Hi Jenny, Yes and yes. And we don't seem to actually disagree about GO at all. That is what I meant by the "DAG nature of the GO annotations". Marc On 07/05/2011 03:22 PM, Jenny Drnevich wrote: > Hi James (and Marc), > > Shame on me for not searching the archives. Thanks for pointing out > your previous thread with Marc. I do want to make sure I'm > understanding this properly. Using my demo results: > >> > hg.KEGG >> $list1 >> Gene to KEGG test for over-representation >> 190 KEGG ids tested (3 have p < 0.01) >> Selected gene set size: 280 >> Gene universe size: 1629 >> Annotation package: porcine >> >> $list2 >> Gene to KEGG test for over-representation >> 105 KEGG ids tested (1 have p < 0.01) >> Selected gene set size: 54 >> Gene universe size: 1363 >> Annotation package: porcine > > So in list1, there were 280 selected genes that mapped to 190 KEGG > ids, and in the universe there were 1629 genes that mapped to these > same 190 KEGG ids? Where as in list2, there were 54 selected genes > that mapped to 105 KEGG ids and 1363 genes in the universe that mapped > to the same 105 KEGG ids, which is why the "Gene universe size" is > different for the two lists? > > Finally, I have to disagree with the reason why GO testing usually > (always?) gives the same number for the "Gene universe size" - it's > because once you have even a single gene map to any GO term, all the > parent terms are pulled in as well, including the root term for the > lineage - "biological process", "molecular function" or "cellular > component". While this is included, the GO universe will _never_ be > made smaller because any term in the universe that has a BP term will > also map to the root "biological process" term. > > Thanks, > Jenny > > > > > > At 12:05 PM 7/5/2011, James F. Reid wrote: >> Hi Jenny, >> >> I think you'll find the answer in this thread: >> https://stat.ethz.ch/pipermail/bioconductor/2010-May/033439.html >> >> Best, >> J. >> >> On 07/05/2011 06:13 PM, Jenny Drnevich wrote: >>> Hi all, >>> >>> I'm doing both GO and KEGG over-representation testing on several >>> different lists of genes, using the same background set for each list. >>> What's got me puzzled is the difference in the "Gene universe size" >>> reported from the hyperGTest results for each list from the KEGG test, >>> even though they have the same background set. When I make a >>> GOHyperGParams object for each list and test them, the results report >>> the same "Gene universe size" for each list, which I assume to be the >>> number of genes in the background that have any GO MF terms. However, >>> for the KEGG test, each list reports a different "Gene universe size", >>> so I'm unsure how selecting a different list from the same background >>> can change the mapping of the background to KEGG terms. I haven't been >>> able to get into the exact code of calling hyperGTest on a >>> KEGGHyperGParams object, so I don't know what is going on - is it a >>> bug? >>> Or for KEGG terms, is this supposed to happen? Reproducible example and >>> sessionInfo() below. >>> >>> Thanks, >>> Jenny >>> >>> > library(annaffy) >>> Loading required package: Biobase >>> >>> Welcome to Bioconductor >>> >>> Vignettes contain introductory material. To view, type >>> 'browseVignettes()'. To cite Bioconductor, see >>> 'citation("Biobase")' and for packages 'citation("pkgname")'. >>> >>> Loading required package: GO.db >>> Loading required package: AnnotationDbi >>> Loading required package: DBI >>> >>> Loading required package: KEGG.db >>> >>> > library(porcine.db) >>> Loading required package: org.Ss.eg.db >>> >>> >>> > library(GOstats) >>> Loading required package: Category >>> Loading required package: graph >>> > >>> > >>> > all.ids <- Rkeys(porcineENTREZID) >>> > length(all.ids) >>> [1] 30160 >>> > >>> > >>> > set.seed(1234) >>> > list1 <- sample(all.ids,5000) >>> > list2 <- list1[1:1000] >>> > list3 <- list1[4501:5000] >>> > >>> > par.MF.list <- list(list1 = new("GOHyperGParams", geneIds = list1, >>> universeGeneIds = all.ids,ontology="MF", >>> + annotation="porcine.db", testDirection="over", >>> pvalueCutoff=0.01,conditional=F), >>> + list2 = new("GOHyperGParams", geneIds = list2, universeGeneIds = >>> all.ids,ontology="MF", >>> + annotation="porcine.db", testDirection="over", >>> pvalueCutoff=0.01,conditional=F) , >>> + list3 = new("GOHyperGParams", geneIds = list3, universeGeneIds = >>> all.ids,ontology="MF", >>> + annotation="porcine.db", testDirection="over", >>> pvalueCutoff=0.01,conditional=F)) >>> > >>> > hg.MF.list <- lapply(par.MF.list,hyperGTest) >>> > hg.MF.list >>> $list1 >>> Gene to GO MF test for over-representation >>> 1007 GO MF ids tested (1 have p < 0.01) >>> Selected gene set size: 569 >>> Gene universe size: 3198 >>> Annotation package: porcine >>> >>> $list2 >>> Gene to GO MF test for over-representation >>> 419 GO MF ids tested (6 have p < 0.01) >>> Selected gene set size: 106 >>> Gene universe size: 3198 >>> Annotation package: porcine >>> >>> $list3 >>> Gene to GO MF test for over-representation >>> 266 GO MF ids tested (2 have p < 0.01) >>> Selected gene set size: 63 >>> Gene universe size: 3198 >>> Annotation package: porcine >>> >>> #Note the Gene universe size is 3198 for all 3 lists >>> >>> > >>> > >>> > par.KEGG <- list(list1 = new("KEGGHyperGParams", geneIds = list1, >>> universeGeneIds = all.ids, >>> + annotation="porcine.db", testDirection="over", pvalueCutoff=0.01), >>> + list2= new("KEGGHyperGParams", geneIds = list2, universeGeneIds = >>> all.ids, >>> + annotation="porcine.db", testDirection="over", pvalueCutoff=0.01) , >>> + list3= new("KEGGHyperGParams", geneIds = list3, universeGeneIds = >>> all.ids, >>> + annotation="porcine.db", testDirection="over", pvalueCutoff=0.01) ) >>> > >>> > hg.KEGG <- lapply(par.KEGG,hyperGTest) >>> > hg.KEGG >>> $list1 >>> Gene to KEGG test for over-representation >>> 190 KEGG ids tested (3 have p < 0.01) >>> Selected gene set size: 280 >>> Gene universe size: 1629 >>> Annotation package: porcine >>> >>> $list2 >>> Gene to KEGG test for over-representation >>> 105 KEGG ids tested (1 have p < 0.01) >>> Selected gene set size: 54 >>> Gene universe size: 1363 >>> Annotation package: porcine >>> >>> $list3 >>> Gene to KEGG test for over-representation >>> 87 KEGG ids tested (1 have p < 0.01) >>> Selected gene set size: 30 >>> Gene universe size: 1204 >>> Annotation package: porcine >>> >>> # Now there are 3 different Gene universe sizes: 1629, 1363 and >>> 1204. WHY? >>> >>> > >>> > >>> > sessionInfo() >>> R version 2.13.0 (2011-04-13) >>> Platform: x86_64-pc-mingw32/x64 (64-bit) >>> >>> locale: >>> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United >>> States.1252 LC_MONETARY=English_United States.1252 >>> [4] LC_NUMERIC=C LC_TIME=English_United States.1252 >>> >>> attached base packages: >>> [1] stats graphics grDevices utils datasets methods base >>> >>> other attached packages: >>> [1] GOstats_2.18.0 graph_1.30.0 Category_2.18.0 porcine.db_2.4.7 >>> org.Ss.eg.db_2.5.0 annaffy_1.24.0 >>> [7] KEGG.db_2.5.0 GO.db_2.5.0 RSQLite_0.9-4 DBI_0.2-5 >>> AnnotationDbi_1.14.1 Biobase_2.12.1 >>> >>> loaded via a namespace (and not attached): >>> [1] annotate_1.30.0 genefilter_1.34.0 GSEABase_1.14.0 RBGL_1.28.0 >>> splines_2.13.0 survival_2.36-5 tools_2.13.0 >>> [8] XML_3.4-0.2 xtable_1.5-6 >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at r-project.org >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >