On 09/13/2011 05:21 AM, Sandeep Amberkar wrote:> Dear All,
>
> I need to fetch GO ontologies for Homo sapiens with their mappings to
> corresponding Uniprot identifiers. I would be using this information to
> compare result from a clustering algorithm with existing protein complexes.
> This would be a test to check how the clustering algorithm accurately
> captures GO terms with respect to the known protein complexes. Can anyone
> suggest a simple workflow with the requisite packages? I am trying to find
> out to fetch GO ontologies for homo sapiens with bioconductor but most
> packages are designed for enrichment analysis. Am I missing something here?
> Any help would be greatly appreciated.
Hi,
Ask on the Bioconductor list.
bioconductor.org/help/mailing-list
For the annotation part of your question, GO.db represents the GO
ontologies. org.Hs.eg.db contains information on uniprot mappings. These
are 'bi-maps' that map from a central identifier (GO id for GO.db;
Entrez id for *eg.db). So for instance
> GOTERM[["GO:0000022"]] # [[ to extract single entries
GOID: GO:0000022
Term: mitotic spindle elongation
Ontology: BP
Definition: Lengthening of the distance between poles of the mitotic
spindle.
Synonym: spindle elongation during mitosis
> egid <- revmap(org.Hs.egGO)[["GO:0000022"]] # reverse map,
extract
> toTable(org.Hs.egUNIPROT[egid]) # subset map; convert to data.frame
gene_id uniprot_id
1 9055 O43663
2 9493 Q02241
There are vignettes, e.g., browseVignettes("AnnotationDbi").
To me your analysis sounds like some kind of hypergeometric test. The
GOstats package is designed to do these, in the context of the GO
directed acyclic graph.
Martin
>
> Thanks a lot in advance.
>
>
> --
> Warm Regards,
> Sandeep Amberkar
> BioQuant,BQ26,
> Im Neuenheimer Feld 267,
> D-69120,Heidelberg
>
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>
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