topGOres {compEpiTools} | R Documentation

## determines GeneOntology (GO) enriched terms for a set of Entrez gene ids

### Description

determines GeneOntology (GO) enriched terms for a set of Entrez gene ids

### Usage

    topGOres(ids, ontology='BP', Pthr=1e-05, maxN=5000, minN=5,
    orgdb, allEG=keys(orgdb),showTerms=NULL)

### Arguments

`ids` | can be either a vector or a list of human or mouse EntrezGene ids
`ontology` | one of the three GO ontologies: BP (Biological Processes), CC (Cellular Components) or MF (Molecular Functions)
`Pthr` | numeric [0,1]; the p-value for an enrichment to be considered significant
`maxN` | numeric; only GO terms with a total up to maxN genes annotated on the genome are considered
`minN` | numeric; only GO terms with a minimum of minN genes annotated on the genome are considered
`orgdb` | An object of class OrgDb; either org.Hs.eg.db, org.Mm.eg.db or org.Dm.eg.db
`allEG` | character; the reference universe of EntrezGene ids, by default all of them
`showTerms` | numeric: the number of GO terms to plot; NULL: no plotting

### Details

Determines GeneOntology (GO) enriched terms for a set of Entrez gene ids. Based on the topGO Bioconductor library. Both maxN and minN refer to the number of genes annotated in the reference genome for a given GO term (indipendently from the ids that the enrichment is being evaluated for). This can be used for excluding GOterm very generic or very specific, since these would mostly be ignored in the final output. This would also save time in the analysis and decrease the severity of the multiple testing issue.

### Value

A matrix containing enriched GO terms ranked by significance is returned, with the following columns:

`GO.ID` | GO id
`Term` | text description of the GO id
`Annotated` | total number of genes annotated with the considered GOterm
`Significant` | number of genes in ids for the specific GOterms
`Expected` | expected number of GOterms genes in ids in case of random enrichment
`Classic` | pvalue for the enrichment as reported from the topGO package
`Genes` | Gene ids of significantly annotated genes for each specific GOterms

### References

http://genomics.iit.it/groups/computational-epigenomics.html

### See Also

topGOdata in the topGO Bioconductor package

### Examples

    require(org.Mm.eg.db)
    egs <- keys(org.Mm.egACCNUM)[1:50]
    topGOres(ids=egs, Pthr=0.006, maxN=5000, minN=5,
    	orgdb=org.Mm.eg.db, allEG=keys(org.Mm.eg.db)[1:5000])

[Package compEpiTools version 1.16.0 Index]