Recently, genome-wide association studies (GWAS), which typically test disease associations with half to a few million single nucleotide polymorphisms (SNPs) across the human genome in hundreds to thousands of samples, have successfully identified many genetic variants contributing to the susceptibilities of complex diseases. However, the variants identified so far, individually or in combination, account for only a small proportion of the inherited component of disease risk [1]. A possible explanation is that due to the large number of genetic polymorphisms examined in GWAS and the massive amount of tests conducted, real but weak associations are likely to be missed after multiple comparison adjustment (e.g., corrected by half a million tests in a typical GWAS).
