Affymetrix GeneChips® are routinely used to measure relative amounts of mRNA transcripts on a genome wide basis. The large number of probe sets (representing genes) available on these arrays gives the researcher a wealth of information, but the multiple testing raises the potential for a large number of false positives. False positives and false negatives can both pose problems for the researcher, each with its own cost, so the balance between the two should be evaluated based upon the goals of the experiment. Increasing the stringency for accepting differences as significant (decreasing p-value) reduces false positives, which is important if verification and follow-up are costly, but simultaneously reduces true positives and may lead investigators to miss important trends in the data. Measurements of false positive risk, such as false discovery rate (FDR) [1,2], are now commonly used to help guide decisions. Although FDR gives the investigator an estimate of how many false positives to expect, it does nothing to identify which results are false positives.
