[BioC] Re: GoHyperG

[Nicholas Lewin-Koh]

Hi Sean,
In this situation I would hope it is a one sided test. I had this
same discussion with a colleague who wanted the same thing. I don't
think testing for under-representation means anything. Think about
the context, one is doing recursive sampling of a finite of a finite
population for which there are two sources of bias, what is represented
in the database or on the chip, and what is annotated on the chip. 
Further you are testing at each node the discrepency from random,
as you go down the DAG zero becomes more and more probable, you can
think
of it as doing a mark-recapture study on your genes. This problem is
exacerbated
by the sampling bias. Finally, a last complication is that test is
further biased by your ability to detect differentially expressed genes. 
At least if you detect over-representation you can argue for a strong
signal.


Nicholas


> 
> Message: 4
> Date: Wed, 22 Dec 2004 11:02:55 -0500
> From: Sean Davis <sdavis2 at mail.nih.gov>
> Subject: [BioC] GoHyperG
> To: Bioconductor <bioconductor at stat.math.ethz.ch>
> Message-ID: <F0EE8E4B-5432-11D9-ACCB-000D933565E8 at mail.nih.gov>
> Content-Type: text/plain; charset=US-ASCII; format=flowed
> 
> Just a quick question--are the p-values from gohyperg one- or 
> two-sided?  I have a collaborator who would like to use it to determine 
> underrepresented ontology categories.
> 
> Thanks,
> Sean
> 
> 
>