[BioC] hyperGTest, different Results using different annotation packages

[Marc Carlson]

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
>
>