gammaMAXT: a fast multiple-testing correction algorithm

The purpose of the maxT algorithm (1993) is to control the family-wise error rate (FWER) when assessing significance of multiple tests jointly. However, the requirements in terms of computing time and memory of this procedure are proportional to the number of investigated hypothesis. The memory issue has been solved by Van Lishout’s implementation of maxT (2013), which makes the memory usage independent from the size of the dataset. This algorithm is implemented in MBMDR-3.0.3, a software that is able to identify genetic interactions, for a variety of SNP-SNP based epistasis model,s in an effective way. However, that implementation turned out to be less suitable for genome-wide interaction analysis studies, due to the prohibitive computational burden. Here, we present gammaMAXT, a novel algorithm which is part of MBMDR-4.2.2. We show that, in the abscence of interaction effects, test-statistics produced by the MB-MDR methodology follow a mixture distribution with a point mass at zero and a shifted gamma distribution for the top 10% of the strictly positive values. We show that the gammaMAXT algorithm has a power comparable to maxT and maintains FWER, but requires less computational resources and time. MBMDR-4.2.2 can be downloaded at http://www.statgen.ulg.ac.be.