\name{GSRI-package}
\alias{GSRI-package}
\alias{GSRI}
\docType{package}
\title{Gene Set Regulation Index (GSRI)}
\description{
This package estimates the number of differentially expressed genes in gene 
sets with the Gene Set Regulation Index (GSRI).
}
\details{
\tabular{ll}{
Package: \tab GSRI\cr
Type: \tab Package\cr
Version: \tab 0.99.5\cr
Date: \tab 2010-04-20\cr
License: \tab GPL-2\cr
LazyLoad: \tab yes\cr
}
This method calculates the number of differentially expressed genes in a gene 
set. It does not require a cut-off value for the distinction between regulated 
and unregulated genes. The approach is based on the fact that p-values obtained 
from a statistical test are uniformly distributed under the null hypothesis and 
accumulated around zero for the alternative hypothesis.

The Gene Set Regulation Index (GSRI) is the 5\%-quantile of the distribution of 
the estimated number of differentially expressed genes obtained from 
bootstrapping the group samples. It indicates, that with a probability of 95\% 
more than GSRI genes in the gene set are differentially expressed. This index 
can also be employed to test the hypothesis whether at least one gene in a set 
is regulated and to compare and rank the regulation of different gene sets, see 
Bartholomé et al. 2009.
}
\author{
Kilian Bartholome, Julian Gehring

Maintainer: Julian Gehring <julian.gehring@fdm.uni-freiburg.de>
}
\references{
Kilian Bartholomé, Clemens Kreutz, and Jens Timmer:
Estimation of gene induction enables a relevance-based ranking of gene sets,
Journal of Computational Biology: A Journal of Computational Molecular Cell 
Biology 16, no. 7 (July 2009): 959-967.
\url{http://www.liebertonline.com/doi/abs/10.1089/cmb.2008.0226}

Functions of the following packages are used in this package:

Korbinian Strimmer (2009).
fdrtool: Estimation and Control of (Local) False Discovery Rates.
R package version 1.2.6.
\url{http://CRAN.R-project.org/package=fdrtool}

R. Gentleman, V. Carey, W. Huber and F. Hahne.
genefilter: methods for filtering genes from microarray experiments.
R package version 1.28.2.
}
\keyword{package}
\seealso{
\code{\link{gsri}}

\code{\link{gsriFromFile}}
}
\examples{
## Simulate expression data for a gene set of:
## 100 genes, 40 samples (20 treatment, 20 control)
## and 30 regulated genes
expdata <- matrix(rnorm(4000,mean=0),nrow=100,ncol=40)
expdata[1:30,1:20] <- rnorm(600,mean=1)
data <- data.frame(expdata)
phenotype <- c(rep(0,20),rep(1,20))
geneSetName <- "Test Gene Set"

## Estimate the number of differentially expressed genes
res <- gsri(data, phenotype, geneSetName)


## Read expression data, phenotypes and gene sets from files
## Input files can be found in the vignette directory of this package
dataFileName <- system.file("extdata", "data.gct", package="GSRI")
phenotypeFileName <- system.file("extdata", "phenotype.cls", package="GSRI")
geneSetFileName <- system.file("extdata", "geneSets.gmt", package="GSRI")

res2 <- gsriFromFile(dataFileName, phenotypeFileName, geneSetFileName)
}