When testing many hypotheses at once, the chance of mistakenly rejecting true ones increases. To address this, different methods have been developed to improve the accuracy of multiple testing. This study compared various statistical methods using gene expression data and found that some methods were more effective at identifying significant genes than others. The researchers looked at different error rates and test statistics to determine which approach worked best for analyzing genetic data.