FastLSU: a more practical approach for the Benjamini-Hochberg FDR controlling procedure for huge-scale testing problems

Vered Madar, Sandra Batista

Abstract: We address a common problem in large-scale data analysis, and especially the field of genetics, the huge-scale testing problem, where millions to billions of hypotheses are tested together creating a computational challenge to control the inflation of the false discovery rate. As a solution we propose an alternative algorithm for the famous Linear Step Up procedure of Benjamini and Hochberg.