Hi Marc, I updated the Category package to Category_2.8.4 and now the results are the same. Thanks for your help. wiebke > Hi Wiebke, > > When did you make your custom annotation package? And when you made it, > was if made from the same human.db0 package (IOW the same release) as > the org.Hs.eg.db package that you compared it to? Based on the > sessionInfo() below, you should have the human.db0 2.2.5 installed in > order for these packages to be comparable. > > > Marc > > > > Wiebke Iffert wrote: > > Dear All, > > > > I want to do an analysis using the function hyperGTest from pakage > GOstats. > > When I use the geneIDs of my own annotation package a get other result > from the analysis than when using the annotation package org.Hs.eg.db. > > > > I have built my own annotation package using AnnotationDbi following the > instructions in the vignette (I'm using data from a self spotted > microarray with oligonucleotides which I mapped to Entrez geneIDs): > > > > > >> library(AnnotationDbi) > >> makeHUMANCHIP_DB(affy=FALSE, prefix="HighDensityArray", > fileName="high_density_array_oid2eg.txt", >baseMapType="eg", outputDir = getwd(), > version="1.0.2", manufacturer = "selfspotted", > >> chipName = "High Density Array", manufacturerUrl = "NA") > >> > > > > To build an object of class GOHyperGParams, I used the geneIDs > corresponding to the oligonucleotides of interest. > > > > > >> paramsBPover<-new("GOHyperGParams",geneIds= > genesOfInterest,universeGeneIds= allgenes, >annotation="HighDensityArray.db", ontology="BP", > pvalueCutoff=0.05, conditional=FALSE, >testDirection="over", categoryName="GO") > >> hgOver.BP<-hyperGTest(paramsBPover) > >> > > > > and I got the result: > > > >> hgOver.BP > >> > > Gene to GO BP test for over-representation > > 1449 GO BP ids tested (180 have p < 0.05) > > Selected gene set size: 203 > > Gene universe size: 1768 > > Annotation package: HighDensityArray.db > > > > > > By coincidence I started the same methods using the annotation package > org.Hs.eg.db with the same geneIDs: > > > > > >> paramsBPover2<-new("GOHyperGParams",geneIds= > genesOfInterest,universeGeneIds= allgenes, >annotation="org.Hs.eg.db", ontology="BP", > pvalueCutoff=0.05, conditional=FALSE, testDirection="over", >categoryName="GO") > >> hgOver.BP2<-hyperGTest(paramsBPover2) > >> > > > > and I got the result: > > > >> hgOver.BP2 > >> > > Gene to GO BP test for over-representation > > 967 GO BP ids tested (118 have p < 0.05) > > Selected gene set size: 203 > > Gene universe size: 1768 > > Annotation package: org.Hs.eg.db > > > > Shouldn't I get the same results independent from these 2 annotation > packages? (I thougth that my package HighDensityArray is something like an > subset of the org.Hs.eg.db package, but using my oligonucleotide IDs as > Identifier instead of geneIDs - or did I get that wrong?). > > Which analysis is the one to rely on? > > > > > > Thanks in advance for any help. > > wiebke > > > > > > P.S. > > sessionInfo() > > R version 2.8.0 (2008-10-20) > > i386-apple-darwin8.11.1 > > > > locale: > > de_DE.UTF-8/de_DE.UTF-8/C/C/de_DE.UTF-8/de_DE.UTF-8 > > > > attached base packages: > > [1] splines tools stats graphics grDevices utils > > [7] datasets methods base > > > > other attached packages: > > [1] org.Hs.eg.db_2.2.6 GOstats_2.8.0 > > [3] RBGL_1.18.0 GO.db_2.2.5 > > [5] HighDensityArray.db_1.0.2 RSQLite_0.7-1 > > [7] DBI_0.2-4 Category_2.8.1 > > [9] genefilter_1.22.0 survival_2.34-1 > > [11] annotate_1.20.1 xtable_1.5-4 > > [13] AnnotationDbi_1.4.3 graph_1.20.0 > > [15] Biobase_2.2.1 > > > > loaded via a namespace (and not attached): > > [1] GSEABase_1.4.0 XML_1.98-1 cluster_1.11.11 --