Creates features from a GSA analysis that can be used in other procedures

Description

Creates features from a GSA analysis that can be used in other procedures, for example, sample classification.

Usage

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GSA.make.features(GSA.func.obj, x, genesets, genenames)

Arguments

GSA.func.obj

Object returned by GSA.func

x

Expression dataset from which the features are to be created

genesets

Gene set collection

genenames

Vector of gene names in expression dataset

Details

Creates features from a GSA analysis that can be used in other procedures, for example, sample classification. For example, suppose the GSA analysis computes a maxmean score for gene set 1 that is positive, based on the mean of the positive part of the scores in that gene set. Call the subset of genes with positive scores "A". Then we compute a new feature for this geneset, for each sample, by computing the mean of the scores for genes in A, setting other gene scores to zero.

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

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######### 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.func.obj<-GSA.func(x,y, genenames=genenames, genesets=genesets,  resp.type="Two class unpaired")


GSA.make.features(GSA.func.obj, x, genesets, genenames)