GSVQ: Gene Set Validation with QTL using Hyper-geometric test...
In GSAQ: Gene Set Analysis with QTL

Description Usage Arguments Value Author(s) Examples

The function computes ths statisical significance value (p-value) for gene set validation using hypergeometric test.

1	GSVQ(geneset, genelist, qtl)

`geneset`	geneset is a vector of characters representing the names of genes/ gene ids selected from the whole gene list by using a gene selection method.
`genelist`	genelist is a N by 3 dataframe/ matrix (genes/gene ids as row names): where, N represents the number of genes in the whole gene set: first coloumn represnting the chromosomal location of genes: second coloumn representing the start position of genes in terms of basepairs: third coloumn representing the end position of genes in terms of basepairs.
`qtl`	qtl is a Q by 3 dataframe/matrix (qtl names/qtl ids as row names);where, Q represents the number of qtls: first coloumn represnting the chromosomal location of qtls: second coloumn representing the start position of qtls in terms of basepairs: third coloumn representing the end position of qtls in terms of basepairs.

The function returns the statisical significance value (p-value) from Hyper-geometric test for validation of the selected gene set with qtl data.

Samarendra Das

data(rice_salt)
data(genelist)
data(qtl_salt)
x=as.data.frame(rice_salt[-1,])
y=as.numeric(rice_salt[1,])
geneset= GeneSelect(x, y, s=50, method="t-score")$selectgenes
genelist=as.data.frame(genelist)
qtl=as.data.frame(qtl_salt)
GSVQ(geneset, genelist, qtl)