Literature DB >> 29281288

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

Zheng Zhang1, Meghan Burke1, Yuri A Mirokhin1, Dmitrii V Tchekhovskoi1, Sanford P Markey1, Wen Yu2, Raghothama Chaerkady3, Sonja Hess3, Stephen E Stein1.   

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. While decoy methods for SLS have been developed for low mass accuracy peptide spectral libraries, it is not clear that they are optimal or directly applicable to high mass accuracy spectra. Therefore, we report the development and validation of methods for high mass accuracy decoy libraries. Two types of decoy libraries were found to be suitable for this purpose. The first, referred to as Reverse, constructs spectra by reversing a library's peptide sequences except for the C-terminal residue. The second, termed Random, randomly replaces all non-C-terminal residues and either retains the original C-terminal residue or replaces it based on the amino-acid frequency of the library's C-terminus. 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 (Zolg, D. P.; et al. Nat. Methods 2017, 14, 259-262). 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 postprocessing approaches such as Percolator. An application of these methods for FDR estimation for the recently reported "hybrid" library search (Burke, M. C.; et al. J. Proteome Res. 2017, 16, 1924-1935) 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.

Entities:  

Keywords:  PeptideProphet algorithm; false discovery rate; peptide mass spectral library; target-decoy approach

Mesh:

Substances:

Year:  2018        PMID: 29281288     DOI: 10.1021/acs.jproteome.7b00614

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  4 in total

Review 1.  Expanding the Use of Spectral Libraries in Proteomics.

Authors:  Eric W Deutsch; Yasset Perez-Riverol; Robert J Chalkley; Mathias Wilhelm; Stephen Tate; Timo Sachsenberg; Mathias Walzer; Lukas Käll; Bernard Delanghe; Sebastian Böcker; Emma L Schymanski; Paul Wilmes; Viktoria Dorfer; Bernhard Kuster; Pieter-Jan Volders; Nico Jehmlich; Johannes P C Vissers; Dennis W Wolan; Ana Y Wang; Luis Mendoza; Jim Shofstahl; Andrew W Dowsey; Johannes Griss; Reza M Salek; Steffen Neumann; Pierre-Alain Binz; Henry Lam; Juan Antonio Vizcaíno; Nuno Bandeira; Hannes Röst
Journal:  J Proteome Res       Date:  2018-10-11       Impact factor: 4.466

Review 2.  Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases.

Authors:  Hayoung Lee; Seung Il Kim
Journal:  Int J Mol Sci       Date:  2022-02-16       Impact factor: 5.923

3.  Sensitive Method for the Confident Identification of Genetically Variant Peptides in Human Hair Keratin.

Authors:  Zheng Zhang; Meghan C Burke; William E Wallace; Yuxue Liang; Sergey L Sheetlin; Yuri A Mirokhin; Dmitrii V Tchekhovskoi; Stephen E Stein
Journal:  J Forensic Sci       Date:  2019-10-31       Impact factor: 1.832

Review 4.  Proteome Discoverer-A Community Enhanced Data Processing Suite for Protein Informatics.

Authors:  Benjamin C Orsburn
Journal:  Proteomes       Date:  2021-03-23
  4 in total

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