| GSA.genescores {GSA} | R Documentation | 
Individual gene scores from a gene set analysis
Description
Compute individual gene scores from a gene set analysis
Usage
GSA.genescores(geneset.number, genesets,  GSA.obj,  genenames, negfirst=FALSE)
Arguments
| geneset.number | Number indicating which gene set is to examined | 
| genesets | The gene set collection | 
| GSA.obj | Object returned by function GSA | 
| genenames | Vector of gene names for gene in expression dataset | 
| negfirst | Should negative genes be listed first? Default FALSE | 
Details
Compute individual gene scores from a gene set analysis. Useful for looking “inside” a gene set that has been called significant by GSA.
Value
A list with components
| res | Matrix of gene names and gene scores (eg t-statistics) for each gene in the gene set | 
,
Author(s)
Robert Tibshirani
References
Efron, B. and Tibshirani, R. On testing the significance of sets of genes. Stanford tech report rep 2006. http://www-stat.stanford.edu/~tibs/ftp/GSA.pdf
Examples
######### two class unpaired comparison
# y must take values 1,2
set.seed(100)
x<-matrix(rnorm(1000*20),ncol=20)
dd<-sample(1:1000,size=100)
u<-matrix(2*rnorm(100),ncol=10,nrow=100)
x[dd,11:20]<-x[dd,11:20]+u
y<-c(rep(1,10),rep(2,10))
genenames=paste("g",1:1000,sep="")
#create some random gene sets
genesets=vector("list",50)
for(i in 1:50){
 genesets[[i]]=paste("g",sample(1:1000,size=30),sep="")
}
geneset.names=paste("set",as.character(1:50),sep="")
GSA.obj<-GSA(x,y, genenames=genenames, genesets=genesets,
             resp.type="Two class unpaired", nperms=100)
# look at 10th gene set
GSA.genescores(10, genesets, GSA.obj, genenames)
[Package GSA version 1.03.3 Index]