Hi, I'm looking for opinions on using RMA and GCRMA normalisations when there are a large amount of changes in expression between treatments. I remember a comment on this list about this subject being largely ignored so far, but don't remember a more full discussion. Basically we are going to look at different genotypes, treated and untreated, with three biological replicates. An initial comparison comparing 9 genotypes treated versus untreated (no reps yet, just 9 affy chips treated versus 9 untreated chips) by GCRMA, followed simply by a paired t-test with multtest "BH" multiple testing correction we see 3000 genes (out of 22000) with p<0.01, and 6000 with p<0.05. Approx 1500 of the p<0.01 have a fold change >2. I've also seen similar amounts of changes for other experiments such as day versus night comparisons. This means that the 'majority of genes not changing' criteria is probably not being met. However, the number and identity of the changes are biologically meaningful and so is it justified to continue to use these methods, particulary in the absence of anything better. So what do people think/do, surely lots of people are seeing similar amounts of changes, so how is it being addressed? Thanks Matt