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

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 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor >