"Correlates" a gene set collection with a given list of gene nams

Description

"Correlates" a gene set collection with a given list of gene names. Gives info on the overlap between the collection and the list of genes

Usage

GSA.correlate(GSA.genesets.obj, genenames)

Arguments

Details

Gives info on the overlap between a gene set collection and the list of gene names. This is for information purposes, to find out, for example, how many genes in the list of genes appear in the gene set collection.

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.correlate(genesets, genenames)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> library(GSA)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GSA/GSA.correlate.Rd_%03d_medium.png", width=480, height=480)
> ### Name: GSA.correlate
> ### Title: "Correlates" a gene set collection with a given list of gene
> ###   nams
> ### Aliases: GSA.correlate
> ### Keywords: univar survival ts nonparametric
> 
> ### ** 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.correlate(genesets, genenames)

Number of gene-sets: 0

Total number of genes in gene-set collection: 0
Total number of unique genes in gene-set collection: 0

Total number of genes in  genenames list: 1000
Total number of unique genes in genenames list: 1000

Number of unique genes in both collections: 0

Quantiles of fraction coverage of gene-sets
  0%  10%  20%  30%  40%  50%  60%  70%  80%  90% 100% 
  NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA 
NULL
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> dev.off()
null device 
          1 
>