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Hi Burak, burak kutlu <burak_kutlu at="" yahoo.com=""> writes: > Hello > I am using hyperGTest to look at the GO enrichments. I am confused > with the output of the test. For a test, I took the genes in my > matrix, and found the those that map to GO:0009790 (there are 8 such > genes). Then I ran hyperGTest: using the 8 genes as the input, the > genes in my matrix as the universe genes (it is a subset of the > genes represented in the hgu133plus2 ). First, I'm a bit confused about what you are trying to accomplish. Usually, hyperGTest is used to find potentially interesting GO terms. Here it seems you are starting with a GO term of interest -- or are you just trying to understand/test hyperGTest? > When I look at the results, the count field is = 3. I would expect > it to be 8. This probably changes the outcome. Am I missing > something? > I include the code below as well as the sessionInfo() output. > Any help is appreciated. I wonder if you could provide a reproducible example? If you can send me off list the myGenes and universeGenes, perhaps I can see what you are seeing. A few comments on your code below... > universeGeneIds = rownames(myMatrix) > genesWithMyGO = as.list(GOALLENTREZID)$'GO:0009790' How about: genesWithMyGO = GOALLENTREZID[["GO:0009790"]] But the GO::GOALLENTREZID map is odd in that it contains data across different organisms. Why not instead: affyWithMyGO = hgu133plus2GO2ALLPROBES[["GO:0009790"]] egWithMyGO = unique(unlist(mget(affyWithMyGO, hgu133plus2ENTREZID))) > geneIds = intersect(genesWithMyGO, universeGeneIds) # there are 8 genes that are in my matrix with this GO id > >> geneIds > [1] "3084" "4683" "5801" "650" "9314" "89870" "2139" "3216" > > params = new("GOHyperGParams", geneIds = mygenes, universeGeneIds = Did you intend to use geneIds instead of mygenes here? > hyp = hyperGTest(params) > t = summary(hyp) > tRep = cbind(t$GOBPID,t$Pvalue,t$OddsRatio,t$ExpCount,t$Count,t$Size,t$Term) > test = tRep[which(tRep[,1]=='GO:0009790'),] # enrichment result with this term > names(test) = c( > "GOBPID","Pvalue","OddsRatio","ExpCount","Count","Size","Term") Why not: t["GO:0009790", ] + seth -- Seth Falcon | Computational Biology | Fred Hutchinson Cancer Research Center http://bioconductor.org

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burak kutlu <burak_kutlu at="" yahoo.com=""> writes: >>But the GO::GOALLENTREZID map is odd in that it contains data across >>different organisms. Why not instead: > >> affyWithMyGO = hgu133plus2GO2ALLPROBES[["GO:0009790"]] >> egWithMyGO = unique(unlist(mget(affyWithMyGO, hgu133plus2ENTREZID))) > > Intersection of 'egWithMyGO' with 'universeGenes' contains 31 genes. > >> mygenes = intersect(egWithMyGO, universeGeneIds) > > When I run the hyperGTest... > >> params = new("GOHyperGParams", geneIds = mygenes, universeGeneIds = universeGeneIds, > annotation = "hgu133plus2",ontology = "BP", pvalueCutoff = 0.05,conditional = FALSE,testDirection = "over") > >> hyp = hyperGTest(params) >> t = summary(hyp) > > I get: > >> t["GO:0009790",] > GOBPID Pvalue OddsRatio ExpCount Count Size > GO:0009790 GO:0009790 4.455886e-60 Inf 0.9285024 31 31 > Term > GO:0009790 embryonic development > > > This result does make sense, note that the Count and Size are the > same, 31. We used 31 genes as input, got 31 back. So my question > about hyperGTest is answered, I was just confused with the different > number of genes. > > Then my new question is why does 'GOALLENTREZID' contain only 8 > genes associated with GO:0009790 while 'egWithMyGO' obtained from > 'hgu133plus2GO2ALLPROBES' contains more, i.e. 31 genes. One would > expect at least the same amount of genes in both environments or > maybe more in 'GOALLENTREZID' because affy chip does not represent > all the genes? I'm confused. Here's what I see with egWithMyGO computed as above: > egFromGO = unique(GOALLENTREZID[["GO:0009790"]]) > length(egFromGO) [1] 3963 > all(egWithMyGO %in% egFromGO) [1] TRUE I'm using devel versions here, so there could be differences in the counts, but I really expect the egWithMyGO to be a subset of egFromGO. -- Seth Falcon | Computational Biology | Fred Hutchinson Cancer Research Center http://bioconductor.org