In shotgun proteomics, one of the major steps necessary for reliable peptide identification is false discovery rate (FDR) estimation, which, ideally, allows preservation of a pre-specified fraction of false positive peptide identifications in the set of those deemed correct. Currently used statistical validation tools for FDR control are dominated by heavily data-dependent approaches with restrictive or empirical, and therefore lacking any theoretical grounding, assumptions and settings which often lead to generation of inaccurate FDR estimates. In this study, a new approach to FDR estimation using the concept of fixed empirical null score distribution based on a single-spectrum statistical confidence measure (E-value), called Common Decoy Distribution (CDD) is proposed.

Separat...[ Read more ]

In shotgun proteomics, one of the major steps necessary for reliable peptide identification is false discovery rate (FDR) estimation, which, ideally, allows preservation of a pre-specified fraction of false positive peptide identifications in the set of those deemed correct. Currently used statistical validation tools for FDR control are dominated by heavily data-dependent approaches with restrictive or empirical, and therefore lacking any theoretical grounding, assumptions and settings which often lead to generation of inaccurate FDR estimates. In this study, a new approach to FDR estimation using the concept of fixed empirical null score distribution based on a single-spectrum statistical confidence measure (E-value), called Common Decoy Distribution (CDD) is proposed.

Separate CDDs constructed for spectra of different charge states were shown to be negligibly sensitive to changes in noise levels and the presence of unexpected post-translational modifications (PTMs) in the analyzed spectra. Optimized implementation of CDD idea in PeptideProphet framework (PP-CDD) allowed calculation of satisfactorily accurate and precise FDR estimates for different sets of validation files, with the performance being on par with that of PeptideProphet variants studied, and much better than Percolator’s. Noticeable sensitivity of the precision of FDR estimation by PP-CDD towards precursor mass tolerance setting applied at the sequence database search stage indicates that accurate determination of E-values for all analyzed peptide-spectrum matches is of paramount importance for the optimal performance of a CDD-based tool for FDR control.