Dear BioC community,
I have a boolean vector called
pval where 1 means differentially expressed and 0 non-DE
, whose element names are the Entrez IDs.
In order to make a GSEA according to GO MF, I do the next:
GOobj <- new("topGOdata", description = "Simple session", ontology = 'MF', allGenes = pval, geneSel = function(x) return(x), nodeSize = 10, annot = annFUN.org, mapping = annotation(transcript), ID = 'entrez') allGO = usedGO(object = GOobj) resultFisher <- runTest(GOobj, algorithm = "classic", statistic = "fisher") allRes <- GenTable(GOobj, classicFisher = resultFisher, orderBy = "classicFisher", ranksOf = "classicFisher", topNodes = length(allGO))
My main problem is that the lowest p-values always correspond to very general terms, such as binding, and therefore they comprise lots of other (probably more interesting) terms. Is there any way to avoid this with the topGO package or is there another package that solves this issue?