[BioC] Differential expression

[Robert Gentleman]

Hi,
  It depends entirely on the biology of the experiment and you have said 
nothing about that. For most experiments, the experimentor knows, a 
priori, that only a small number of genes are likely to change (in the 
low hundreds). If you did an experiment where you anticipate lots of 
genes changing expression values, then as has already been pointed out, 
the assumptions of most normalization methods are not met. What to do in 
that case is up to you and would require consultation with a local 
expert, IMHO.

  best wishes
   Robert


E Motakis, Mathematics wrote:
> Dear all,
> 
> I am working on two colours microarray experiments and, from a set of 42000 
> genes, I would like to identify the differentially expressed ones. I have 
> read several articles on this issue and most of them imply that the number 
> of differential expressed genes in such experiments should be a small 
> number (compared to the whole set).
> 
> Could anyone tell me why this is correct? What if I find half of the genes 
> to be differentially expressed according to the t-test p-value?
> 
> I am not discussing the issue of p-values and q-values yet. I am asking 
> only about why most of the papers imply a low number of differentially 
> expressed genes.
> 
> Thank you,
> Makis
> 
> 
> ----------------------
> E Motakis, Mathematics
> E.Motakis at bristol.ac.uk
> 
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-- 
Robert Gentleman, PhD
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M2-B876
PO Box 19024
Seattle, Washington 98109-1024
206-667-7700
rgentlem at fhcrc.org