[BioC] cross experiments or geo series normalization
Robert Gentleman
rgentlem at fhcrc.org
Thu Jun 30 15:07:17 CEST 2005
Hi Chuming,
If what you are asking about is the joint normalization of multiple
different experiments then I think the answer is that it is probably not
a good idea. You will almost surely need some sort of random effects
model to address between experiment differences regardless of whether
the joint normalization "works", and you can use that on experiments
normalized separately. I am aware of no study that compares joint versus
separate normalization, but I doubt that it would be of much real value,
even if done. There are examples where joint normalization of highly
related experiments (same people, similar biological material and
similar processing) that do not remove all experimental artifacts, and
hnece it is unlikely that this procedure would have better results on
unrelated experiments.
Random effects models have provided the basis for such analyses for
some years now. Cox and Solomon, Components of Variance, have a pretty
good discussion of the issues involved and include explicit discussion
of microarray experiments.
Robert
Chuming Chen wrote:
> Hi, all,
>
> Has anybody done cross experiments or GEO series normalization on
> Affymetrix arrays? Any suggestions or related links will be highly
> appreciated.
>
> Thanks,
>
> Chuming Chen
>
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