Dear mailing list,
I try to get a final solution to the following problem: I have two color
microarray data (common reference, dye-swap, multi-factor, multi-group) of
which I want to extract differentially expressed genes (DEGs) using LIMMA.
Those DEGs I want to analyse for the over-representation of GO-Terms using
GOstats.
I got as far as a list with GO-Terms and their respective P-values and even
could construct a nice direct-acyclic graph out of this data.

*However, the output I get does not account for the following:
Are single genes/transcripts up- or down-regulated?
What about the up- and down-regulation of whole over-represented GO-Terms?
*
*Could I get there using clustering approaches?
*

I'm sure somebody on the list has already tried such an approach, *finally
yielding over-represented GO-Terms, which are either up- or down-regulated.*

Thanks in advance,
Andreas

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