R: Individual gene scores from a gene set analysis

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 Index]