Bridging the False Discovery Gap.

Controlling the false discovery rate (FDR) among discoveries from a tandem mass spectrometry proteomics experiment using target decoy competition (TDC) controls only the proportion of false discoveries in an average sense. Thus, for any particular analysis, even with a valid FDR control procedure, the proportion of false discoveries (the FDP) may be higher than the specified FDR threshold. We demonstrate this phenomenon using real data and describe two recently developed methods that help bridge the gap between controlling the expected or average rate of false discoveries and the empirical rate (FDP). The FDP Stepdown method controls the FDP at any desired confidence level, and the TDC Uniform Band provides a confidence, or upper prediction bound, on the FDP in TDC's list of discoveries.

Competition-based control of the false discovery proportion.

Recently, Barber and Candès laid the theoretical foundation for a general framework for false discovery rate (FDR) control based on the notion of "knockoffs." A closely related FDR control methodology has long been employed in the analysis of mass spectrometry data, referred to there as "target-decoy competition" (TDC). However, any approach that aims to control the FDR, which is defined as the expected value of the false discovery proportion (FDP), suffers from a problem. Specifically, even when successfully controlling the FDR at level α, the FDP in the list of discoveries can significantly exceed α. We offer FDP-SD, a new procedure that rigorously controls the FDP in the knockoff/TDC competition setup by guaranteeing that the FDP is bounded by α at a desired confidence level. Compared with the recently published framework of Katsevich and Ramdas, FDP-SD generally delivers more power and often substantially so in simulated and real data.