The classical BH, conformal, and competition testing procedures are shown to be special cases of a generalized Randomized BH framework that relaxes exchangeability and enables integration of distributed tests.
A theoretical foundation of the target-decoy search strategy for false discovery rate control in proteomics
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abstract
Motivation: Target-decoy search (TDS) is currently the most popular strategy for estimating and controlling the false discovery rate (FDR) of peptide identifications in mass spectrometry-based shotgun proteomics. While this strategy is very useful in practice and has been intensively studied empirically, its theoretical foundation has not yet been well established. Result: In this work, we systematically analyze the TDS strategy in a rigorous statistical sense. We prove that the commonly used concatenated TDS provides a conservative estimate of the FDR for any given score threshold, but it cannot rigorously control the FDR. We prove that with a slight modification to the commonly used formula for FDR estimation, the peptide-level FDR can be rigorously controlled based on the concatenated TDS. We show that the spectrum-level FDR control is difficult. We verify the theoretical conclusions with real mass spectrometry data.
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2026 1verdicts
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The Randomized BH Procedure: A Generalized Framework Encompassing Conformal and Competition Tests
The classical BH, conformal, and competition testing procedures are shown to be special cases of a generalized Randomized BH framework that relaxes exchangeability and enables integration of distributed tests.