hyperGTest, different Results using different annotation packages
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@wiebke-iffert-3382
Last seen 9.6 years ago
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 --
Annotation GO AnnotationDbi Annotation GO AnnotationDbi • 1.1k views
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Marc Carlson ★ 7.2k
@marc-carlson-2264
Last seen 7.7 years ago
United States
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 > > > -- > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > >
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