[BioC] Extract genes for a GO term in GOstat

Chao-Jen Wong cwon2 at fhcrc.org
Thu Jun 3 20:56:16 CEST 2010


Oh, never mind. James and Steve have suggested better ways to do it.
On 06/03/10 10:17, Chao-Jen Wong wrote:
> Hi, Rohit,
>
> I wrote a short script to extract the gene associated with the
> over-represented GO terms. Hope this would help. Let me know if it
> doesn't work.
>
> your code is:
>   
>> params <- new("GOHyperGParams", geneIds=entrez.ids,
>> annotation=c("hgu133plus2"), ontology="BP", pvalueCutoff=0.05,
>> conditional=FALSE, testDirection="over")
>> resultBP<-hyperGTest(params)
>>
>> please help to find out the genes associated with the go terms
>>
>> Rohit
>>   
>>     
> You can do the following:
>
> p <- params
> origGeneIds <- geneIds(p)
> selected <- intersect(geneIds(p), universeGeneIds(p))
> cat2Entrez <- categoryToEntrezBuilder(p)
> ## get the gene (Entrez ID) in the category
> geneInCat <- lapply(as.list(summary(resultBP)[,1]),
>                     function(goid) {
>                       selected[selected %in% cat2Entrez[[goid]]]
>                     } )
>
> ## if you want to convert the Entrez ID to manufacture id
> x=revmap(as.list(hgu133plus2ENTREZID))
> geneInCatName <- lapply(geneInCat, function(geneid) {
>                         unlist(lapply(as.list(geneid), function(id)
>                             sel[sel %in% x[[id]] ] ))
>                         })
>   names(geneInCatName) <- summary(hgOver$result)[,1]
>   ## return
> geneInCatName
>
>
>   


-- 
Chao-Jen Wong
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Avenue N., M1-B514
PO Box 19024
Seattle, WA 98109
206.667.4485
cwon2 at fhcrc.org



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