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Quantifying Specificity of GO Terms

Paul Shannon pshannon at systemsbiology.org
Tue Apr 17 21:36:23 PDT 2007


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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