But if common complex disorders/traits are highly polygenic (Chabris, Lee, Cesarini, Benjamin, & Laibson, 2015) with many variants of small effect, why would we restrict ourselves to consider as hits only the few most stringently selected variants? Why not relax the threshold and explore “suggestive” hits as well? Surely these are enriched for true signals. This is a seductive argument and we admit some level of sympathy. However, if the purpose of conducting a GWAS is to identify variants that are associated with a disease in order to conduct extremely expensive and time-consuming functional follow-up experiments to identify and understand biological mechanisms, then it is even more important to control the family-wise error rate, or the probability that at least one hit is a Type I error, and the convention since Fisher's time has been to control this rate at 1 in 20, or .05. This is what a Bonferroni correction of 5×10−8 does. A popular alternative to a Bonferroni correction is false discovery rate correction, which typically provides less stringent control of Type I errors in favor of controlling
