changed output format to contain FPKM etc. ; fixed a bug for paired-end reads

[rsem.git] / EBSeq / man / GeneMultiSimu.Rd

diff --git a/EBSeq/man/GeneMultiSimu.Rd b/EBSeq/man/GeneMultiSimu.Rd
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-\name{GeneMultiSimu}
-\alias{GeneMultiSimu}
-%- Also NEED an '\alias' for EACH other topic documented here.
-\title{
-Gene Level Simulation for multiple conditions
-}
-\description{
-Simulate Gene level expression data from a Negative Binomial assumption. (Without outliers)
-}
-\usage{
-GeneMultiSimu(DVDconstant = NULL, DVDqt1 = NULL, DVDqt2 = NULL, Conditions,AllParti, NumofSample, NumofGene = NULL, DEGeneProp, Phiconstant = NULL, Phi.qt1 = NULL, Phi.qt2 = NULL, Meanconstant = NULL,  NormFactor=NULL, OnlyData = T)
-}
-%- maybe also 'usage' for other objects documented here.
-\arguments{
-  \item{DVDconstant}{
-Whether want to use constant fold change value for all the DE genes. 
-If set DVDconstant=4, all the DE genes will have fold change of 4 across two condtions. 
-If this parameter is specified, the settings of DVDqt1 and DVDqt2 will be ignored. 
-}
-  \item{DVDqt1, DVDqt2}{
-If DVDconstant is not specified, the user could use a range of empirical DVD's f
-rom Gould' data. The lower and upper bound ( quantile) could be specified.
-The suggested value is c(.96, .97). DVD for each gene will be randomly choosed within the range.
-
-}
-  \item{Conditions}{
-A vector of charecters to show each sample's condition. 
-(Only the two-condition case is supported now)
-}
-\item{AllParti}{
-           A matrix indicates the interested patterns. Columns shoule be conditions and rows should be patterns.
-                   The matrix could be obtained by the GetPatterns function. If AllParti=NULL, all possible patterns will be used.
-}
-
-  \item{NumofSample}{
-Number of samples to generte.
-}
-  \item{NumofGene}{
-Number of genes to generate.
-}
-  \item{DEGeneProp}{
-The proportion of genes to be generated as DE. The value should be in [0, 1].
-Besides, the same proportion of genes will be generated as EE genes with outlier. 
-The genes will be generated as EE at first, then the count of one of the samples 
-(randomly selected) will be setted as its original counts multiplied by one of (4, 6, 8, 10).
-}
-  \item{Phiconstant}{
-Whether set the disperse parameter phi to be a constant. If this parameter is specified, the settings of Phi.qt1 and Phi.qt2 will be ignored.
-}
-  \item{Phi.qt1, Phi.qt2}{
-If Phiconstant is not specified, the user could use a range of empirical phi's from Gould' data. The lower and upper bound ( quantile) could be specified.
-The suggested value is c(.25, .75). phi for each gene will be randomly choosed w
-ithin the range.
-
-}
-  \item{Meanconstant}{
-Wether set the mean of each gene to be a constant.
-}
-  \item{OnlyData}{
-Wether the user only want the generated data matrix. If OnlyData=T, the function will return the simulated matrix
-and the name of the DE genes.
-Otherwise the funtion will run DESeq, EBSeq, edgeR, baySeq and BBSeq and provide the results of each method. 
-}
-
-\item{NormFactor}{
-If NormFactor is NULL, each lane will be set to be with the same library size. Otherwise NormFactor should be a 
-vector with length NumofSample. 
-}
-
-}
-\details{
-For each gene, we assumed that the expression follows a Negative Binomial distribution with mean mu_g and variance mu_g * (1 + mu_g * phi_g). 
-For DE genes, we assumed that in one condition the genes are with mean mu_g * DVD.
-mu, phi and DVD could be specified by the parameter settings.
-}
-\value{
-\item{data}{
-A matrix of expression values will be generated. The rows of the matrix refer to the genes and the columns of the matrix are the samples. The genes are named "G_1", "G_2", ... The first part of the genes will be the DE ones. (The number depends on the DEGeneProp parameter.)
-}
-\item{Patterns}{The pattern each gene belongs to}
-
-}
-
-\references{
-%% ~put references to the literature/web site here ~
-}
-\author{
-Ning Leng
-}
-\note{
-%%  ~~further notes~~
-}
-
-%% ~Make other sections like Warning with \section{Warning }{....} ~
-
-\seealso{
-IsoSimu, IsoSimuAt, GeneSimuAt
-}
-\examples{
-Conditions=c("C1","C1","C2","C2","C3","C3")
-PosParti=GetPatterns(Conditions)
-AllParti=PosParti[-3,]
-
-MultiData=GeneMultiSimu(Conditions=Conditions,AllParti=AllParti,
-                                                                       NumofSample=6,NumofGene=1000,DEGeneProp=c(.7,.1,.1,.1),
-                                                                                                                       DVDqt1=.98,DVDqt2=.99,Phi.qt1=.25,Phi.qt2=.75)
-
-}
-% Add one or more standard keywords, see file 'KEYWORDS' in the
-% R documentation directory.
-\keyword{ simulation }
-\keyword{ ~kwd2 }% __ONLY ONE__ keyword per line