Hypergeometric test of gene set enrichment - Calculate P-value for multiple gene sets in one script?

Hi,

I have around 100 different gene sets (as tab-delimited files, no ranking) and would like to see whether my experimental gene list is enriched for any of those gene sets, by hypergeometric testing in R. (This is a custom genome (Toxoplasma gondii), I can't use e.g. PANTHER, DAVID, ReactomePA as far as I can tell). I'm an R novice and am lost as to how to do this test for multiple gene sets. To test one gene set, I've been using (a bit long-winded):

dhyperRandom <- function(myGeneList, myGeneSet, genome){
myRandomGS <- sample( genome,size=length(myGeneSet) )
myX <- length(which(myGeneList %in% myRandomGS))
myM <- length(myRandomGS)
myN <- length(genome) - length(myM)
myK <- length(myGeneList)
return(dhyper(x=myX, m=myM, n=myN, k=myK))
 }
for(i in 1:1000){
 pvalue[i] <- dhyperRandom( myGeneList, myGeneSet, genome )
}

mean(pvalue)

I could go through each gene set individually...but there must be a way of automating this process and reporting the data in a single table. I'd be very grateful for any suggestions!

Natalie

next-gen r go

• 7,403 views • link

updated 4.3 years ago by Ram

• written 11.5 years ago by nsilmondemonerri •

As you did loop for permutations, write similar loop for gene lists. I would try something like this:

foreach(my.list=allGeneSets, .combine=rbind) %do% {
    myGeneSet <- fread(my.list)
    for(i in 1:1000){
        pvalue[i] <- dhyperRandom(myGeneList, myGeneSet, genome)
    }
}

You should have paths to your datasets in allGeneSets. This is not tested, suggestions to optimize are welcome :-)

• 0 views • link

updated 4.3 years ago by Ram

• written 11.5 years ago by PoGibas

Thanks a lot for your suggestion Pgibas! I pasted the random gene set iterations but perhaps should start with just a regular hypergeometric test on each gene set. I tried what you suggested but having some problems. This is the code I'm trying:

#Set paths to files
allGeneSets<-list.files("path", full.names=TRUE)
genome<-t(fread("path"))
myGeneList<-fread("path")
hypervalues<-c()
dhyper_my <- function(myGeneList, myGeneSet, genome){
myX <- length(which(myGeneList %in% myGeneSet))
myM <- length(myGeneSet)
myN <- length(genome) - length(myM)
myK <- length(myGeneList)
return(dhyper(x=myX, m=myM, n=myN, k=myK))
 }
foreach(my.list=allGeneSets, .combine=rbind) %do% {
    myGeneSet <- fread(my.list)
    for(i in 1:73){
        hypervalues[i] <- dhyper_my( myGeneList, myGeneSet, genome )
    }
}

Output:

NULL, In dhyper(x = myX, m = myM, n = myN, k = myK) : NaNs produced

When I do length(which(myGeneList %in% myGeneSet)) separately I get the wrong number... This is what the files look like that I'm reading in:

TGME49_259010    TGME49_285240    TGME49_214440    TGME49_273740    TGME49_288450    TGME49_263130    TGME49_268850    TGME49_238950    TGME49_318580    TGME49_249390    TGME49_273490    TGME49_275568    TGME49_226400    TGME49_262760    TGME49_284190

Sorry if these are stupid questions! Like I said, R newbie :)

• 0 views • link

updated 4.3 years ago by Ram

• written 11.5 years ago by nsilmondemonerri •

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