[BioC] multiple testing with 54000 genes

[James W. MacDonald]

Dipl.-Ing. Johannes Rainer wrote:
> hi,
> 
> i wanted to ask if someone has experience in multiple testing with a 
> large number of genes.
> 
> i have in total 24 Affymetrix chips (hgu133plus2), 12 patients, for 
> every patient an 0 hours and 6 hours after treatment sample. i 
> calculated p values using permutation (mt.maxT function with 
> test="pairt") and corrected for multiple testing using the Benjamini 
> Hochberg method. the problem is, that with that large number of tests 
> (54675 genes and therefore 54675 tests) after adjusting the p values no 
> gene shows a "significant" difference.
> 
> i will now reduce the number of genes to test to get to some results.
> has anyone experienced similar problems?

You probably don't have enough samples to use a permuted null 
distribution. I believe the smallest p-value you can get with a permuted 
null is going to be ~0.00024, which may not be small enough to survive a 
multiplicity correction with that many genes. I would imagine you would 
get better results if you used a parametric null (e.g., using the limma 
package).


Best,

Jim


> 
> thanks, jo
> 
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-- 
James W. MacDonald
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623