For microarray data, differential expression analysis is done for each probeset. The problem is that one gene is typically mapped to multiple probesets. Since for most if not all practical reasons, we are interested in differential expression at the gene but not probeset level, I am wondering what's the best way to map probeset analysis into gene analysis. For instance, there are multiple probesets for a gene and each probeset has a p-value, fold-change, etc. When we map the probelets into the corresponding gene, shall we take the probeset with the smallest p-value and use its statistics for the gene? Or median p-value? Mean? ...?
Thanks in advance!