\name{SetMethodsSims-class}
\docType{class}
\alias{SetMethodsSims-class}
\alias{SetMethodsSims-method}
\alias{show,SetMethodsSims-method}

\title{Class representation for depositing output from simulations.}
\description{Stores results from the \code{sim.data.p.values} function.}

\section{Objects from the class}{

 New objects can be created using calls of the form 
 \code{new("SetMethodsSims", null.dist, perc.samples, spiked.set.sizes,
       GeneSizes, GeneSets, Coverage, EventsBySample, Mutations, Scores,
       results)}

}

\section{Slots}{
  \describe{
    \item{\code{null.dist}:}{Object of class \code{"character"}.
    		  	     Can be either "Passenger null" or
			     "Permutation null," depending on what 
			     method is used to get the null data.} 
    \item{\code{perc.samples}:}{Object of class \code{"numeric"}.
    				Vector representing the probabilities 
				of the spiked-in gene-sets being
  				altered in any given sample, as percentages; 
				for example
				\code{perc.samples = c(75, 90)} 
				means that these probabilities are
				\code{0.75} and \code{0.90}.} 
    \item{\code{spiked.set.sizes}:}{Object of class \code{"numeric"}. 
    				    Vector representing the sizes, in genes, 
				    of the spiked-in gene-sets;
				    for example, if 
				    \code{perc.samples = c(75, 90)} and
				    \code{spiked.set.sizes = c(50, 100)}, 
				    there would be 4 spiked-in sets,
				    one with 50 genes and probability of 
				    being altered of 0.75 in each sample,
				    one with 50 genes and probability of 
				    being altered of 0.90 in each sample,
				    one with 100 genes and probability of 
				    being altered of 0.75 in each sample, and
				    one with 100 genes and probability of 
				    being altered of 0.90 in each sample.} 
    \item{\code{GeneSizes}:}{Object of class \code{"list"}.
    			     The entries of the list are objects similar to
			     \code{GeneSizes08} and correspond to the
			     simulation iterations.}
    \item{\code{GeneSets}:}{Object of class \code{"list"}.
    			    The entries of the list correspond to
			    gene-sets and give the genes annotated to them.} 
    \item{\code{Coverage}:}{Object of class \code{"list"}.
    			    The entries of the list are objects similar to
			    \code{CoverageBrain} and correspond to the
			    simulation iterations.}
    \item{\code{EventsBySample}:}{Object of class \code{"list"}.
    			    The entries of the list are objects similar to
			    \code{EventsBySampleBrain} and correspond to the
			    simulation iterations.}
    \item{\code{Mutations}:}{Object of class \code{"list"}.
    			    The entries of the list are objects similar to
			    \code{MutationsBrain} and correspond to the
			    simulation iterations.}
    \item{\code{Scores}:}{Object of class \code{"list"}.
    			  The entries of this list are the output of
			  \code{cma.scores} and correspond to the
			  simulation iterations.}
    \item{\code{results}:}{Object of class \code{"list"}.
    			   The entries of this list are the output of
			   \code{do.gene.set.analysis} and correspond to the
			   simulation iterations.}
  }
}

\section{Methods}{
\describe{
\item{show}{\code{signature(object = "SetMethodsSims")}}
}
}

\references{
Boca S.M., Kinzler K., Velculescu V.E., Vogelstein B.,
Parmigiani G.
Patient-oriented gene-set analysis for cancer mutation data.
\emph{Submitted}, 2010.
}
\author{
Simina M. Boca, Giovanni Parmigiani.
}

\seealso{
\code{CoverageBrain},
\code{EventsBySampleBrain}, \code{GeneSizes08},
\code{MutationsBrain},
\code{sim.data.p.values}, \code{do.gene.set.analysis},
\code{combine.sims}, \code{extract.sims.method}
}

\keyword{datasets}