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Quantifying Specificity of GO Terms

Stan Dong qdong at genome.Stanford.EDU
Wed Apr 18 10:01:25 PDT 2007


Another tool is the GO-TermFinder by Gavin Sherlock. I believe there  
is interest for Amigo to incorporate this tool.

     http://search.cpan.org/dist/GO-TermFinder/

SGD has been using it with great satisfaction from our users. You may  
check the SGD page to get some sense of a use case.

     http://db.yeastgenome.org/cgi-bin/GO/goTermFinder

-Stan

On Apr 17, 2007, at 9:36 PM, Paul Shannon wrote:

> The Bioconductor project has, I believe, a fine solution to this  
> problem -- though
> please forgive me if I have misconstrued things.   The relevant  
> packages (see
> below) use the Hypergeometric distribution to calculate a p-value  
> for the
> enrichment of any GO node for the genes in question.  I typically  
> map proteins
> to GeneID's as the first step in my analysis.
>
> If this sounds like it addresses your problem, you may wish to take  
> a look at
>
>    http://bioconductor.org/packages/1.9/bioc/html/GOstats.html   and
>    http://bioconductor.org/packages/1.9/bioc/html/Category.html
>
> Each of these web pages contains a 'vignette' in a pdf file which  
> makes for
> a good introduction to the methods.
>
> Though orginally conceived in the context of microarrays, I use  
> these packages
> quite fruitfully with proteomics data.
>
>  - Paul
>
>
>>> I am working on a project that involves curation of protein data  
>>> that
>>> includes GO terms, and it would be very helpful if I had some
>>> numerical quantification of the specificity of each term.  It is
>>> possible to manually examine each term to determine this  
>>> specificity,
>>> but because there is a large amount of data, I would like to  
>>> automate
>>> the process.  I understand that there is no reliable way to do this
>>> simply using the level in the DAG hierarchy, but I am wondering  
>>> if any
>>> of you might have a work-around.
>
> --
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