Competition-based control of the false discovery proportion
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Target-decoy competition (TDC) is commonly used in the computational mass spectrometry community for false discovery rate (FDR) control (6). Recently, TDC's underlying approach of competition-based FDR control has gained significant popularity in other fields after Barber and Candes laid its theoretical foundation in a more general setting (1). 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 al level α, the FDP in our list of discoveries can significantly exceed α. We offer two new procedures to address this problem. TDC-SD rigorously controls the FDP in the competition setup by guaranteeing that the FDP is bounded by α at any desired confidence level. The complementary TDC-UB is designed to bound the FDP for any list of top scoring target discoveries. For example, TDC-UB can give a 95 for controlling the FDR. We demonstrate the utility of these procedures using synthetic and real data in multiple domains.
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