Title: Controlling the false discovery rate for discrete data: New results and computational tools
Authors: Sebastian Doehler - Darmstadt University of Applied Science (Germany) [presenting]
Etienne Roquain - University Pierre et Marie Curie (France)
Guillermo Durand - Universite Pierre et Marie Curie (France)
Abstract: The Benjamini-Hochberg procedure and related methods are classical methods for controlling the false discovery rate for multiple testing problems. These procedures were originally designed for continuous test statistics. However, in many applications, the test statistics are discretely distributed. While it is well known that e.g. the Benjamini-Hochberg procedure still controls the false discovery rate in the discrete paradigm, it may be unnecessarily conservative. Thus, developing more powerful FDR procedures for discrete data is interesting. We present improved procedures that incorporate the discreteness of the p-value distributions and introduce an R package which implements these approaches.