In high dimensional studies, controlling the false discovery rate (FDR) has become an important issue where the multiplicity is a problem. Traditionally, familywise error rate (FWER) is used to control the overall type I error rate in the application of multiple comparisons. However, when many of null hypotheses are false, FWER tendsto be more conservative and has less power. To improve the drawbacks of FWER, an innovative approach based on FDR can be used. The purpose of this article is to compare the performance of current step-up and step-down procedures and detect the merits and flaws of these procedures. In addition, the comparison of those procedures is illustrated by an example.