

   (My apologies if this is not the proper place for introducing a
non-R-based tool)

   Rainer.

   We developed a very simple tool for grouping genes in base on their
annotations, that can be useful for you. You just need a list of gene
names and their functional annotations (sentences in free text or
keywords of any type). Just paste the data as text-tabulated text in
the area.

   The system compares the annotations and puts together those genes
with similar words. It is independent on any external database.

   If your table contains logRatio measures for one or several
microarray experiments, they will appear in the results as colored
boxes (see example2 in the main page).

   Even if this tool will not fully solve your question, It is a
extremely simple text-mining tool that helps the users finding
functionally related genes on a list. It is up to the user to extract
conclusions from the results.

   The system is called "Researcher's Digest":

   http://bioinfogp.cnb.csic.es/tools/digest

   I hope that helps.

   best,

   Juan Carlos Oliveros,Ph.D

   CNB-CSIC, Spain

   Quoting Rainer Tischler <rainer_t62@yahoo.de>:

> Dear all,
>
> I have a script that generates a large number of gene sets
(vectors 
> of gene names) and would like to apply a functional analysis (e.g. 

> how many transcription factors occur in each gene set? how many   
> kinases... etc.). I can convert the gene names into different   
> formats using biomaRt, however, the only functional analysis tools
I 
> have found in R apply an enrichment analysis on either GO or KEGG   
> gene sets. Is there a package that allows me to answer more simple 

> questions, e.g. just counting the number of transcription factors
in 
> a gene set by connecting to a public database?
>
> Many thanks,
> Rainer
>
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