A decoy-free approach to the identification of peptides
- Author
- Giulia Gonnelli (UGent) , Michiel Stock (UGent) , Jan Verwaeren (UGent) , Davy Maddelein (UGent) , Bernard De Baets (UGent) , Lennart Martens (UGent) and Sven Degroeve (UGent)
- Organization
- Project
- 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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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-6896431
- MLA
- Gonnelli, Giulia, et al. “A Decoy-Free Approach to the Identification of Peptides.” JOURNAL OF PROTEOME RESEARCH, vol. 14, no. 4, 2015, pp. 1792–98, doi:10.1021/pr501164r.
- 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. https://doi.org/10.1021/pr501164r
- Chicago author-date
- 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): 1792–98. https://doi.org/10.1021/pr501164r.
- Chicago author-date (all authors)
- 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. doi:10.1021/pr501164r.
- 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.
- IEEE
- [1]G. Gonnelli et al., “A decoy-free approach to the identification of peptides,” JOURNAL OF PROTEOME RESEARCH, vol. 14, no. 4, pp. 1792–1798, 2015.
@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}},
keywords = {{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://doi.org/10.1021/pr501164r}},
volume = {{14}},
year = {{2015}},
}
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