> The only GO terms that are tested are those that arise from mapping your
Entrez Gene IDs to GO terms.
Just to be clear, you mean by mapping the *significant*/selected Entrez
Gene IDs (say by a differential expression analysis) to GO terms? Because
the universe/possible Entrez Gene IDs on the microarray was identical in
both examples below.

Thanks,
Andrew

On Mon, Apr 23, 2012 at 10:42 AM, James W. MacDonald <jmacdon@uw.edu> wrote:

> Hi Andrew,
>
> On 4/20/2012 10:50 PM, Andrew Jaffe wrote:
> > Hopefully I can get a quick answer to this question about GOstats.
> >
> > I'm trying to calculate enrichment for every GO category using the
> GOstats
> > package. I would assume that setting the p-value cutoff = 1 with
> > conditional=FALSE would give me an enrichment odds ratio/p-value for
> every
> > GO category in, say, the BP ontology. However, this does not seem to be
> the
> > case, as the number of categories returned seems to be a function of the
> > geneIds supplied:
> >
> >> params = new("GOHyperGParams", geneIds = y$ENTREZID[y$p<  0.001],
> > + universeGeneIds = y$ENTREZID,
> > + annotation = "hgu133plus2.db",
> > + ontology = "BP", pvalueCutoff = 1, conditional = FALSE,
> > + testDirection="over")
> >> ht=hyperGTest(params)
> >> nrow(summary(ht))
> > [1] 6080
> >
> >> params2 = new("GOHyperGParams", geneIds = y$ENTREZID[y$p<  0.01],
> >          universeGeneIds = y$ENTREZID,
> > + universeGeneIds = y$ENTREZID,
> > + annotation = "hgu133plus2.db",
> > + ontology = "BP", pvalueCutoff = 1, conditional = FALSE,
> > + testDirection="over")
> >> ht2=hyperGTest(params2)
> >> nrow(summary(ht2))
> > [1] 7856
> >
> > Does the HyperGTest function drop GO categories without any genes in them
> > prior to returning the results table? Or is something else going on?
>
> Technically, yes. The only GO terms that are tested are those that arise
> from mapping your Entrez Gene IDs to GO terms.
>
> Best,
>
> Jim
>
>
> >
> > Thanks,
> > Andrew
> >
> >> sessionInfo()
> > R version 2.15.0 Patched (2012-04-20 r59123)
> > Platform: x86_64-unknown-linux-gnu (64-bit)
> >
> > locale:
> >   [1] LC_CTYPE=en_US.iso885915       LC_NUMERIC=C
> >   [3] LC_TIME=en_US.iso885915        LC_COLLATE=en_US.iso885915
> >   [5] LC_MONETARY=en_US.iso885915    LC_MESSAGES=en_US.iso885915
> >   [7] LC_PAPER=C                     LC_NAME=C
> >   [9] LC_ADDRESS=C                   LC_TELEPHONE=C
> > [11] LC_MEASUREMENT=en_US.iso885915 LC_IDENTIFICATION=C
> >
> > attached base packages:
> > [1] stats     graphics  grDevices datasets  utils     methods   base
> >
> > other attached packages:
> >   [1] GO.db_2.7.1          sva_3.2.0            mgcv_1.7-13
> >   [4] corpcor_1.6.2        hgu133plus2.db_2.7.1 genefilter_1.38.0
> >   [7] RColorBrewer_1.0-5   GOstats_2.22.0       Category_2.22.0
> > [10] org.Hs.eg.db_2.7.1   RSQLite_0.11.1       DBI_0.2-5
> > [13] funxBox_0.1          digest_0.5.2         multtest_2.12.0
> > [16] GSEABase_1.18.0      graph_1.34.0         annotate_1.34.0
> > [19] AnnotationDbi_1.18.0 limma_3.12.0         Biobase_2.16.0
> > [22] BiocGenerics_0.2.0
> >
> > loaded via a namespace (and not attached):
> >   [1] grid_2.15.0      IRanges_1.14.2   lattice_0.20-6   MASS_7.3-17
> >   [5] Matrix_1.0-6     nlme_3.1-103     RBGL_1.32.0      splines_2.15.0
> >   [9] stats4_2.15.0    survival_2.36-12 tools_2.15.0     XML_3.9-4
> > [13] xtable_1.7-0
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
> --
> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099
>
>

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