GSA.listsets: List the results from a Gene set analysis

Description

List the results from a call to GSA (Gene set analysis)

Usage

GSA.listsets(GSA.obj, geneset.names = NULL, maxchar = 20, FDRcut = 0.2)

Arguments

GSA.obj

Object returned by GSA function

geneset.names

Optional vector of names for the gene sets

maxchar

Maximum number of characters in printed output

FDRcut

False discovery rate cutpoint for listed sets. A value of 1 will cause all sets to be listed

Value

A list with components

FDRcut

The false discovery rate threshold used.

negative

A table of the negative gene sets. "Negative" means that lower expression of most genes in the gene set correlates with higher values of the phenotype y. Eg for two classes coded 1,2, lower expression correlates with class 2. For survival data, lower expression correlates with higher risk, i.e shorter survival (Be careful, this can be confusing!)

positive

A table of the positive gene sets. "Positive" means that higher expression of most genes in the gene set correlates with higher values of the phenotype y. See "negative" above for more info.

nsets.neg

Number of negative gene sets

nsets.pos

Number of positive gene sets

Details

This function list the sigificant gene sets, based on a call to the GSA (Gene set analysis) function.

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

Run this code

# NOT RUN {
######### 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 radnom 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)


GSA.listsets(GSA.obj, geneset.names=geneset.names,FDRcut=.5)


# }

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