[BioC] hyperGTest, different Results using different annotation packages

[Wiebke Iffert]

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



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