846c092 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: HighThroughputSequencing, RIPseq Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/software.html source.ver: src/contrib/RIPSeeker_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RIPSeeker_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RIPSeeker_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RIPSeeker_1.2.0.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: 1.4.1 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: 315e07bbda76208b686f00ca8564d3c6 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: source.ver: src/contrib/Risa_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Risa_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Risa_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Risa_1.4.1.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: 1.24.0 Depends: R (>= 2.1.0) Imports: graphics, grDevices, MASS, stats, utils License: LGPL (>= 2) MD5sum: efe9f80dc869a9decaf1a0eade95a3ff 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_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RLMM_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RLMM_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RLMM_1.24.0.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: 1.18.0 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: 9cf9a06be076b5a0b6c24eb352587dc3 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rmagpie_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rmagpie_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rmagpie_1.18.0.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: 1.12.0 Depends: methods Suggests: RCurl License: Artistic 2.0 MD5sum: c82539dd96717290bf655f5093f54031 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RMAPPER_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RMAPPER_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RMAPPER_1.12.0.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: 1.4.0 Depends: mzR,rcdk,yaml,methods Imports: XML,RCurl,rjson Suggests: gplots,RMassBankData, xcms (>= 1.37.1), CAMERA, ontoCAT, RUnit License: Artistic-2.0 MD5sum: e7f0fd2daa2b32e2d647537e975f19fa 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RMassBank_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RMassBank_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RMassBank_1.4.0.tgz vignettes: vignettes/RMassBank/inst/doc/RMassBank.pdf, vignettes/RMassBank/inst/doc/RMassBankNonstandard.pdf vignetteTitles: RMassBank walkthrough, RMassBank non-standard usage hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RMassBank/inst/doc/RMassBank.R, vignettes/RMassBank/inst/doc/RMassBankNonstandard.R Package: rMAT Version: 3.12.0 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: cf0e9c84454829e746d927929b74b5f6 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_3.12.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/rMAT_3.12.0.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: 1.18.0 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: 3fac9ea7f498e1e0ced0b38ef8ace875 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RmiR_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RmiR_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RmiR_1.18.0.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: 1.10.0 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: c914b48033f2a1896970253f78fdea0b 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RNAinteract_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RNAinteract_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RNAinteract_1.10.0.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: 2.10.0 Depends: R (>= 2.10), topGO, RankProd, prada Imports: geneplotter, limma, biomaRt, car, splots, methods License: Artistic-2.0 MD5sum: 7292caea0a017a9a132a086b1601bcef 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, Bioinformatics, 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_2.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RNAither_2.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RNAither_2.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RNAither_2.10.0.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: 2.18.0 Depends: R (>= 2.11.0), methods, Biobase, Rsamtools Imports: GenomicRanges , IRanges, edgeR, DESeq, DBI License: GPL-2 Archs: i386, x64 MD5sum: cc04fdd43e3e97cf0761749ac8419f0e 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, Bioinformatics, ReportWriting, Transcription, GeneExpression, DifferentialExpression, HighThroughputSequencing, RNAseq, SAGE, Visualization Author: Anna Lesniewska ; Michal Okoniewski Maintainer: Michal Okoniewski source.ver: src/contrib/rnaSeqMap_2.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rnaSeqMap_2.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rnaSeqMap_2.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rnaSeqMap_2.18.0.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: 1.2.0 License: LGPL (>=2) MD5sum: d03659e3e76c59cd754c4b5a11e012d5 NeedsCompilation: no Title: Sample size for RNAseq studies Description: RNA-seq, sample size Author: Terry M Therneau [aut, cre], Hart Stephen [ctb] Maintainer: Terry M Therneau source.ver: src/contrib/RNASeqPower_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RNASeqPower_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RNASeqPower_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RNASeqPower_1.2.0.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: ROC Version: 1.38.0 Depends: R (>= 1.9.0), utils, methods Suggests: Biobase License: Artistic-2.0 Archs: i386, x64 MD5sum: 35bcbd9af068098247f16b7db12afc0c NeedsCompilation: yes Title: utilities for ROC, with uarray focus Description: utilities for ROC, with uarray focus biocViews: Bioinformatics, DifferentialExpression Author: Vince Carey , Henning Redestig for C++ language enhancements Maintainer: Vince Carey URL: http://www.bioconductor.org source.ver: src/contrib/ROC_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ROC_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ROC_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ROC_1.38.0.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: 1.0.0 Depends: R (>= 2.10), pracma, reshape, plotrix, microRNA, biomaRt, Biostrings, Biobase, DBI Suggests: ggplot2 License: GPL-2 MD5sum: 8ef695427cb9750c810d7a7bac4abac4 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. biocViews: microRNA Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/roleswitch.html source.ver: src/contrib/Roleswitch_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Roleswitch_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Roleswitch_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Roleswitch_1.0.0.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: 1.18.0 Depends: R (>= 2.9.0), graphics, grDevices, methods, ShortRead Imports: mclust, Biostrings, graphics, grDevices, IRanges, methods, ShortRead, stats Enhances: fork License: GPL-2 MD5sum: 0e46527749064afa35664e439374e8be 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rolexa_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rolexa_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rolexa_1.18.0.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: 1.4.0 Depends: methods Imports: XML, XMLSchema (>= 0.6.0), SSOAP (>= 0.8.0), Biobase Suggests: xtable, GO.db, knitr (>= 1.1.0) License: GPL-2 MD5sum: 0dcd1c65612ca93b65548b1f78befcb9 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rols_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rols_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rols_1.4.0.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: 1.2.0 Depends: methods, graph, boot, KEGGREST, KEGGgraph, Rgraphviz Suggests: RUnit, BiocGenerics License: GPL (>= 3) MD5sum: f82de32dee423ab4ebc4ff38d4b77dd7 NeedsCompilation: no Title: R Onto-Tools suite Description: Suite of tools for functional analysis biocViews: NetworkAnalysis, Microarray, GraphsAndNetworks Author: Calin Voichita and Sorin Draghici Maintainer: Calin Voichita source.ver: src/contrib/ROntoTools_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ROntoTools_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ROntoTools_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ROntoTools_1.2.0.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: 1.18.0 Depends: R (>= 2.15.0), affy, affydata, methods, parallel License: FreeBSD MD5sum: f495afe2202cd23425a0314522fd128e 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RPA_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RPA_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RPA_1.18.0.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: 2.4.0 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: 085b4cafcc56a35514fa718f93171c25 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_2.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RpsiXML_2.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RpsiXML_2.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RpsiXML_2.4.0.tgz vignettes: vignettes/RpsiXML/inst/doc/RpsiXML.pdf, vignettes/RpsiXML/inst/doc/RpsiXMLApp.pdf vignetteTitles: Reading PSI-25 XML files, Application Examples of RpsiXML package hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/RpsiXML/inst/doc/RpsiXML.R, vignettes/RpsiXML/inst/doc/RpsiXMLApp.R dependsOnMe: ScISI importsMe: ScISI Package: rqubic Version: 1.8.0 Depends: methods, Biobase, biclust Imports: Biobase, biclust Suggests: RColorBrewer License: GPL-2 Archs: i386, x64 MD5sum: 97f7980193890bc728b4bca4e10bf891 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/rqubic_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/rqubic_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/rqubic_1.8.0.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: 1.0.0 Depends: VennDiagram, grid License: GPL-2 MD5sum: 639c74c5de30144460f0b8a15c55fc31 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RRHO_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RRHO_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RRHO_1.0.0.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: 1.14.3 Depends: methods, IRanges (>= 1.19.11), GenomicRanges (>= 1.13.35), XVector, Biostrings (>= 2.29.7) Imports: utils, BiocGenerics (>= 0.1.3), zlibbioc, bitops LinkingTo: IRanges, XVector, Biostrings Suggests: 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: e47a853e3a69ac2848af2ee5b67b06c1 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, HighThroughputSequencing 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_1.14.3.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rsamtools_1.14.3.zip win64.binary.ver: bin/windows64/contrib/3.0/Rsamtools_1.14.3.zip mac.binary.ver: bin/macosx/contrib/3.0/Rsamtools_1.14.3.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, casper, chimera, CNVrd2, deepSNV, easyRNASeq, EDASeq, exomeCopy, exomePeak, GGtools, girafe, oneChannelGUI, prebs, qrqc, Rcade, ReQON, rfPred, RIPSeeker, rnaSeqMap, ShortRead, TEQC, VariantAnnotation importsMe: AllelicImbalance, annmap, ArrayExpressHTS, biovizBase, CAGEr, CexoR, customProDB, deepSNV, DEXSeq, DNaseR, FunciSNP, ggbio, gmapR, Gviz, HTSeqGenie, MEDIPS, PICS, QuasR, R453Plus1Toolbox, Repitools, rtracklayer, VariantAnnotation, VariantTools suggestsMe: AnnotationHub, biomvRCNS, DiffBind, gage, GenomicFeatures, GenomicRanges, QuasR, R453Plus1Toolbox, seqbias, SigFuge, SplicingGraphs, Streamer Package: rsbml Version: 2.20.1 Depends: R (>= 2.6.0), BiocGenerics (>= 0.3.2), methods, utils Imports: BiocGenerics, graph, utils License: Artistic-2.0 Archs: i386, x64 MD5sum: 3569cf8b92d53542880055e5e940f97b 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: GraphsAndNetworks, Pathways, NetworkAnalysis Author: Michael Lawrence Maintainer: Michael Lawrence URL: http://www.sbml.org SystemRequirements: libsbml (>=3.0.3) source.ver: src/contrib/rsbml_2.20.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/rsbml_2.20.1.zip win64.binary.ver: bin/windows64/contrib/3.0/rsbml_2.20.1.zip mac.binary.ver: bin/macosx/contrib/3.0/rsbml_2.20.1.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: 0.10.0 Depends: R (>= 2.13.0), BiocGenerics, IRanges (>= 1.19.5), XVector, Biostrings (>= 2.29.2), GenomicRanges, ShortRead (>= 1.15.9), xtable, methods Imports: methods, IRanges, XVector, Biostrings, ShortRead, GenomicRanges, Biobase LinkingTo: IRanges, XVector, Biostrings License: Artistic-2.0 MD5sum: 968b08a748bdc6095618128f62c8213a 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, HighThroughputSequencing Author: Matt Settles , Sam Hunter, Brice Sarver, Ilia Zhbannikov, Kyu-Chul Cho Maintainer: Matt Settles source.ver: src/contrib/rSFFreader_0.10.0.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/rSFFreader_0.10.0.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: 1.12.6 License: GPL-3 MD5sum: 593068189db38d4149787ef5ade00da3 NeedsCompilation: yes Title: Rsubread: high-performance read alignment, quantification and mutation discovery Description: This R package provides easy-to-use tools for analyzing next-gen sequencing read data. Functions of these tools include quality assessment, read alignment, read summarization, exon-exon junction detection, absolute expression calling and SNP calling. These tools are highly efficient and accurate. They 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. This package can be installed on multiple operating systems incluidng Linux, Mac OS X, FreeBSD and Solaris. biocViews: Bioinformatics, Sequencing, HighThroughputSequencing, SequenceMatching, RNAseq, ChIPseq, GeneExpression, GeneRegulation, Genetics, SNP, GeneticVariability, Preprocessing, QualityControl, SequenceAnnotation, 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_1.12.6.tar.gz mac.binary.ver: bin/macosx/contrib/3.0/Rsubread_1.12.6.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: 1.2.1 Depends: R (>= 3.0.0), Biostrings, GenomicRanges Imports: methods, IRanges, ShortRead Suggests: BSgenome.Hsapiens.UCSC.hg19, MASS, rtracklayer License: LGPL-3 MD5sum: b9ba209085a1df631dacc1825d27d195 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: Bioinformatics,HighThroughputSequencing,HighThroughputSequencingData Author: Christoph Bartenhagen Maintainer: Christoph Bartenhagen source.ver: src/contrib/RSVSim_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/RSVSim_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/RSVSim_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/RSVSim_1.2.1.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: 1.2.1 Depends: XML, Rcpp, data.table (>= 1.8.8) Imports: methods LinkingTo: Rcpp Suggests: biomaRt License: Artistic-1.0 | file LICENSE Archs: i386, x64 MD5sum: 429621c97c8244a6d0d1cd959f6365c5 NeedsCompilation: yes Title: Encapsulates X!Tandem in R. Description: This package encapsulate X!Tandem in R. In its most basic functionality, this package allows to call tandem(input) from R, just as tandem.exe /path/to/input.xml would be used to run X!Tandem from the command line. Classes are also provided for taxonomy and parameters objects and methods are provided to convert xml files to R objects and vice versa. 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_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/rTANDEM_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/rTANDEM_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/rTANDEM_1.2.1.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: 1.14.0 Depends: methods,stats,graphics,Biobase,RColorBrewer, gtools Suggests: xtable License: LGPL-3 MD5sum: acc0b47da9aec3e524f872456c96ede8 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RTCA_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RTCA_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RTCA_1.14.0.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: 1.0.0 Depends: R (>= 2.15), methods, igraph Imports: minet, snow, limma, RedeR (>= 1.8.1) Suggests: HTSanalyzeR, RUnit, BiocGenerics License: Artistic-2.0 MD5sum: e62b1dec1034fed27a4f036659bae307 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. biocViews: NetworkInference, NetworkAnalysis, NetworkEnrichment, GeneRegulation, GeneExpression, GraphsAndNetworks 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RTN_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RTN_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RTN_1.0.0.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: 1.8.0 Depends: R (>= 2.11.0), Biobase Imports: limma, multtest Suggests: limma, org.Hs.eg.db, KEGG.db, GO.db License: GPL (>= 3) MD5sum: f2277a6624caefe08bbbc6f1fbdb9114 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/RTopper_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/RTopper_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/RTopper_1.8.0.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: 1.22.7 Depends: R (>= 2.10), methods, GenomicRanges (>= 1.13.3) Imports: XML (>= 1.98-0), BiocGenerics (>= 0.7.7), IRanges (>= 1.19.34), XVector (>= 0.1.3), GenomicRanges (>= 1.13.43), Biostrings (>= 2.29.18), BSgenome (>= 1.23.1), zlibbioc, RCurl (>= 1.4-2), Rsamtools (>= 1.13.1) 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: e212cde9538344b43d8df3a3e865cc93 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_1.22.7.tar.gz win.binary.ver: bin/windows/contrib/3.0/rtracklayer_1.22.7.zip win64.binary.ver: bin/windows64/contrib/3.0/rtracklayer_1.22.7.zip mac.binary.ver: bin/macosx/contrib/3.0/rtracklayer_1.22.7.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, HTSeqGenie, MethylSeekR, RIPSeeker, spliceR importsMe: BiSeq, CAGEr, CexoR, ChromHeatMap, customProDB, FunciSNP, GenomicFeatures, ggbio, gmapR, Gviz, HiTC, HTSeqGenie, interactiveDisplay, MEDIPS, methyAnalysis, MotifDb, VariantAnnotation, VariantTools suggestsMe: biovizBase, GenomicFeatures, GenomicRanges, goseq, Gviz, gwascat, methylumi, MotIV, NarrowPeaks, oneChannelGUI, PICS, PING, QuasR, R453Plus1Toolbox, Repitools, Ringo, rMAT, RSVSim, triplex, TSSi Package: Rtreemix Version: 1.24.0 Depends: R (>= 2.5.0), methods, graph, Biobase Imports: methods, graph, Biobase, Hmisc Suggests: Rgraphviz License: LGPL Archs: i386, x64 MD5sum: cb45d454f00d422026b5967dbbbfa131 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: Bioinformatics Author: Jasmina Bogojeska Maintainer: Jasmina Bogojeska source.ver: src/contrib/Rtreemix_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Rtreemix_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Rtreemix_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Rtreemix_1.24.0.tgz vignettes: vignettes/Rtreemix/inst/doc/ClassDiagram.pdf, vignettes/Rtreemix/inst/doc/ExtendedVignette.pdf, vignettes/Rtreemix/inst/doc/Rtreemix.pdf, vignettes/Rtreemix/inst/doc/topologies.pdf vignetteTitles: ClassDiagram.pdf, ExtendedVignette.pdf, Rtreemix, topologies.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/Rtreemix/inst/doc/Rtreemix.R Package: rTRM Version: 1.0.5 Depends: R (>= 2.10), igraph, RSQLite, annotate Imports: AnnotationDbi Suggests: RUnit, BiocGenerics, MotifDb, graph, PWMEnrich, biomaRt, knitr, Biostrings, BSgenome.Mmusculus.UCSC.mm8, org.Mm.eg.db License: GPL-3 MD5sum: 0f29dec8ea92e4e7a9feaa48b85f4768 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, NetworkAnalysis, GeneRegulation, GraphsAndNetworks Author: Diego Diez Maintainer: Diego Diez VignetteBuilder: knitr source.ver: src/contrib/rTRM_1.0.5.tar.gz win.binary.ver: bin/windows/contrib/3.0/rTRM_1.0.5.zip win64.binary.ver: bin/windows64/contrib/3.0/rTRM_1.0.5.zip mac.binary.ver: bin/macosx/contrib/3.0/rTRM_1.0.5.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 dependsOnMe: rTRMui Package: rTRMui Version: 1.0.4 Depends: shiny (>= 0.5), rTRM, MotifDb, org.Hs.eg.db, org.Mm.eg.db License: GPL-3 MD5sum: c4a68ea36e872e00117256eb14c0cfda 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, NetworkAnalysis, GeneRegulation, GraphsAndNetworks, GUI Author: Diego Diez Maintainer: Diego Diez source.ver: src/contrib/rTRMui_1.0.4.tar.gz win.binary.ver: bin/windows/contrib/3.0/rTRMui_1.0.4.zip win64.binary.ver: bin/windows64/contrib/3.0/rTRMui_1.0.4.zip mac.binary.ver: bin/macosx/contrib/3.0/rTRMui_1.0.4.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: 1.26.0 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: 0d419d17922883bf03a4633d1e7726fe 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_1.26.0.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: 3.2.0 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: c77f3f551e11758e901488f1ce2ab2d3 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_3.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/safe_3.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/safe_3.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/safe_3.2.0.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: 1.32.0 Depends: R (>= 2.10), SparseM (>= 0.73), methods Imports: graphics, methods, SparseM, stats, utils License: GPL (>= 2) MD5sum: a402ec6cd85a5357966102f7f23c3900 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_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sagenhaft_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sagenhaft_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sagenhaft_1.32.0.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: 1.36.0 Depends: R (>= 2.5.0), stats, multtest, methods Imports: Biobase, stats4 Suggests: KEGG.db, hu6800.db, MASS License: GPL-3 Archs: i386, x64 MD5sum: eda891484fb8ece1da16fc90acccc370 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, Bioinformatics, DifferentialExpression, Clustering, MultipleComparisons Author: Per Broberg Maintainer: Per Broberg, URL: http://home.swipnet.se/pibroberg/expression_hemsida1.html source.ver: src/contrib/SAGx_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SAGx_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SAGx_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SAGx_1.36.0.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: 1.16.0 Depends: R (>= 2.10) Imports: methods License: GPL (>= 2) Archs: i386, x64 MD5sum: c59e1205b95b529eff91aaf9991c5be7 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: Bioinformatics, FlowCytometry, CellBiology, Clustering, Cancer, FlowCytData, StemCells, HIV Author: Habil Zare and Parisa Shooshtari Maintainer: Habil Zare source.ver: src/contrib/SamSPECTRAL_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SamSPECTRAL_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SamSPECTRAL_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SamSPECTRAL_1.16.0.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: SANTA Version: 1.2.0 Depends: R (>= 2.14), igraph Imports: msm, snow Suggests: RUnit, BiocGenerics, org.Sc.sgd.db License: Artistic-2.0 Archs: i386, x64 MD5sum: bde2976ed2cfc0f9cd20268a7610a14c 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: NetworkAnalysis, NetworkEnrichment, Clustering Author: Alex Cornish and Florian Markowetz Maintainer: Alex Cornish source.ver: src/contrib/SANTA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SANTA_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SANTA_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SANTA_1.2.0.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: SBMLR Version: 1.58.0 Depends: XML, deSolve Suggests: rsbml License: GPL-2 MD5sum: f08b4106bfd36f095a31ca74e0a3fa6c NeedsCompilation: no Title: SBML-R Interface and Analysis Tools Description: This package contains a systems biology markup language (SBML) interface to R. biocViews: GraphsAndNetworks, Pathways, NetworkAnalysis Author: Tomas Radivoyevitch, Vishak Venkateswaran Maintainer: Tomas Radivoyevitch URL: http://epbi-radivot.cwru.edu/SBMLR/SBMLR.html source.ver: src/contrib/SBMLR_1.58.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SBMLR_1.58.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SBMLR_1.58.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SBMLR_1.58.0.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: 2.4.2 Depends: R (>= 2.14.0), Biobase (>= 2.6.0), oligo, Biostrings, GEOquery, affy, affyio, foreach Imports: utils, methods, MASS, tools Suggests: pd.hg.u95a License: MIT MD5sum: 2c985d5deb06a89816f4d379ef1076c4 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 estimate 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_2.4.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/SCAN.UPC_2.4.2.zip win64.binary.ver: bin/windows64/contrib/3.0/SCAN.UPC_2.4.2.zip mac.binary.ver: bin/macosx/contrib/3.0/SCAN.UPC_2.4.2.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: 1.34.0 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: 750f36c134b01935e1de28066f527f6e NeedsCompilation: no Title: In Silico Interactome Description: Package to create In Silico Interactomes biocViews: GraphsAndNetworks, Proteomics, NetworkInference Author: Tony Chiang Maintainer: Tony Chiang source.ver: src/contrib/ScISI_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ScISI_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ScISI_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ScISI_1.34.0.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: segmentSeq Version: 1.14.0 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: 4f35bce2b0f348e302a268701163ace9 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_1.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/segmentSeq_1.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/segmentSeq_1.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/segmentSeq_1.14.0.tgz vignettes: vignettes/segmentSeq/inst/doc/methylationAnalysis.pdf, vignettes/segmentSeq/inst/doc/segmentSeq.pdf vignetteTitles: methylationAnalysis, 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: 1.2.1 Depends: gdsfmt (>= 1.0.0) Imports: methods, Biostrings, GenomicRanges, IRanges, VariantAnnotation Suggests: parallel, snow, BiocGenerics, RUnit, Rcpp License: GPL-3 Archs: i386, x64 MD5sum: 3e2663b52f8432b973ddf9815b1b568f 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: Bioinformatics, 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_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/SeqArray_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/SeqArray_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/SeqArray_1.2.1.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: 1.10.0 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: b1f62d8c4d189ac37b71f9f958705877 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, HighThroughputSequencing Author: Daniel Jones Maintainer: Daniel Jones source.ver: src/contrib/seqbias_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/seqbias_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/seqbias_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/seqbias_1.10.0.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: 1.2.0 Depends: R (>= 2.10), GLAD (>= 2.14), doSNOW (>= 1.0.5), adehabitatLT (>= 0.3.4), seqCNA.annot (>= 0.99), methods License: GPL-3 Archs: i386, x64 MD5sum: da8f671e61c3d429dbb28dd0998182e8 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: Bioinformatics, CopyNumberVariants, Genetics, HighThroughputSequencing Author: David Mosen-Ansorena Maintainer: David Mosen-Ansorena SystemRequirements: samtools source.ver: src/contrib/seqCNA_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/seqCNA_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/seqCNA_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/seqCNA_1.2.0.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: 1.2.1 Depends: Biobase, BiocGenerics, DESeq, biomaRt, foreach Imports: methods, doParallel License: GPL (>= 3) MD5sum: 0c451957f13617b98388904122e56e8f 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: HighThroughputSequencing, RNAseq, GeneSetEnrichment, GeneExpression, DifferentialExpression Author: Xi Wang Maintainer: Xi Wang source.ver: src/contrib/SeqGSEA_1.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/SeqGSEA_1.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/SeqGSEA_1.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/SeqGSEA_1.2.1.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: 1.28.0 Depends: methods, grid License: LGPL (>= 2) MD5sum: 9957cdd2e199dfc3922304bef466b9f6 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/seqLogo_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/seqLogo_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/seqLogo_1.28.0.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: 1.0.0 Depends: SeqArray (>= 1.1.1) Imports: methods, GenomicRanges, IRanges, GWASExactHW Suggests: BiocGenerics, RUnit License: GPL-3 MD5sum: 7da31ff9ac5b01d4c78785248183a5e7 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, HighThroughputSequencing, Genetics Author: Stephanie M. Gogarten, Xiuwen Zheng Maintainer: Stephanie M. Gogarten , Xiuwen Zheng source.ver: src/contrib/SeqVarTools_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SeqVarTools_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SeqVarTools_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SeqVarTools_1.0.0.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: 1.0.0 Depends: rTANDEM, shiny, biomaRt License: GPL-3 MD5sum: 866aaa0842fb323cda376dc8bca27b5a 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 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/shinyTANDEM_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/shinyTANDEM_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/shinyTANDEM_1.0.0.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: 1.20.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.19.34), GenomicRanges (>= 1.13.43), Biostrings (>= 2.29.18), lattice, Rsamtools (>= 1.13.1) Imports: Biobase, hwriter, zlibbioc, latticeExtra LinkingTo: IRanges, XVector, Biostrings Suggests: biomaRt, RUnit, GenomicFeatures, yeastNagalakshmi Enhances: Rmpi, parallel License: Artistic-2.0 Archs: i386, x64 MD5sum: f25d1f1aff15fe5a66c9b2e0e2befa81 NeedsCompilation: yes Title: Classes and methods for high-throughput short-read sequencing data. Description: Base classes, functions, and methods for representation of high-throughput, short-read sequencing data. biocViews: DataImport, Sequencing, HighThroughputSequencing, QualityControl Author: Martin Morgan, Michael Lawrence, Simon Anders Maintainer: Bioconductor Package Maintainer source.ver: src/contrib/ShortRead_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ShortRead_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ShortRead_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ShortRead_1.20.0.tgz vignettes: vignettes/ShortRead/inst/doc/Overview.pdf, vignettes/ShortRead/inst/doc/ShortRead_and_HilbertVis.pdf vignetteTitles: An introduction to ShortRead, ShortRead_and_HilbertVis.pdf hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/ShortRead/inst/doc/Overview.R dependsOnMe: chipseq, ChIPseqR, easyRNASeq, EDASeq, girafe, HTSeqGenie, nucleR, OTUbase, Rolexa, rSFFreader, segmentSeq importsMe: ArrayExpressHTS, chipseq, ChIPseqR, ChIPsim, nucleR, OTUbase, QuasR, R453Plus1Toolbox, Rolexa, rSFFreader, RSVSim suggestsMe: CSAR, DBChIP, Genominator, PICS, PING, R453Plus1Toolbox, Repitools, Rsamtools Package: sigaR Version: 1.6.0 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: 149e2fa37fe47c32e044198b47f5b04e 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, Bioinformatics, 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_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sigaR_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sigaR_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sigaR_1.6.0.tgz vignettes: vignettes/sigaR/inst/doc/sigaR.pdf, vignettes/sigaR/inst/doc/statisticalUnit.pdf vignetteTitles: sigaR, statisticalUnit.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/sigaR/inst/doc/sigaR.R dependsOnMe: HCsnip Package: SigFuge Version: 1.0.2 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: bdd62641f24ca9701db82c16b057606e 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_1.0.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/SigFuge_1.0.2.zip win64.binary.ver: bin/windows64/contrib/3.0/SigFuge_1.0.2.zip mac.binary.ver: bin/macosx/contrib/3.0/SigFuge_1.0.2.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: 1.36.0 Depends: methods, Biobase, multtest, splines, graphics Imports: stats4 Suggests: affy, annotate, genefilter, KernSmooth, scrime (>= 1.2.5) License: LGPL (>= 2) MD5sum: 441c332d5189421028651921f6247423 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: MultipleComparisons, Microarray, GeneExpression, SNP, ExonArray, DifferentialExpression Author: Holger Schwender Maintainer: Holger Schwender source.ver: src/contrib/siggenes_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/siggenes_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/siggenes_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/siggenes_1.36.0.tgz vignettes: vignettes/siggenes/inst/doc/siggenes.pdf, vignettes/siggenes/inst/doc/siggenesRnews.pdf vignetteTitles: siggenes Manual, siggenesRnews.pdf 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: 1.30.0 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: 5636efc1cdcc651fa4a0352abcd774cd 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: Bioinformatics, DifferentialExpression, MultipleComparisons 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_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sigPathway_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sigPathway_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sigPathway_1.30.0.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: 1.32.0 Depends: R (>= 2.4), quantreg Imports: graphics, stats, globaltest, quantsmooth Suggests: biomaRt, RColorBrewer License: GPL (>= 2) Archs: i386, x64 MD5sum: 1b8976e860df3277743e70b323cc521d NeedsCompilation: yes Title: Integrated Analysis on two human genomic datasets Description: Finds associations between two human genomic datasets. biocViews: Microarray, Bioinformatics, Visualization Author: Renee X. de Menezes and Judith M. Boer Maintainer: Renee X. de Menezes source.ver: src/contrib/SIM_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SIM_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SIM_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SIM_1.32.0.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: 1.0.0 Depends: R (>= 2.10), methods, Ringo Imports: limma, mclust, Biobase License: GPL-3 MD5sum: 10b8d68552a48540164c7c4460066640 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SimBindProfiles_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SimBindProfiles_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SimBindProfiles_1.0.0.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: 2.38.0 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: 68fbe75b4e04265c0fe43610afdeff04 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, Bioinformatics, 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_2.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/simpleaffy_2.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/simpleaffy_2.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/simpleaffy_2.38.0.tgz vignettes: vignettes/simpleaffy/inst/doc/QCandSimpleaffy.pdf, vignettes/simpleaffy/inst/doc/simpleAffy.pdf vignetteTitles: QCandSimpleaffy.pdf, simpleaffy primer hasREADME: TRUE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/simpleaffy/inst/doc/simpleAffy.R dependsOnMe: yaqcaffy importsMe: affyQCReport, arrayMvout, arrayQualityMetrics suggestsMe: AffyExpress, ArrayTools Package: sizepower Version: 1.32.0 Depends: stats License: LGPL MD5sum: 4b831c816fa11496de3631735ed7bea3 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, Bioinformatics Author: Weiliang Qiu and Mei-Ling Ting Lee and George Alex Whitmore Maintainer: Weiliang Qiu source.ver: src/contrib/sizepower_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sizepower_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sizepower_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sizepower_1.32.0.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: 0.88.0 Depends: R (>= 2.10.0), methods Imports: methods License: GPL (>= 2) MD5sum: 2a8d1f3cbcf4870488d7b05f9fde09fa 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_0.88.0.tar.gz hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: RWebServices importsMe: RWebServices Package: SLGI Version: 1.22.0 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: 63b52e30d5740677f13c2ca8cc083d1e NeedsCompilation: no Title: Synthetic Lethal Genetic Interaction Description: A variety of data files and functions for the analysis of genetic interactions biocViews: GraphsAndNetworks, Proteomics, Genetics, NetworkAnalysis Author: Nolwenn LeMeur, Zhen Jiang, Ting-Yuan Liu, Jess Mar and Robert Gentleman Maintainer: Nolwenn Le Meur source.ver: src/contrib/SLGI_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SLGI_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SLGI_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SLGI_1.22.0.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: 1.28.0 Depends: R(>= 2.4.0) Imports: stats Suggests: RColorBrewer License: GPL (>= 2) MD5sum: 5dbb7b7f9a4319319fb374b32e2ce01c 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: Bioinformatics, MicrotitrePlateAssay, qPCR Author: Matthias Kohl Maintainer: Matthias Kohl source.ver: src/contrib/SLqPCR_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SLqPCR_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SLqPCR_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SLqPCR_1.28.0.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: 1.26.0 Depends: R (>= 2.10), methods License: GPL-2 Archs: i386, x64 MD5sum: acd1793efe06650cfe90ce66ccb8394a 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, CopyNumberVariants Author: Robin Andersson Maintainer: Robin Andersson source.ver: src/contrib/SMAP_1.26.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SMAP_1.26.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SMAP_1.26.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SMAP_1.26.0.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: 1.2.0 Depends: R (>= 2.6.0), SNAGEEdata Suggests: ALL, hgu95av2.db Enhances: parallel License: Artistic-2.0 MD5sum: 2992411d5f1c331242b07dc8cffdd8ef 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SNAGEE_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SNAGEE_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SNAGEE_1.2.0.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: 1.32.0 Depends: limma, DNAcopy, methods Imports: aCGH, cluster, DNAcopy, GLAD, graphics, grDevices, limma, methods, stats, tilingArray, utils License: GPL Archs: i386, x64 MD5sum: d84ff68e1f526ba4b4a292714d848c63 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, CopyNumberVariants, TwoChannel, Preprocessing Author: Mike L. Smith, John C. Marioni, Steven McKinney, Thomas Hardcastle, Natalie P. Thorne Maintainer: John Marioni source.ver: src/contrib/snapCGH_1.32.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/snapCGH_1.32.0.zip win64.binary.ver: bin/windows64/contrib/3.0/snapCGH_1.32.0.zip mac.binary.ver: bin/macosx/contrib/3.0/snapCGH_1.32.0.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: 1.10.2 Depends: R (>= 2.12.0) Imports: corpcor, lme4 (>= 1.0), splines License: LGPL MD5sum: afa6ce66e5d8ce91ccdac964c541c086 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, MultipleComparisons, Preprocessing, QualityControl Author: Brig Mecham and John D. Storey Maintainer: John D. Storey source.ver: src/contrib/snm_1.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/snm_1.10.2.zip win64.binary.ver: bin/windows64/contrib/3.0/snm_1.10.2.zip mac.binary.ver: bin/macosx/contrib/3.0/snm_1.10.2.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: 2.8.0 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: 3c45e6a9950349660e6fffad788f6382 NeedsCompilation: no Title: Visualizations for copy number alterations Description: This package defines methods for visualizing high-throughput genomic data biocViews: CopyNumberVariants, 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_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SNPchip_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SNPchip_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SNPchip_2.8.0.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: 1.12.0 Depends: R(>= 2.10.0), survival, methods, Matrix Imports: graphics, grDevices, methods, stats, survival, utils, Matrix, BiocGenerics Suggests: hexbin License: GPL-3 Archs: i386, x64 MD5sum: 05608e57a73258fc13f8a7600e23e527 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/snpStats_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/snpStats_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/snpStats_1.12.0.tgz vignettes: vignettes/snpStats/inst/doc/data-input-vignette.pdf, vignettes/snpStats/inst/doc/differences.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, 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/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, gwascat importsMe: FunciSNP, GGtools suggestsMe: crlmm, GWASTools, VariantAnnotation Package: SomatiCA Version: 1.4.0 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: e460d005732197282b423c97eb70bdf7 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: Bioinformatics, Sequencing, CopyNumberVariants Author: Mengjie Chen , Hongyu Zhao Maintainer: Mengjie Chen source.ver: src/contrib/SomatiCA_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SomatiCA_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SomatiCA_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SomatiCA_1.4.0.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: SpacePAC Version: 1.0.0 Depends: R(>= 2.15),iPAC Suggests: RUnit, BiocGenerics, rgl License: GPL-2 MD5sum: 9f3d3e625eaf90bf2b09722db398dfbf 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SpacePAC_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SpacePAC_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SpacePAC_1.0.0.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: 1.10.2 Depends: R (>= 2.11), igraph, Rclusterpp Imports: Biobase, flowCore, igraph, Rclusterpp Suggests: flowViz License: GPL-2 Archs: i386, x64 MD5sum: c0095db79e2e209de4280522e7dc7a8a 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, GraphsAndNetworks, GUI, Visualization, Clustering Author: M. Linderman, P. Qiu, E. Simonds, Z. Bjornson Maintainer: Michael Linderman URL: http://cytospade.org source.ver: src/contrib/spade_1.10.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/spade_1.10.2.zip win64.binary.ver: bin/windows64/contrib/3.0/spade_1.10.2.zip mac.binary.ver: bin/macosx/contrib/3.0/spade_1.10.2.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: 1.16.0 Depends: R (>= 2.10.0), mclust (>= 3.3.1), Biobase (>= 1.15.13), fields, hwriter (>= 1.1), RColorBrewer, methods License: LGPL (>=2) MD5sum: 496dff890b351d2b166c535f098c0964 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, Bioinformatics, MultipleComparisons, Clustering, ReportWriting Author: Florence Cavalli Maintainer: Florence Cavalli source.ver: src/contrib/SpeCond_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SpeCond_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SpeCond_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SpeCond_1.16.0.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: 1.2.0 Depends: R (>= 2.15.1), Rsolnp, Biobase, methods License: GPL-2 MD5sum: 73f697a0bcc5295931adf43b77d1cc4f NeedsCompilation: no Title: S-system parameter estimation method Description: This package can optimize the parameter in S-system models given time series data biocViews: Bioinformatics, NetworkAnalysis, NetworkInference, Software Author: Xinyi YANG Developer, Jennifer E. DENT Developer and Christine NARDINI Supervisor Maintainer: Xinyi YANG source.ver: src/contrib/SPEM_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SPEM_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SPEM_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SPEM_1.2.0.tgz vignettes: vignettes/SPEM/inst/doc/Flowchartmain.pdf, vignettes/SPEM/inst/doc/S_system.pdf, vignettes/SPEM/inst/doc/sospathway.pdf, vignettes/SPEM/inst/doc/SPEM-package.pdf vignetteTitles: Flowchartmain.pdf, S_system.pdf, sospathway.pdf, Vignette for SPEM hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/SPEM/inst/doc/SPEM-package.R Package: SPIA Version: 2.14.0 Depends: R (>= 2.14.0), graphics, KEGGgraph Imports: graphics Suggests: graph, Rgraphviz, hgu133plus2.db License: GPL (>= 2) MD5sum: 879e813b9f59288846c21928273185a2 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, GraphsAndNetworks 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_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SPIA_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SPIA_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SPIA_2.14.0.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: 2.22.0 Imports: graphics, grDevices, stats, utils License: GPL-2 MD5sum: 1531d8d2549d8952b6e8dc95268ad86b 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_2.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/spikeLI_2.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/spikeLI_2.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/spikeLI_2.22.0.tgz vignettes: vignettes/spikeLI/inst/doc/collapse_A14.pdf, vignettes/spikeLI/inst/doc/Ivsc.pdf, vignettes/spikeLI/inst/doc/IvsDG_TagE.pdf, vignettes/spikeLI/inst/doc/langmuir2.pdf, vignettes/spikeLI/inst/doc/spikeLI.pdf vignetteTitles: collapse_A14.pdf, Ivsc.pdf, IvsDG_TagE.pdf, langmuir2.pdf, spikeLI hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/spikeLI/inst/doc/spikeLI.R Package: spkTools Version: 1.18.0 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: ee71c4777b1199e49a6eafb18ba6f23b 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, AssayTechnologies, Microarray Author: Matthew N McCall , Rafael A Irizarry Maintainer: Matthew N McCall URL: http://bioconductor.org source.ver: src/contrib/spkTools_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/spkTools_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/spkTools_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/spkTools_1.18.0.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: 1.34.0 Depends: R (>= 2.6.0), methods, Biobase(>= 2.5.5) Imports: annotate, Biobase, graphics, grDevices, grid, methods, utils, XML License: LGPL MD5sum: 06d7f460808e0e1902599040be87451f 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/splicegear_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/splicegear_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/splicegear_1.34.0.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: 1.3.1 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: 0ef71715c919b36826f1c6979db88953 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: Bioinformatics, DifferentialExpression, HighThroughputSequencing, HighThroughputSequencingData, RNAseq, RNAseqData, software, visualization Author: Johannes Waage , Kristoffer Vitting-Seerup Maintainer: Johannes Waage , Kristoffer Vitting-Seerup source.ver: src/contrib/spliceR_1.3.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/spliceR_1.3.1.zip win64.binary.ver: bin/windows64/contrib/3.0/spliceR_1.3.1.zip mac.binary.ver: bin/macosx/contrib/3.0/spliceR_1.3.1.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: 1.0.0 Depends: methods,rbamtools,refGenome (>= 1.1.2),doBy,Biobase,Biostrings (>= 2.28.0),seqLogo Imports: BiocGenerics License: GPL-2 Archs: i386, x64 MD5sum: 875480eba65d282e2416ad4bf4a91507 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_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/spliceSites_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/spliceSites_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/spliceSites_1.0.0.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: 1.2.0 Depends: BiocGenerics, IRanges (>= 1.17.43), GenomicRanges (>= 1.13.5), GenomicFeatures, Rgraphviz (>= 2.3.7) Imports: methods, utils, igraph, BiocGenerics, IRanges, GenomicRanges, GenomicFeatures, graph, Rgraphviz Suggests: igraph, Gviz, Rsamtools, TxDb.Hsapiens.UCSC.hg19.knownGene, RNAseqData.HNRNPC.bam.chr14, RUnit License: Artistic-2.0 MD5sum: 7c6b2f08bd996435c278c5d96e9a2d5d 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_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SplicingGraphs_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SplicingGraphs_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SplicingGraphs_1.2.0.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: 1.28.0 Imports: grid, RColorBrewer License: LGPL MD5sum: 859d512c3be1b912101d621978e9618f 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, HighThroughputSequencing, MicrotitrePlateAssay Author: Wolfgang Huber, Oleg Sklyar Maintainer: Wolfgang Huber source.ver: src/contrib/splots_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/splots_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/splots_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/splots_1.28.0.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: 1.36.0 Depends: R (>= 2.10), mclust License: GPL (>= 2) MD5sum: 2b2b7bbcf5a4203364dff3223af60b4c 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_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/spotSegmentation_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/spotSegmentation_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/spotSegmentation_1.36.0.tgz vignettes: vignettes/spotSegmentation/inst/doc/spotsegdoc.pdf vignetteTitles: spotsegdoc.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: SQUADD Version: 1.12.0 Depends: R (>= 2.11.0) Imports: graphics, grDevices, methods, RColorBrewer, stats, utils License: GPL (>=2) MD5sum: cffc98c19d19cb41b0faf6ca7c1a22d1 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: GraphsAndNetworks, NetworkAnalysis, 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SQUADD_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SQUADD_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SQUADD_1.12.0.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: 1.16.0 Depends: RSQLite (>= 0.8-4) , graph, RCurl Imports: GEOquery Suggests: Rgraphviz License: Artistic-2.0 MD5sum: 5acb750fbfd47fa219be17911bf83e14 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, HighThroughputSequencing, DataImport Author: Jack Zhu and Sean Davis Maintainer: Jack Zhu URL: http://gbnci.abcc.ncifcrf.gov/sra/ source.ver: src/contrib/SRAdb_1.16.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SRAdb_1.16.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SRAdb_1.16.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SRAdb_1.16.0.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: 1.4.0 Depends: WriteXLS Imports: gplots, pls, ROCR, qvalue License: GPL-3 MD5sum: 73e98aa0372fd9595f89689258994cd9 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sRAP_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sRAP_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sRAP_1.4.0.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: 1.34.0 Depends: R (>= 1.8.0), affy, affyio Suggests: affydata License: GPL (>= 2) MD5sum: b9780ec01ae88c61ab10d56c6d4ad0cf 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: Bioinformatics, 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sscore_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sscore_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sscore_1.34.0.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: 1.0.0 Depends: R (>= 3.0), caTools, RColorBrewer License: GPL (>= 3) MD5sum: 271b2426014b6aaaa250bd342a792bd4 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. Author: Danni Yu , Wolfgang Huber and Olga Vitek Maintainer: Danni Yu source.ver: src/contrib/sSeq_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sSeq_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sSeq_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sSeq_1.0.0.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: 1.36.0 Depends: gdata, xtable License: LGPL MD5sum: f6708a69703ffa006803d826323bdf53 NeedsCompilation: no Title: Estimate Microarray Sample Size Description: Functions for computing and displaying sample size information for gene expression arrays. biocViews: Bioinformatics, Microarray, DifferentialExpression Author: Gregory R. Warnes, Peng Liu, and Fasheng Li Maintainer: Gregory R. Warnes source.ver: src/contrib/ssize_1.36.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ssize_1.36.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ssize_1.36.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ssize_1.36.0.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: 2.2.0 Depends: R (>= 2.12), methods, qvalue, lattice, limma Imports: graphics, stats Suggests: genefilter, edgeR, DESeq License: GPL (>= 2) Archs: i386, x64 MD5sum: 03aa9528c9581ea0b79bfd867b780278 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, Statistics Author: Maarten van Iterson Maintainer: Maarten van Iterson URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html source.ver: src/contrib/SSPA_2.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SSPA_2.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SSPA_2.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SSPA_2.2.0.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: 1.4.0 Depends: methods, cellHTS2, R (>= 2.10) License: GPL MD5sum: efedafe9f81d8877a6cf97d3b39036c7 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: Bioinformatics, MultipleComparisons, CellBiology, CellBasedAssays, MicrotitrePlateAssay Author: Juliane Siebourg, Niko Beerenwinkel Maintainer: Juliane Siebourg source.ver: src/contrib/staRank_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/staRank_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/staRank_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/staRank_1.4.0.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: 1.18.1 Depends: Ringo, affy, affxparser, lattice Imports: pspline, MASS, zlibbioc License: Artistic-2.0 Archs: i386, x64 MD5sum: d5c9e944fa162c2e03a80800584f94b0 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_1.18.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/Starr_1.18.1.zip win64.binary.ver: bin/windows64/contrib/3.0/Starr_1.18.1.zip mac.binary.ver: bin/macosx/contrib/3.0/Starr_1.18.1.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: 1.34.0 Depends: R (>= 1.8.0), marray, methods Imports: marray, MASS, methods, stats License: LGPL MD5sum: 2c48d08833cc72bb83089550dfe0b572 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/stepNorm_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/stepNorm_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/stepNorm_1.34.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Package: stepwiseCM Version: 1.8.0 Depends: R (>= 2.14), randomForest, MAclinical, tspair, pamr, snowfall, glmpath, penalized, e1071, Biobase License: GPL (>2) MD5sum: cfb91c85b707bdd37b64b9b3f6aff16c 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, Bioinformatics, Integration Author: Askar Obulkasim Maintainer: Askar Obulkasim source.ver: src/contrib/stepwiseCM_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/stepwiseCM_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/stepwiseCM_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/stepwiseCM_1.8.0.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: 1.8.0 Imports: methods, graph, RBGL, parallel, BiocGenerics Suggests: RUnit, Rsamtools (>= 1.5.53), Rgraphviz License: Artistic-2.0 Archs: i386, x64 MD5sum: 35355b93788f4136d0906a3ea15e8df9 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Streamer_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Streamer_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Streamer_1.8.0.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: 1.0.1 Depends: R (>= 2.14.0), png, sqldf, plyr, igraph, RCurl, plotrix, methods Suggests: RUnit, BiocGenerics License: GPL-2 MD5sum: c65f68ddda264f2805db6446cbc3e506 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 ). Author: Andrea Franceschini Maintainer: Andrea Franceschini , Alexander Roth , Christian Von Mering , Michael Kuhn , Lars J Jensen source.ver: src/contrib/STRINGdb_1.0.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/STRINGdb_1.0.1.zip win64.binary.ver: bin/windows64/contrib/3.0/STRINGdb_1.0.1.zip mac.binary.ver: bin/macosx/contrib/3.0/STRINGdb_1.0.1.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 Package: supraHex Version: 1.0.0 Depends: R (>= 3.0.1), hexbin Imports: grid, MASS, Biobase License: GPL-2 MD5sum: 5a0d010b61abeb0b963b3bbb1f975c01 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 data. The supraHex is able to carray out gene/meta-gene clustering and sample correlation, plus intuitive visualisations to facilitate exploratory analysis. Uniquely to this package, users can simultaneously understand their own omics data in a sample-specific fashion but without loss of information on large genes. biocViews: Bioinformatics, Clustering, Visualization, GeneExpression Author: Hai Fang and Julian Gough Maintainer: Hai Fang URL: http://supfam.org/SUPERFAMILY/dcGO/supraHex.html source.ver: src/contrib/supraHex_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/supraHex_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/supraHex_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/supraHex_1.0.0.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: 1.12.0 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: 50e44a0771e01c1d0d193a078dac2f14 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/survcomp_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/survcomp_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/survcomp_1.12.0.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 Package: sva Version: 3.8.0 Depends: R (>= 2.8), corpcor, mgcv Imports: graphics, stats Suggests: limma,pamr,bladderbatch License: Artistic-2.0 Archs: i386, x64 MD5sum: c00e486a5ffff7f00bfaa27cea809b13 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,Statistics,Preprocessing,MultipleComparisons 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_3.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/sva_3.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/sva_3.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/sva_3.8.0.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 importsMe: ChAMP, charm, trigger Package: SwimR Version: 1.0.0 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: 80a2197e31a189fad22b60947fed2272 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: Bioinformatics Author: Jing Wang , Andrew Hardaway and Bing Zhang Maintainer: Randy Blakely source.ver: src/contrib/SwimR_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/SwimR_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/SwimR_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/SwimR_1.0.0.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: 1.4.1 Depends: R (>= 2.15), methods, MSnbase Imports: hwriter, tcltk, tcltk2, RColorBrewer, lattice, qvalue, multtest, utils, Biobase, knitr Suggests: synapterdata, xtable License: GPL-2 MD5sum: 617af16a701e360255891e032ff95d09 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: Bioinformatics, MassSpectrometry, Proteomics, GUI Author: Laurent Gatto, Nick J. Bond and Pavel V. Shliaha Maintainer: Laurent Gatto URL: http://lgatto.github.com/synapter/ VignetteBuilder: knitr source.ver: src/contrib/synapter_1.4.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/synapter_1.4.1.zip win64.binary.ver: bin/windows64/contrib/3.0/synapter_1.4.1.zip mac.binary.ver: bin/macosx/contrib/3.0/synapter_1.4.1.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: 1.0.0 Depends: pracma, Matrix Suggests: TargetScoreData, gplots, Biobase, GEOquery License: GPL-2 MD5sum: f20670e159b86c74400d3b16ad7179a1 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: microRNA Author: Yue Li Maintainer: Yue Li URL: http://www.cs.utoronto.ca/~yueli/software.html source.ver: src/contrib/TargetScore_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TargetScore_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TargetScore_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TargetScore_1.0.0.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: 1.18.0 Depends: R (>= 2.7.0), mzR Imports: graphics, grDevices, methods, stats, tcltk, utils Suggests: TargetSearchData License: GPL (>= 2) Archs: i386, x64 MD5sum: 9e6141f6a291f312e866932df128670c 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_1.18.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TargetSearch_1.18.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TargetSearch_1.18.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TargetSearch_1.18.0.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: 1.2.0 Depends: R (>= 2.15), methods, DESeq, edgeR, baySeq, ROC Imports: EBSeq, samr Suggests: RUnit, BiocGenerics Enhances: snow License: GPL-2 MD5sum: 271da5318b89a03a009849181685d038 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 other sophisticated packages (especially edgeR, DESeq, and baySeq). biocViews: HighThroughputSequencing, DifferentialExpression, RNAseq Author: Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer: Jianqiang Sun , Tomoaki Nishiyama source.ver: src/contrib/TCC_1.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TCC_1.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TCC_1.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TCC_1.2.0.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 Package: TDARACNE Version: 1.12.0 Depends: GenKern, Rgraphviz, Biobase License: GPL-2 MD5sum: 748cfaa520fddfb63cf1e3efe5208f3d 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_1.12.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TDARACNE_1.12.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TDARACNE_1.12.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TDARACNE_1.12.0.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: 3.2.0 Depends: methods, BiocGenerics (>= 0.1.0), IRanges (>= 1.13.5), Rsamtools, hwriter Imports: Biobase (>= 2.15.1) License: GPL (>= 2) MD5sum: f603e86e5b1d327f62673680275526d3 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, HighThroughputSequencing, Bioinformatics, Genetics Author: M. Hummel, S. Bonnin, E. Lowy, G. Roma Maintainer: Manuela Hummel source.ver: src/contrib/TEQC_3.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TEQC_3.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TEQC_3.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TEQC_3.2.0.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: 1.6.0 Depends: R (>= 2.10.0), methods Imports: utils, igraph License: GPL (>= 2) Archs: i386, x64 MD5sum: 4d13c8ccbf82b853bd2c0516489d962f NeedsCompilation: yes Title: Ternary Network Estimation Description: A computational Bayesian approach to ternary gene regulatory network estimation from gene perturbation experiments. biocViews: Software, CellBiology, GraphsAndNetworks, Bioinformatics Author: Matthew N. McCall , Anthony Almudevar Maintainer: Matthew N. McCall source.ver: src/contrib/ternarynet_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/ternarynet_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/ternarynet_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/ternarynet_1.6.0.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: 1.0.0 Depends: R (>= 3.0.1), methods, IRanges(>= 1.19.38) Imports: Biostrings(>= 2.29.19), RSQLite(>= 0.11.4), seqLogo License: GPL-2 MD5sum: 05016c8dc11c5520eb9286d5c14556f6 NeedsCompilation: no Title: Software package for TFBS Description: Software package for TFBS. biocViews: MotifAnnotation, GeneRegulation, MotifDiscovery Author: Ge Tan Maintainer: Ge Tan URL: http://jaspardev.genereg.net/ source.ver: src/contrib/TFBSTools_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TFBSTools_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TFBSTools_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TFBSTools_1.0.0.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: 1.16.1 Depends: R (>= 2.11.0), BiocGenerics, Biobase Imports: methods, BiocGenerics, Biobase, AnnotationDbi, gplots, graphics, puma, stats, utils, annotate, DBI, RSQLite Suggests: puma, drosgenome1.db, annotate, lumi License: AGPL-3 Archs: i386, x64 MD5sum: 1d39e607fcf84f5673ba662e57fd577b 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, Bioinformatics, TimeCourse, GeneExpression, Transcription 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_1.16.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/tigre_1.16.1.zip win64.binary.ver: bin/windows64/contrib/3.0/tigre_1.16.1.zip mac.binary.ver: bin/macosx/contrib/3.0/tigre_1.16.1.tgz vignettes: vignettes/tigre/inst/doc/tigre_quick.pdf, vignettes/tigre/inst/doc/tigre.pdf vignetteTitles: tigre Quick Guide, tigre User 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: 1.40.0 Depends: R (>= 2.11.0), Biobase, methods, pixmap Imports: strucchange, affy, vsn, genefilter, RColorBrewer, grid, stats4 License: Artistic-2.0 Archs: i386, x64 MD5sum: 1bbf633782a484f8e6f62931ab98ee08 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/tilingArray_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/tilingArray_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/tilingArray_1.40.0.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: 1.34.0 Depends: R (>= 2.1.1), MASS, methods Imports: Biobase, graphics, limma (>= 1.8.6), MASS, marray, methods, stats License: LGPL MD5sum: 97fd9ed17ea253c9aca0de3c3c23eab7 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/timecourse_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/timecourse_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/timecourse_1.34.0.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: tkWidgets Version: 1.40.0 Depends: R (>= 2.0.0), methods, widgetTools (>= 1.1.7), DynDoc (>= 1.3.0), tools Suggests: Biobase, hgu95av2 License: Artistic-2.0 MD5sum: add1b0a90e4203e43fc7dae67a541e3f 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/tkWidgets_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/tkWidgets_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/tkWidgets_1.40.0.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: 2.14.0 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: b5e7fa20902b4755787dbd5f0ffde648 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,Bioinformatics,Visualization Author: Adrian Alexa, Jorg Rahnenfuhrer Maintainer: Adrian Alexa source.ver: src/contrib/topGO_2.14.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/topGO_2.14.0.zip win64.binary.ver: bin/windows64/contrib/3.0/topGO_2.14.0.zip mac.binary.ver: bin/macosx/contrib/3.0/topGO_2.14.0.tgz vignettes: vignettes/topGO/inst/doc/topGO_classes_v3.pdf, vignettes/topGO/inst/doc/topGO.pdf vignetteTitles: topGO_classes_v3.pdf, topGO hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/topGO/inst/doc/topGO.R dependsOnMe: RNAither, tRanslatome importsMe: GOSim suggestsMe: Ringo Package: tRanslatome Version: 1.0.0 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: f07f27e99b9a64bd37ce32714380749e 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, 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, Regulation, GeneExpression, DifferentialExpression, Microarray, HighThroughputSequencing, QualityControl, GO, MultipleComparisons, Bioinformatics Author: Toma Tebaldi, Erik Dassi, Galena Kostoska Maintainer: Toma Tebaldi source.ver: src/contrib/tRanslatome_1.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/tRanslatome_1.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/tRanslatome_1.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/tRanslatome_1.0.0.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: 1.6.1 Depends: methods,GenomicRanges Imports: Rsamtools,zlibbioc,gplots,IRanges LinkingTo: Rsamtools Suggests: RUnit,pasillaBamSubset License: GPL-3 Archs: i386, x64 MD5sum: 1f66b7c3f32867aa92257ed0671b4a1b 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: Bioinformatics,DNAMethylation,GeneExpression,Transcription, Microarray,Sequencing,HighThroughputSequencing,ChIPseq,RNAseq, Methylseq,DataImport,Visualization,Clustering,MultipleComparisons Author: Julius Muller Maintainer: Julius Muller URL: http://bioconductor.org/packages/release/bioc/html/TransView.html source.ver: src/contrib/TransView_1.6.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/TransView_1.6.1.zip win64.binary.ver: bin/windows64/contrib/3.0/TransView_1.6.1.zip mac.binary.ver: bin/macosx/contrib/3.0/TransView_1.6.1.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: 1.4.0 Depends: R (>= 2.11.0), IRanges, yaml Imports: IRanges, yaml, BiocGenerics Suggests: RUnit License: GPL-2 MD5sum: 925d7d1853ed33b4c4c3ddaee1adb2e5 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 Håndstad Developer [aut, cre] Maintainer: Tony Håndstad Developer source.ver: src/contrib/triform_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/triform_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/triform_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/triform_1.4.0.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: 1.8.0 Depends: R (>= 2.14.0), corpcor, qtl Imports: qvalue, methods, graphics, sva License: GPL-3 Archs: i386, x64 MD5sum: 0ea5a14f0b933ef47d7ecc444f0209ec 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/trigger_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/trigger_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/trigger_1.8.0.tgz vignettes: vignettes/trigger/inst/doc/net50.pdf, vignettes/trigger/inst/doc/trigger.pdf vignetteTitles: net50.pdf, Trigger Tutorial hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/trigger/inst/doc/trigger.R Package: trio Version: 3.0.0 Depends: R (>= 3.0.1) Suggests: survival, haplo.stats, mcbiopi, siggenes, splines, LogicReg (>= 1.5.3), logicFS (>= 1.28.1), KernSmooth License: LGPL-2 MD5sum: 2f89229baaf5cd5a96f223428cd066d1 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, Margaret Taub, Ingo Ruczinski Maintainer: Holger Schwender source.ver: src/contrib/trio_3.0.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/trio_3.0.0.zip win64.binary.ver: bin/windows64/contrib/3.0/trio_3.0.0.zip mac.binary.ver: bin/macosx/contrib/3.0/trio_3.0.0.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: 1.2.2 Depends: R (>= 2.15.0), IRanges (>= 1.19.5), XVector, Biostrings (>= 2.29.2) 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: b2eaa7751abfa8187fa2eea3b4e0ddce 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_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/triplex_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/triplex_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/triplex_1.2.2.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: 1.20.0 Depends: R (>= 2.10), Biobase (>= 2.4.0) License: GPL-2 Archs: i386, x64 MD5sum: ae48744d26dd7d5018b9dbaae48d06bf 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, Bioinformatics Author: Jeffrey T. Leek Maintainer: Jeffrey T. Leek source.ver: src/contrib/tspair_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/tspair_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/tspair_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/tspair_1.20.0.tgz vignettes: vignettes/tspair/inst/doc/tsp.pdf, vignettes/tspair/inst/doc/tsp1.pdf vignetteTitles: tspTutorial, tsp1.pdf hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/tspair/inst/doc/tsp.R dependsOnMe: stepwiseCM Package: TSSi Version: 1.8.0 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: 6d3b202bbaf1d554599abf1b6b55faf0 NeedsCompilation: yes Title: Transcription Start Site Identification Description: Identify and normalize transcription start sites in high-throughput sequencing data. biocViews: Sequencing, HighThroughputSequencing, RNAseq, Genetics, Preprocessing Author: Clemens Kreutz, Julian Gehring Maintainer: Julian Gehring URL: http://julian-gehring.github.com/TSSi/ source.ver: src/contrib/TSSi_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TSSi_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TSSi_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TSSi_1.8.0.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: 1.10.0 Depends: R (>= 2.12.0), convert, limma (>= 1.7.0), marray Imports: stats, grDevices, affy, lattice Suggests: affydata, affy, lattice License: LGPL Archs: i386, x64 MD5sum: b92a4d128a1bbda2cd51e1109ebbc5de 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_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TurboNorm_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TurboNorm_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TurboNorm_1.10.0.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: 1.8.0 Depends: R (>= 2.12.0) Imports: MASS, limma, edgeR, parallel, cqn Suggests: tweeDEseqCountData, xtable License: GPL (>= 2) Archs: i386, x64 MD5sum: 1632922d57afe9bdae7bc9ac44f9c6a9 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: Statistics, DifferentialExpression, HighThroughputSequencing, 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/tweeDEseq_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/tweeDEseq_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/tweeDEseq_1.8.0.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: 1.38.0 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: 7770fc647d78dfbd008735d2ebb380dc 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, Bioinformatics, DifferentialExpression, MultipleComparisons Author: Stefanie Scheid Maintainer: Stefanie Scheid URL: http://compdiag.molgen.mpg.de/software/twilight.shtml source.ver: src/contrib/twilight_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/twilight_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/twilight_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/twilight_1.38.0.tgz vignettes: vignettes/twilight/inst/doc/bcb_logo.pdf, vignettes/twilight/inst/doc/tr_2004_01.pdf vignetteTitles: bcb_logo.pdf, 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: 1.28.0 Depends: methods Suggests: Biobase License: BSD MD5sum: bf151bf5e3cbae71ae63721a69f3d11d 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/TypeInfo_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/TypeInfo_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/TypeInfo_1.28.0.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: UniProt.ws Version: 2.2.1 Depends: RSQLite, RCurl, methods, utils Imports: BiocGenerics, AnnotationDbi Suggests: RUnit License: Artistic License 2.0 MD5sum: ec6ac7a11fcf3f4e3d162d4ac530c6ea 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_2.2.1.tar.gz win.binary.ver: bin/windows/contrib/3.0/UniProt.ws_2.2.1.zip win64.binary.ver: bin/windows64/contrib/3.0/UniProt.ws_2.2.1.zip mac.binary.ver: bin/macosx/contrib/3.0/UniProt.ws_2.2.1.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 importsMe: dagLogo suggestsMe: cleaver Package: VanillaICE Version: 1.24.0 Depends: R (>= 2.14.0) 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: ecf8ac4b7fc3a7d3fee058a9735c1b1a 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: Bioinformatics, CopyNumberVariants, SNP, GeneticVariability, Visualization Author: Robert Scharpf , Kevin Scharpf, and Ingo Ruczinski Maintainer: Robert Scharpf source.ver: src/contrib/VanillaICE_1.24.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/VanillaICE_1.24.0.zip win64.binary.ver: bin/windows64/contrib/3.0/VanillaICE_1.24.0.zip mac.binary.ver: bin/macosx/contrib/3.0/VanillaICE_1.24.0.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: 1.8.13 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.7.7), GenomicRanges (>= 1.13.51), Rsamtools (>= 1.13.47), IRanges (>= 1.19.36), XVector Imports: methods, BiocGenerics, IRanges, XVector, Biostrings (>= 2.29.2), Biobase, Rsamtools, AnnotationDbi (>= 1.17.11), zlibbioc, BSgenome, GenomicFeatures (>= 1.13.11), 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: 208adf9e80c90f4b636ca3cd8b0558bf NeedsCompilation: yes Title: Annotation of Genetic Variants Description: Annotate variants, compute amino acid coding changes, predict coding outcomes biocViews: DataImport, Sequencing, HighThroughputSequencing, 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_1.8.13.tar.gz win.binary.ver: bin/windows/contrib/3.0/VariantAnnotation_1.8.13.zip win64.binary.ver: bin/windows64/contrib/3.0/VariantAnnotation_1.8.13.zip mac.binary.ver: bin/macosx/contrib/3.0/VariantAnnotation_1.8.13.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, VariantTools importsMe: customProDB, FunciSNP, ggbio, GGtools, gmapR, HTSeqGenie, R453Plus1Toolbox, SeqArray, VariantTools suggestsMe: GenomicRanges, gmapR, GWASTools, vtpnet Package: VariantTools Version: 1.4.5 Depends: IRanges (>= 1.19.34), GenomicRanges (>= 1.13.43), VariantAnnotation (>= 1.7.35), methods Imports: IRanges, Rsamtools (>= 1.11.10), GenomicRanges, BiocGenerics, Biostrings, parallel, gmapR (>= 1.3.8), GenomicFeatures, VariantAnnotation, methods, Matrix, rtracklayer, BiocParallel Suggests: RUnit, LungCancerLines (>= 0.0.6), RBGL License: Artistic-2.0 MD5sum: 92564f19c586ba034e8be7b3e7f971eb NeedsCompilation: no Title: Tools for Working with Genetic Variants Description: Tools for detecting, filtering, calling, comparing and plotting variants. biocViews: Genetics, GeneticVariability, HighThroughputSequencing Author: Michael Lawrence, Jeremiah Degenhardt, Robert Gentleman Maintainer: Michael Lawrence source.ver: src/contrib/VariantTools_1.4.5.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: 1.30.0 Depends: R (>= 2.10) Suggests: Biobase (>= 2.5.5), statmod License: GPL (>= 2) MD5sum: 5e3edc33e97eac11c12d151cfcc12dac 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: Bioinformatics,Classification Author: Nicola Lama , Mark Girolami Maintainer: Nicola Lama URL: http://bioinformatics.oxfordjournals.org/cgi/content/short/btm535v1 source.ver: src/contrib/vbmp_1.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/vbmp_1.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/vbmp_1.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/vbmp_1.30.0.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: 1.10.0 Depends: R (>= 2.10) License: GPL-2 Archs: i386, x64 MD5sum: 7a707e0b782b110bc1efa244d1fa92fb 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, CopyNumberVariants Author: Sandro Morganella Maintainer: Sandro Morganella source.ver: src/contrib/Vega_1.10.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/Vega_1.10.0.zip win64.binary.ver: bin/windows64/contrib/3.0/Vega_1.10.0.zip mac.binary.ver: bin/macosx/contrib/3.0/Vega_1.10.0.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: 2.8.0 Depends: R (>= 2.10.0), biomaRt, Biobase, genoset Imports: methods License: GPL-2 Archs: i386, x64 MD5sum: 6246f26c7489eacc99ce794c44adbfae 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: Bioinformatics, aCGH, CopyNumberVariants Author: S. Morganella and M. Ceccarelli Maintainer: Sandro Morganella source.ver: src/contrib/VegaMC_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/VegaMC_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/VegaMC_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/VegaMC_2.8.0.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: virtualArray Version: 1.6.0 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: 3e32a3f4590568f7baf9a0047ddc4640 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, Bioinformatics, MultipleComparisons Author: Andreas Heider Maintainer: Andreas Heider source.ver: src/contrib/virtualArray_1.6.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/virtualArray_1.6.0.zip win64.binary.ver: bin/windows64/contrib/3.0/virtualArray_1.6.0.zip mac.binary.ver: bin/macosx/contrib/3.0/virtualArray_1.6.0.tgz vignettes: vignettes/virtualArray/inst/doc/virtualArray-016.pdf, vignettes/virtualArray/inst/doc/virtualArray.pdf vignetteTitles: virtualArray-016.pdf, virtualArray Vignette hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/virtualArray/inst/doc/virtualArray.R Package: vsn Version: 3.30.0 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: 81388e1ba615aeac7566847a3bc5fc23 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_3.30.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/vsn_3.30.0.zip win64.binary.ver: bin/windows64/contrib/3.0/vsn_3.30.0.zip mac.binary.ver: bin/macosx/contrib/3.0/vsn_3.30.0.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, LVSmiRNA, MmPalateMiRNA, webbioc importsMe: arrayQualityMetrics, imageHTS, MSnbase, pvca, Ringo, tilingArray suggestsMe: adSplit, Agi4x44PreProcess, beadarray, BiocCaseStudies, cellHTS, DESeq, DESeq2, ggbio, GlobalAncova, globaltest, limma, lumi, twilight Package: vtpnet Version: 0.2.0 Depends: R (>= 3.0.0), graph, GenomicRanges Suggests: MotifDb, VariantAnnotation, Rgraphviz License: Artistic-2.0 MD5sum: fe010e84ca797da151c74549da77e3f0 NeedsCompilation: no Title: variant-transcription factor-phenotype networks Description: variant-transcription factor-phenotype networks, inspired by Maurano et al., Science (2012), PMID 22955828 Author: VJ Carey Maintainer: VJ Carey source.ver: src/contrib/vtpnet_0.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/vtpnet_0.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/vtpnet_0.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/vtpnet_0.2.0.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: 1.2.2 Depends: R (>= 2.10), limma, methods, matrixStats, methylumi, lumi, IlluminaHumanMethylation450k.db, ROC Suggests: RPMM Enhances: minfi, methylumi, IMA License: GPL-3 MD5sum: a51be1d45c46db4f49e2345267d7d39d 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_1.2.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/wateRmelon_1.2.2.zip win64.binary.ver: bin/windows64/contrib/3.0/wateRmelon_1.2.2.zip mac.binary.ver: bin/macosx/contrib/3.0/wateRmelon_1.2.2.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: 1.4.0 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: 32ed626609f1c8be8dc98b6553371d54 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_1.4.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/waveTiling_1.4.0.zip win64.binary.ver: bin/windows64/contrib/3.0/waveTiling_1.4.0.zip mac.binary.ver: bin/macosx/contrib/3.0/waveTiling_1.4.0.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: 1.28.0 Depends: R (>= 2.5.0), digest, tools, utils, codetools Suggests: codetools License: GPL-2 MD5sum: a16c51036cdbc9bd75b0e57c68bb91cb 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_1.28.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/weaver_1.28.0.zip win64.binary.ver: bin/windows64/contrib/3.0/weaver_1.28.0.zip mac.binary.ver: bin/macosx/contrib/3.0/weaver_1.28.0.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: 1.34.0 Depends: R (>= 1.8.0), Biobase, affy, multtest, annaffy, vsn, gcrma, qvalue Imports: multtest, qvalue, stats, utils, BiocInstaller License: GPL (>= 2) MD5sum: 1303d98ba46ec104b7a095dcf5df3426 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_1.34.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/webbioc_1.34.0.zip win64.binary.ver: bin/windows64/contrib/3.0/webbioc_1.34.0.zip mac.binary.ver: bin/macosx/contrib/3.0/webbioc_1.34.0.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: 1.40.0 Depends: R (>= 2.4.0), methods, utils, tcltk Suggests: Biobase License: LGPL MD5sum: bf2c5ccdc89b904f430ee2dc2c1b29b1 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_1.40.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/widgetTools_1.40.0.zip win64.binary.ver: bin/windows64/contrib/3.0/widgetTools_1.40.0.zip mac.binary.ver: bin/macosx/contrib/3.0/widgetTools_1.40.0.tgz vignettes: vignettes/widgetTools/inst/doc/widget.pdf, vignettes/widgetTools/inst/doc/widgetTools.pdf vignetteTitles: widget.pdf, 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: 1.38.0 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, KEGGSOAP, Rmpi, XML License: GPL (>= 2) Archs: i386, x64 MD5sum: 9dee773e2680ec32571ce2d3fd0b8766 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/ source.ver: src/contrib/xcms_1.38.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/xcms_1.38.0.zip win64.binary.ver: bin/windows64/contrib/3.0/xcms_1.38.0.zip mac.binary.ver: bin/macosx/contrib/3.0/xcms_1.38.0.tgz vignettes: vignettes/xcms/inst/doc/FlowChart.pdf, 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: FlowChart.pdf, 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 importsMe: CAMERA, Risa suggestsMe: MassSpecWavelet, RMassBank Package: XDE Version: 2.8.0 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: f5553fdc8c531d0745b99e4345e77fa9 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, Bioinformatics, DifferentialExpression Author: R.B. Scharpf, G. Parmigiani, A.B. Nobel, and H. Tjelmeland Maintainer: Robert Scharpf source.ver: src/contrib/XDE_2.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/XDE_2.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/XDE_2.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/XDE_2.8.0.tgz vignettes: vignettes/XDE/inst/doc/XDE.pdf, vignettes/XDE/inst/doc/XdeParameterClass.pdf vignetteTitles: XDE Vignette, XdeParameterClass Vignette hasREADME: FALSE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/XDE/inst/doc/XDE.R, vignettes/XDE/inst/doc/XdeParameterClass.R Package: xmapbridge Version: 1.20.0 Depends: R (>= 2.0), methods Suggests: RUnit, RColorBrewer License: LGPL-3 MD5sum: 5bd757bb18741cae279de4c66604b53d 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_1.20.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/xmapbridge_1.20.0.zip win64.binary.ver: bin/windows64/contrib/3.0/xmapbridge_1.20.0.zip mac.binary.ver: bin/macosx/contrib/3.0/xmapbridge_1.20.0.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: 1.22.2 Depends: R (>= 2.6.0), methods, utils Suggests: tools License: GPL (>= 2.0) Archs: i386 MD5sum: e0b7cdcc2b01f21848cd4c8152d7274a 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_1.22.2.tar.gz win.binary.ver: bin/windows/contrib/3.0/xps_1.22.2.zip win64.binary.ver: bin/windows64/contrib/3.0/xps_1.22.2.zip mac.binary.ver: bin/macosx/contrib/3.0/xps_1.22.2.tgz vignettes: vignettes/xps/inst/doc/APTvsXPS.pdf, vignettes/xps/inst/doc/xps.pdf, vignettes/xps/inst/doc/xpsClasses.pdf, vignettes/xps/inst/doc/xpsPreprocess.pdf vignetteTitles: 3. XPS Vignette: Comparison APT vs XPS, 1. XPS Vignette: Overview, 2. XPS Vignette: Classes, 4. XPS Vignette: Function express() hasREADME: TRUE hasNEWS: TRUE hasINSTALL: FALSE hasLICENSE: FALSE Rfiles: vignettes/xps/inst/doc/APTvsXPS.R, vignettes/xps/inst/doc/xps.R, vignettes/xps/inst/doc/xpsClasses.R, vignettes/xps/inst/doc/xpsPreprocess.R Package: XVector Version: 0.2.0 Depends: R (>= 2.8.0), methods, BiocGenerics (>= 0.7.2), IRanges (>= 1.19.36) Imports: methods, BiocGenerics, IRanges LinkingTo: IRanges Suggests: Biostrings, drosophila2probe, RUnit License: Artistic-2.0 Archs: i386, x64 MD5sum: d5c6799b09b67f1fa5942ed6d60e5452 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_0.2.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/XVector_0.2.0.zip win64.binary.ver: bin/windows64/contrib/3.0/XVector_0.2.0.zip mac.binary.ver: bin/macosx/contrib/3.0/XVector_0.2.0.tgz hasREADME: FALSE hasNEWS: FALSE hasINSTALL: FALSE hasLICENSE: FALSE dependsOnMe: Biostrings, DECIPHER, GenomicRanges, motifRG, Rsamtools, rSFFreader, triplex, VariantAnnotation importsMe: Biostrings, ChIPsim, DECIPHER, gcrma, Gviz, R453Plus1Toolbox, rSFFreader, rtracklayer, VariantAnnotation suggestsMe: IRanges Package: yaqcaffy Version: 1.22.0 Depends: simpleaffy (>= 2.19.3), methods Imports: stats4 Suggests: MAQCsubsetAFX, affydata, xtable, tcltk2, tcltk License: Artistic-2.0 MD5sum: db7071e55fbfb761c7d7ce1fd996c108 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_1.22.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/yaqcaffy_1.22.0.zip win64.binary.ver: bin/windows64/contrib/3.0/yaqcaffy_1.22.0.zip mac.binary.ver: bin/macosx/contrib/3.0/yaqcaffy_1.22.0.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: 1.8.0 License: Artistic-2.0 + file LICENSE Archs: i386, x64 MD5sum: 699d7d5bc95ba1da70d5776f2f98089d 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_1.8.0.tar.gz win.binary.ver: bin/windows/contrib/3.0/zlibbioc_1.8.0.zip win64.binary.ver: bin/windows64/contrib/3.0/zlibbioc_1.8.0.zip mac.binary.ver: bin/macosx/contrib/3.0/zlibbioc_1.8.0.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, ChemmineOB, DiffBind, makecdfenv, oligo, QuasR, rhdf5, Rsamtools, rtracklayer, seqbias, ShortRead, Starr, VariantAnnotation