Literature DB >> 21692516

A statistical method for assessing peptide identification confidence in accurate mass and time tag proteomics.

Jeffrey R Stanley1, Joshua N Adkins, Gordon W Slysz, Matthew E Monroe, Samuel O Purvine, Yuliya V Karpievitch, Gordon A Anderson, Richard D Smith, Alan R Dabney.   

Abstract

Current algorithms for quantifying peptide identification confidence in the accurate mass and time (AMT) tag approach assume that the AMT tags themselves have been correctly identified. However, there is uncertainty in the identification of AMT tags, because this is based on matching LC-MS/MS fragmentation spectra to peptide sequences. In this paper, we incorporate confidence measures for the AMT tag identifications into the calculation of probabilities for correct matches to an AMT tag database, resulting in a more accurate overall measure of identification confidence for the AMT tag approach. The method is referenced as Statistical Tools for AMT Tag Confidence (STAC). STAC additionally provides a uniqueness probability (UP) to help distinguish between multiple matches to an AMT tag and a method to calculate an overall false discovery rate (FDR). STAC is freely available for download, as both a command line and a Windows graphical application.

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Year:  2011        PMID: 21692516      PMCID: PMC3212438          DOI: 10.1021/ac2009806

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  32 in total

1.  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

2.  A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases.

Authors:  Rovshan G Sadygov; John R Yates
Journal:  Anal Chem       Date:  2003-08-01       Impact factor: 6.986

3.  Proteome analyses using accurate mass and elution time peptide tags with capillary LC time-of-flight mass spectrometry.

Authors:  Eric F Strittmatter; P Lee Ferguson; Keqi Tang; Richard D Smith
Journal:  J Am Soc Mass Spectrom       Date:  2003-09       Impact factor: 3.109

4.  TANDEM: matching proteins with tandem mass spectra.

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Journal:  Bioinformatics       Date:  2004-02-19       Impact factor: 6.937

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6.  Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST.

Authors:  Daniel López-Ferrer; Salvador Martínez-Bartolomé; Margarita Villar; Mónica Campillos; Fernando Martín-Maroto; Jesús Vázquez
Journal:  Anal Chem       Date:  2004-12-01       Impact factor: 6.986

7.  Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry.

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8.  A hierarchical statistical model to assess the confidence of peptides and proteins inferred from tandem mass spectrometry.

Authors:  Changyu Shen; Zhiping Wang; Ganesh Shankar; Xiang Zhang; Lang Li
Journal:  Bioinformatics       Date:  2007-11-17       Impact factor: 6.937

9.  Spectral probabilities and generating functions of tandem mass spectra: a strike against decoy databases.

Authors:  Sangtae Kim; Nitin Gupta; Pavel A Pevzner
Journal:  J Proteome Res       Date:  2008-07-03       Impact factor: 4.466

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Journal:  Mol Cell Proteomics       Date:  2008-07-02       Impact factor: 5.911

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  26 in total

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Journal:  Analyst       Date:  2019-01-28       Impact factor: 4.616

2.  Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics.

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Journal:  J Proteome Res       Date:  2015-02-27       Impact factor: 4.466

6.  Short-Term Stable Isotope Probing of Proteins Reveals Taxa Incorporating Inorganic Carbon in a Hot Spring Microbial Mat.

Authors:  Laurey Steinke; Gordon W Slysz; Mary S Lipton; Christian Klatt; James J Moran; Margie F Romine; Jason M Wood; Gordon Anderson; Donald A Bryant; David M Ward
Journal:  Appl Environ Microbiol       Date:  2020-03-18       Impact factor: 4.792

7.  A multi-omic systems approach to elucidating Yersinia virulence mechanisms.

Authors:  Charles Ansong; Alexandra C Schrimpe-Rutledge; Hugh D Mitchell; Sadhana Chauhan; Marcus B Jones; Young-Mo Kim; Kathleen McAteer; Brooke L Deatherage Kaiser; Jennifer L Dubois; Heather M Brewer; Bryan C Frank; Jason E McDermott; Thomas O Metz; Scott N Peterson; Richard D Smith; Vladimir L Motin; Joshua N Adkins
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8.  Hepatic Cytochrome P450 Activity, Abundance, and Expression Throughout Human Development.

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Journal:  Drug Metab Dispos       Date:  2016-04-15       Impact factor: 3.922

9.  Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis.

Authors:  Paul D Piehowski; Vladislav A Petyuk; Daniel J Orton; Fang Xie; Ronald J Moore; Manuel Ramirez-Restrepo; Anzhelika Engel; Andrew P Lieberman; Roger L Albin; David G Camp; Richard D Smith; Amanda J Myers
Journal:  J Proteome Res       Date:  2013-04-10       Impact factor: 4.466

10.  Increasing Confidence of LC-MS Identifications by Utilizing Ion Mobility Spectrometry.

Authors:  Kevin L Crowell; Erin S Baker; Samuel H Payne; Yehia M Ibrahim; Matthew E Monroe; Gordon W Slysz; Brian L LaMarche; Vladislav A Petyuk; Paul D Piehowski; William F Danielson; Gordon A Anderson; Richard D Smith
Journal:  Int J Mass Spectrom       Date:  2013-11-15       Impact factor: 1.986

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