Re-investigating the correctness of decoy-based false discovery rate control in proteomics tandem mass spectrometry

Abstract

Traditional database search methods for the analysis of bottom-up proteomics tandem mass spectrometry (MS/MS) data are limited in their ability to detect peptides with post-translational modifications (PTMs). Recently, "open modification" database search strategies, in which the requirement that the mass of the database peptide closely matches the observed precursor mass is relaxed, have become popular as a way to find a wider variety of types of PTMs. Indeed, in one study, Kong et al. reported that the open modification search tool MSFragger can achieve higher statistical power to detect peptides than a traditional "narrow window" database search. At the same time, Kong et al. reported that their empirical results suggest a problem with false discovery (FDR) control in the narrow window setting. We investigated these claims empirically and, in the process, uncovered a potential problem with FDR control in the machine learning post-processors Percolator and PeptideProphet. However, we also found that, after accounting for chimeric spectra as well as for the inherent difference in the number of candidates in open and narrow searches, the data does not provide sufficient evidence that FDR control in proteomics MS/MS database search is problematic.