Literature DB >> 23720762

Combining results of multiple search engines in proteomics.

David Shteynberg1, Alexey I Nesvizhskii, Robert L Moritz, Eric W Deutsch.   

Abstract

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

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Year:  2013        PMID: 23720762      PMCID: PMC3769318          DOI: 10.1074/mcp.R113.027797

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  43 in total

1.  Implementation and uses of automated de novo peptide sequencing by tandem mass spectrometry.

Authors:  J A Taylor; R S Johnson
Journal:  Anal Chem       Date:  2001-06-01       Impact factor: 6.986

2.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

3.  Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets.

Authors:  Kang Ning; Damian Fermin; Alexey I Nesvizhskii
Journal:  Proteomics       Date:  2010-07       Impact factor: 3.984

4.  Open mass spectrometry search algorithm.

Authors:  Lewis Y Geer; Sanford P Markey; Jeffrey A Kowalak; Lukas Wagner; Ming Xu; Dawn M Maynard; Xiaoyu Yang; Wenyao Shi; Stephen H Bryant
Journal:  J Proteome Res       Date:  2004 Sep-Oct       Impact factor: 4.466

5.  The generating function of CID, ETD, and CID/ETD pairs of tandem mass spectra: applications to database search.

Authors:  Sangtae Kim; Nikolai Mischerikow; Nuno Bandeira; J Daniel Navarro; Louis Wich; Shabaz Mohammed; Albert J R Heck; Pavel A Pevzner
Journal:  Mol Cell Proteomics       Date:  2010-09-09       Impact factor: 5.911

6.  PepNovo: de novo peptide sequencing via probabilistic network modeling.

Authors:  Ari Frank; Pavel Pevzner
Journal:  Anal Chem       Date:  2005-02-15       Impact factor: 6.986

7.  Development and validation of a spectral library searching method for peptide identification from MS/MS.

Authors:  Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Nichole King; Stephen E Stein; Ruedi Aebersold
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

8.  FDRAnalysis: a tool for the integrated analysis of tandem mass spectrometry identification results from multiple search engines.

Authors:  David C Wedge; Ritesh Krishna; Paul Blackhurst; Jennifer A Siepen; Andrew R Jones; Simon J Hubbard
Journal:  J Proteome Res       Date:  2011-02-21       Impact factor: 4.466

Review 9.  A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.

Authors:  Alexey I Nesvizhskii
Journal:  J Proteomics       Date:  2010-09-08       Impact factor: 4.044

10.  The mzIdentML data standard for mass spectrometry-based proteomics results.

Authors:  Andrew R Jones; Martin Eisenacher; Gerhard Mayer; Oliver Kohlbacher; Jennifer Siepen; Simon J Hubbard; Julian N Selley; Brian C Searle; James Shofstahl; Sean L Seymour; Randall Julian; Pierre-Alain Binz; Eric W Deutsch; Henning Hermjakob; Florian Reisinger; Johannes Griss; Juan Antonio Vizcaíno; Matthew Chambers; Angel Pizarro; David Creasy
Journal:  Mol Cell Proteomics       Date:  2012-02-27       Impact factor: 5.911

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  60 in total

1.  A Scalable Approach for Protein False Discovery Rate Estimation in Large Proteomic Data Sets.

Authors:  Mikhail M Savitski; Mathias Wilhelm; Hannes Hahne; Bernhard Kuster; Marcus Bantscheff
Journal:  Mol Cell Proteomics       Date:  2015-05-17       Impact factor: 5.911

2.  PeptideShaker enables reanalysis of MS-derived proteomics data sets.

Authors:  Marc Vaudel; Julia M Burkhart; René P Zahedi; Eystein Oveland; Frode S Berven; Albert Sickmann; Lennart Martens; Harald Barsnes
Journal:  Nat Biotechnol       Date:  2015-01       Impact factor: 54.908

Review 3.  Quantitative proteomic analysis of histone modifications.

Authors:  He Huang; Shu Lin; Benjamin A Garcia; Yingming Zhao
Journal:  Chem Rev       Date:  2015-02-17       Impact factor: 60.622

4.  Building high-quality assay libraries for targeted analysis of SWATH MS data.

Authors:  Olga T Schubert; Ludovic C Gillet; Ben C Collins; Pedro Navarro; George Rosenberger; Witold E Wolski; Henry Lam; Dario Amodei; Parag Mallick; Brendan MacLean; Ruedi Aebersold
Journal:  Nat Protoc       Date:  2015-02-12       Impact factor: 13.491

5.  Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data.

Authors:  Karin Schork; Katharina Podwojski; Michael Turewicz; Christian Stephan; Martin Eisenacher
Journal:  Methods Mol Biol       Date:  2021

6.  Analyzing trapped protein complexes by Virotrap and SFINX.

Authors:  Kevin Titeca; Emmy Van Quickelberghe; Noortje Samyn; Delphine De Sutter; Annick Verhee; Kris Gevaert; Jan Tavernier; Sven Eyckerman
Journal:  Nat Protoc       Date:  2017-03-30       Impact factor: 13.491

7.  JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy.

Authors:  Xusheng Wang; Yuxin Li; Zhiping Wu; Hong Wang; Haiyan Tan; Junmin Peng
Journal:  Mol Cell Proteomics       Date:  2014-09-08       Impact factor: 5.911

8.  Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data.

Authors:  Chengjian Tu; Quanhu Sheng; Jun Li; Danjun Ma; Xiaomeng Shen; Xue Wang; Yu Shyr; Zhengping Yi; Jun Qu
Journal:  J Proteome Res       Date:  2015-09-30       Impact factor: 4.466

9.  Tiered Human Integrated Sequence Search Databases for Shotgun Proteomics.

Authors:  Eric W Deutsch; Zhi Sun; David S Campbell; Pierre-Alain Binz; Terry Farrah; David Shteynberg; Luis Mendoza; Gilbert S Omenn; Robert L Moritz
Journal:  J Proteome Res       Date:  2016-09-12       Impact factor: 4.466

10.  The 5300-year-old Helicobacter pylori genome of the Iceman.

Authors:  Frank Maixner; Ben Krause-Kyora; Dmitrij Turaev; Alexander Herbig; Michael R Hoopmann; Janice L Hallows; Ulrike Kusebauch; Eduard Egarter Vigl; Peter Malfertheiner; Francis Megraud; Niall O'Sullivan; Giovanna Cipollini; Valentina Coia; Marco Samadelli; Lars Engstrand; Bodo Linz; Robert L Moritz; Rudolf Grimm; Johannes Krause; Almut Nebel; Yoshan Moodley; Thomas Rattei; Albert Zink
Journal:  Science       Date:  2016-01-08       Impact factor: 47.728

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