Hello Srini,

It sounds as if you are attempting to establish a prior probability and
compare it to the posterior probability -- a perfect candidate for bayesian
analysis. I would simply do a search for 'bayesian analysis of gene
expression data'  -- there are a number of statistical packages that are
available.  A number of R packages are available as well as a software
package from Yale: http://www.yale.edu/townsend/Software/BAGELTutorial.html

Hope this helps,

James


On Thu, Jan 31, 2013 at 11:11 PM, Srinivas Iyyer
<srini_iyyer_bio@yahoo.com>wrote:

> Hi:
> Apologies for asking the following question. As this may sound very basic
> and stupid for this forum , I honestly do not know how to solve it and I do
> not have a teacher who can help me understand.
>
> I have list of genes (200) that are involved in a particular process and I
> call this as a ProcSet.   From an independent experiment I found that out
> of 10,000 genes, 1500 are significant and I call these1500 genes as
> ResultSet.
>
> The intersection of ResultSet and ProcSet are 80 genes.
>
> That means 40% of ProcSet are significant.
>
>  How do I calculate that 40% is significant and more than I expect by
> chance given ResultSet and 10,000 genes I evaluated in the experiment.
>
> What I have:
> n = 200 (ProcSet)
> p = 0.4
>
> N = 1500  (ResultSet)
>
> N1 =10,000
>
> Pn = 0.15
>
> What kind of test will help me know that 0.4 is significant given 0.15.
> Any suggestions will greatly help me.
>
> Thank you.
> Srini
>
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>



-- 
*James C. Whanger*
*
*
*"It ain't what you don't know that gets you into trouble. It's what you
know for sure that just ain't so."  Mark Twain*

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