Recent multiple testing (see also Multiple comparisons) applications have benefited from the introduction of methodologies based on the false discovery rate (FDR), which has been defined in a seminal paper [1] as the expected value of the ratio of wrongly rejected null hypotheses (false discoveries) over the total rejected null hypotheses (discoveries). Procedures based on the FDR have been increasing in popularity since they offer a more powerful approach than traditional multiple comparison methods [2] in many applications, especially when the number of tests is very high.