topGOres: determines GeneOntology (GO) enriched terms for a set of...

In kamalfartiyal84/compEpiTools: Tools for computational epigenomics

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])

kamalfartiyal84/compEpiTools documentation built on May 29, 2019, 5:40 a.m.