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Reverse and Random Decoy Methods for False Discovery Rate Estimation in High Mass Accuracy Peptide Spectral Library Searches

Published

Author(s)

Zheng Zhang, Meghan C. Burke, Yuri A. Mirokhin, Dmitrii V. Tchekhovskoi, Sanford P. Markey, Wen Yu, Raghothama Chaerkady, Sonja Hess, Stephen E. Stein

Abstract

Spectral library searching (SLS) is an attractive alternative to sequence database searching (SDS) for peptide identification due to its speed, sensitivity, and ability to include any selected mass spectra. However, SLS does not have a widely tested and accepted target-decoy process for calculating false discovery rates (FDR) as does SDS. The present study reports the development and testing of decoy library methods for FDR estimation in SLS. Two types of decoy library methods were found suitable for high resolution, high mass accuracy peptide SLS, referred to as Reverse and Random methods. In both cases the m/z values of fragment ions are shifted accordingly. Determination of FDR is performed in a manner equivalent to SDS, concatenating a library with its decoy prior to a search. The utility of Reverse and Random libraries for target-decoy SLS in estimating false positives and FDRs was demonstrated using spectra derived from a recently published synthetic human proteome project. For data sets from two large-scale label-free and iTRAQ experiments, these decoy building methods yielded highly similar score thresholds and spectral identifications at 1% FDR. The results were also found to be equivalent to those of using the decoy-free PeptideProphet algorithm. Using these new methods for FDR estimation, MSPepSearch, which is freely available search software, led to 18% more identifications at 1% FDR and 23% more at 0.1% FDR when compared with other widely-used SDS engines coupled to post-processing approaches such as Percolator. An application of these methods for FDR estimation for the recently reported hybrid library search method is also made. The application of decoy methods for high mass accuracy SLS permits the merging of these results with those of SDS, thereby increasing the assignment of more peptides, leading to deeper proteome coverage.
Citation
Journal of Proteome Research
Volume
17
Issue
2

Keywords

peptide mass spectral library, target-decoy approach, PeptideProphet algorithm, false discovery rate

Citation

Zhang, Z. , Burke, M. , Mirokhin, Y. , Tchekhovskoi, D. , Markey, S. , Yu, W. , Chaerkady, R. , Hess, S. and Stein, S. (2018), Reverse and Random Decoy Methods for False Discovery Rate Estimation in High Mass Accuracy Peptide Spectral Library Searches, Journal of Proteome Research, [online], https://doi.org/10.1021/acs.jproteome.7b00614 (Accessed July 25, 2024)

Issues

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Created February 2, 2018, Updated February 13, 2020