[BioC] Quick start to linking GO terms and microarray data

[Ting-Yuan Liu]

Hi Michael,

> Again, I ask, does anyone have any simple examples of going from a list
> of LocusLink IDs to a list of GO Terms?  (i.e. GO identifiers and the
> biological function/term associated with those identifiers)

I think the environment "GOLOCUSID2GO" in the GO package is what you are 
looking for.  Use ?GOLOCUSID2GO to see the examples.  

HTH,
Ting
______________________________________
Ting-Yuan Liu
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
Seattle, WA, USA
______________________________________


> 
> Many thanks
> Mick
> 
> -----Original Message-----
> From: Sean Davis [mailto:sdavis2 at mail.nih.gov] 
> Sent: 01 March 2006 11:44
> To: michael watson (IAH-C); Bioconductor
> Subject: Re: [BioC] Quick start to linking GO terms and microarray data
> 
> 
> 
> 
> On 3/1/06 6:20 AM, "michael watson (IAH-C)" <michael.watson at bbsrc.ac.uk>
> wrote:
> 
> > Hi
> > 
> > I want to investigate the GO terms associated with my microarray data
> > (normally, a list of genes from topTable() in limma)
> > 
> > I have read the vignettes for goTools and GOStats, and to be honest, I
> > am still a little unclear what the overall process is, particularly if
> I
> > am working with a custom array and not with affy or operon.
> > 
> > Lets say, for example, I have my array data in a data.frame containing
> > gene names.  In a separate data frame I have a link between my gene
> > names and LocusLink IDs.  How do I:
> > 
> > 1) Find the GO terms associated with subsets of my genes? (I realise I
> > can use merge() to link my array data to the LocusLink ids, but what
> do
> > I do then?)
> >
> > 2) Fins out if a particular GO term is statistically over-represented
> in
> > a particular group
> 
> Hi, Mick.
> 
> I would take your locuslink IDs for your genes and dump out two lists to
> a
> text file:
> 
> 1)  All LocusIDs on your array.
> 2)  All LoucsIDs in your genelist.
> 
> Then use an external program or web tool such as DAVID/EASE to do the
> analysis.
> 
> That said, there was some discussion on using straight locusIDs (rather
> than
> requiring a metadata package) in GOHyperG.  I don't know where that
> conversion stands.
> 
> As to your question about linking genes to GO, that is actually done at
> the
> transcript/protein level.  Merging to entrez gene (locuslink) happens
> after
> the fact.  Using various data sources, you can link by refseq,
> locuslink,
> ensembl ids, ucsc knowngenes, human invitational ids (human), and
> probably
> several others in species other than human.
> 
> Sean
> 
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