[BioC] Differential expression

[Kimpel, Mark William]

Makis,

I am speaking as a biologist, not as a statistician. Under conditions of
most biologic experiments, the assumption is that cells need to continue
mundane "housekeeping" functions and that these are minimally effected
by the differential conditions of the experiment. In my area, which is
neuroscience, we hope to see differential expression of genes involved
with neurotransmission or synaptic plasticity, but do not expect to see
differential expression of genes involved in just keeping neurons and
support cells alive and intact. It turns out that most genes are
involved in the latter, not the former, processes. We occasionally see
examples on this list, however, where very drastic experimental
conditions, such as one might see in toxicology, lead to differential
expression of a larger percentage of genes.

It is important, then, to put your experiment into biologic context to
consider whether your current findings make sense and how best to
proceed with normalization and analysis. For instance, normalization
techniques that make sense when only a small percentage of genes are
differentially expressed may not be appropriate when a much large
percentage of genes are differentially expressed (and I'll let the
statisticians on this list address what those procedures are and how to
decide which to use when).

If you would, you might describe for the list the context of your
experiment so that others might know how best to advise you to proceed.

Mark

Mark W. Kimpel MD 

Indiana University School of Medicine

.ch] On Behalf Of E Motakis, Mathematics
Sent: Friday, May 26, 2006 11:07 AM
To: Bioconductor
Subject: [BioC] Differential expression

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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