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A decoy-free approach to the identification of peptides

Giulia Gonnelli (UGent) , Michiel Stock (UGent) , Jan Verwaeren (UGent) , Davy Maddelein (UGent) , Bernard De Baets (UGent) , Lennart Martens (UGent) and Sven Degroeve (UGent)
(2015) JOURNAL OF PROTEOME RESEARCH. 14(4). p.1792-1798
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Bioinformatics: from nucleotids to networks (N2N)
Abstract
A growing number of proteogenomics and metaproteomics studies indicate potential limitations of the application of the decoy database paradigm used to separate correct peptide identifications from incorrect ones in traditional shotgun proteomics. We therefore propose a binary classifier called Nokoi that allows fast yet reliable decoy-free separation of correct from incorrect peptide-to-spectrum matches (PSMs). Nokoi was trained on a very large collection of heterogeneous data using ranks supplied by the Mascot search engine to label correct and incorrect PSMs. We show that Nokoi outperforms Mascot and achieves a performance very close to that of Percolator at substantially higher processing speeds.
Keywords
METAPROTEOMICS, CONFIDENCE, PROTEINS, PROTEOMICS, PROTEOGENOMICS, STATISTICAL-MODEL, SPECTROMETRY, MS/MS, DATABASE SEARCH, TANDEM MASS-SPECTRA, decoy databases, machine learning, peptide identification

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Chicago
Gonnelli, Giulia, Michiel Stock, Jan Verwaeren, Davy Maddelein, Bernard De Baets, Lennart Martens, and Sven Degroeve. 2015. “A Decoy-free Approach to the Identification of Peptides.” Journal of Proteome Research 14 (4): 1792–1798.
APA
Gonnelli, G., Stock, M., Verwaeren, J., Maddelein, D., De Baets, B., Martens, L., & Degroeve, S. (2015). A decoy-free approach to the identification of peptides. JOURNAL OF PROTEOME RESEARCH, 14(4), 1792–1798.
Vancouver
1.
Gonnelli G, Stock M, Verwaeren J, Maddelein D, De Baets B, Martens L, et al. A decoy-free approach to the identification of peptides. JOURNAL OF PROTEOME RESEARCH. 2015;14(4):1792–8.
MLA
Gonnelli, Giulia, Michiel Stock, Jan Verwaeren, et al. “A Decoy-free Approach to the Identification of Peptides.” JOURNAL OF PROTEOME RESEARCH 14.4 (2015): 1792–1798. Print.
@article{6896431,
  abstract     = {A growing number of proteogenomics and metaproteomics studies indicate potential limitations of the application of the decoy database paradigm used to separate correct peptide identifications from incorrect ones in traditional shotgun proteomics. We therefore propose a binary classifier called Nokoi that allows fast yet reliable decoy-free separation of correct from incorrect peptide-to-spectrum matches (PSMs). Nokoi was trained on a very large collection of heterogeneous data using ranks supplied by the Mascot search engine to label correct and incorrect PSMs. We show that Nokoi outperforms Mascot and achieves a performance very close to that of Percolator at substantially higher processing speeds.},
  author       = {Gonnelli, Giulia and Stock, Michiel and Verwaeren, Jan and Maddelein, Davy and De Baets, Bernard and Martens, Lennart and Degroeve, Sven},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {METAPROTEOMICS,CONFIDENCE,PROTEINS,PROTEOMICS,PROTEOGENOMICS,STATISTICAL-MODEL,SPECTROMETRY,MS/MS,DATABASE SEARCH,TANDEM MASS-SPECTRA,decoy databases,machine learning,peptide identification},
  language     = {eng},
  number       = {4},
  pages        = {1792--1798},
  title        = {A decoy-free approach to the identification of peptides},
  url          = {http://dx.doi.org/10.1021/pr501164r},
  volume       = {14},
  year         = {2015},
}

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