[BioC] adjusted p-values for large number of genes...

[James W. MacDonald]

Lourdes Peña Castillo wrote:
> Hello,
> 
> I am using  limma to select differentially expressed genes. I have 24
> arrays and 40k genes. According to the limma users' guide, "If none of
> the raw p-value are less than 1/G, where G is the number of genes,
> then all of the adjusted p-values will be
> equal to 1". 
> 
> I get raw p-values which are less than 1/G after applying eBayes;
> however, the lowest adjusted p-value I get using "fdr"  is 0.66. Does
> that mean that I cannot adjust for multiple testing in experiments
> involving  many genes?   Should I then use an arbitrary cut-off on the
> raw p-values? or what are the alternatives?

The problem here is that you don't have any evidence for differential 
expression (which is *not* the same as saying there are no differences). 
With 24 arrays this is sort of hard to believe, unless you have say, 12 
samples and only duplicates for each. Regardless, you do have options.

First, you can filter the genes prior to doing the statistics to reduce 
the number of comparisons you are doing. See the genefilter package for 
various methods of doing this.

Second, if you have an a priori idea of the 'type' of genes that you 
expect to be differentially expressed, you can do the statistical 
analysis using only those genes. This sort of analysis is a bit more 
difficult to do than the agnostic filtering done by genefilter - you may 
need to extract those genes that have a certain gene ontology term 
associated with them. This may take some work, but is quite doable.

Third, even if you don't do one of the above, limma does return genes 
ranked in likely order of importance. You could simply take the top n 
genes (where n is dictated by the time and resources you are willing to 
expend) and try to validate them using qPCR or Northerns, etc. Note that 
you should use new samples if you want to generalize the results to a 
population other than the existing samples.

Best,

Jim



> 
> Thanks!
> 
> Lourdes
> 
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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