Artificial decoy spectral libraries for false discovery rate estimation in spectral library searching in proteomics

Journal of Proteome Research

Volumn 9, Issue 1, 2010, Pages 605-610

  Lam, Henry ^a   Deutsch, Eric W ^b   Aebersold, Ruedi ^b,c,d  

^a HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^b INSTITUTE FOR SYSTEMS BIOLOGY   (United States)

^c ETH ZURICH   (Switzerland)

^d UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Decoy counting; False discovery rates; Spectral libraries; Target decoy searching

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL DECOY SPECTRAL LIBRARY; COMPUTER PROGRAM; DATA BASE; FALSE DISCOVERY RATE; HUMAN; MASS SPECTROMETRY; PARAMETER; PRIORITY JOURNAL; PROTEIN DETERMINATION; PROTEOMICS; RELIABILITY; REPRODUCIBILITY; TARGET DECOY SEARCHING; TECHNIQUE; VALIDITY;

ALGORITHMS; DATABASES, PROTEIN; HUMANS; PROTEOMICS; SOFTWARE; TANDEM MASS SPECTROMETRY;

EID: 73649110293     PISSN: 15353893     EISSN: None     Source Type: Journal    
DOI: 10.1021/pr900947u     Document Type: Article

References (29)

1. Aebersold, R.; Mann, M. Mass spectrometry-based proteomics. Nature 2003, 422, 198-207.
2. Domon, B.; Aebersold, R. Mass spectrometry and protein analysis. Science 2006, 312, 212-217.
3. Steen, H.; Mann, M. The ABC's (and XYZ's) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 2004, 5, 699-711.
4. Eng, J. K.; McCormack, A. L.; Yates, J. R., III. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom. 1994, 5, 976-989.
5. Perkins, D. N.; Pappin, D. J. C.; Creasy, D. M.; Cottrell, J. S. Probability-based protein identification by searching sequence database using mass spectrometry data. Electrophoresis 1999, 20, 3551-3567.
6. Craig, R.; Beavis, R. C. TANDEM: Matching proteins with mass spectra. Bioinformatics 2004, 20, 1466-1467.
7. Geer, L. Y.; Markey, S. P.; Kowalak, J. A.; Wagner, L.; Xu, M.; Maynard, D. M.; Yang, X.; Shi, W.; Bryant, S. H. Open mass spectrometry search algorithm. J. Proteome Res. 2004, 3, 958-964.
8. Tabb, D. L.; Fernando, C. G.; Chambers, M. C. MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis. J. Proteome Res. 2007, 6, 654-661.
9. Lam, H.; Deutsch, E. W.; Eddes, J. S.; Eng, J. K.; King, N.; Stein, S. E.; Aebersold, R. Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics 2007, 7, 655-667.
10. Craig, R.; Cortens, J. C.; Fenyo, D.; Beavis, R. C. Using annotated peptide mass spectrum libraries for protein identification. J. Proteome Res. 2006, 5, 1843-1849.
11. Frewen, B. E.; Merrihew, G. E.; Wu, C. C.; Noble, W. S.; MacCoss, M. J. Analysis of peptide MS/MS spectra from large-scale proteomics experiments using spectrum libraries. Anal. Chem. 2006, 78, 5678-5684.
12. Falkner, J. A.; Falkner, J. W.; Yocum, A. K.; Andrews, P. C. A spectral clustering approach to MS/MS identification of post-translational modifications. J. Proteome Res. 2008, 7, 4614-4622.
13. Nesvizhskii, A. I.; Vitek, O.; Aebersold, R. Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat. Methods 2007, 4, 787-797.
14. Choi, H.; Nesvizhskii, A. I. False discovery rates and related statistical concepts in mass spectrometry-based proteomics. J. Proteome Res. 2008, 7, 47-50.
15. Fitzgibbon, M.; Li, Q.; McIntosh, M. Modes of inference for evaluating the confidence of peptide identifications. J. Proteome Res. 2007, 7, 35-39.
16. Keller, A.; Nesvizhskii, A. I.; Kolker, E.; Aebersold, R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 2002, 74, 5383-5392.
17. Elias, J. E.; Gygi, S. P. Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat. Methods 2007, 4, 207-214.
18. Käll, L.; Storey, J.; Maccoss, M.; Noble, W. Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. J. Proteome Res. 2008, 7, 29-34.
19. Shen, C.; Sheng, Q.; Dai, J.; Li, Y.; Zeng, R.; Hang, H. On the estimation of false positives in peptide identifications using decoy search strategy. Proteomics 2009, 9, 194-204.
20. Käll, L.; Canterbury, J. D.; Weston, J.; Noble, W. S.; MacCoss, M. J. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nature Methods 2007, 4, 923-925.
21. Shen, Y.; Tolic, N.; Hixson, K. K.; Purvine, S. O.; Pasa-Tolic, L.; Qian, W.; Adkins, J. N.; Moore, R. J.; Smith, R. D. Proteome-wide identification of proteins and their modifications with decreased ambiguities and improved false discovery rates using unique sequence tags. Anal. Chem. 2008, 80, 1871-1882.
22. Kim, S.; Gupta, N.; Pevzner, P. A. Spectral probabilities and generating functions of tandem mass spectra: a strike against decoy databases. J. Proteome Res. 2008, 7, 3354-3363.
23. Lam, H.; Deutsch, E. W.; Eddes, J. S.; Eng, J. K.; Stein, S. E.; Aebersold, R. Building consensus spectral libraries for peptide identification in proteomics. Nat. Methods 2008, 5, 873-875.
24. Keller, A.; Eng, J.; Zhang, N.; Li, X. J.; Aebersold, R. A uniform proteomics MS/MS analysis platform utilizing open XML file formats. Mol. Syst. Biol. 2005, 1, 17.
25. Omenn, G. S.; States, D. J.; Adamski, M.; Blackwell, T. W.; Menon, R.; Hermjakob, H.; Apweiler, R.; Haab, B. B.; Simpson, R. J.; Eddes, J. S.; Kapp, E. A.; Moritz, R. L.; Chan, D. W.; Rai, A. J.; Admon, A.; Aebersold, R.; Eng, J.; Hancock, W. S.; Hefta, S. A.; Meyer, H.; Paik, Y. K.; Yoo, J. S.; Ping, P.; Pounds, J.; Adkins, J.; Qian, X.; Wang, R.; Wasinger, V.; Wu, C. Y.; Zhao, X.; Zeng, R.; Archakov, A.; Tsugita, A.; Beer, I.; Pandey, A.; Pisano, M.; Andrews, P.; Tammen, H.; Speicher, D. W.; Hanash, S. M. Overview of the HUPO Plasma Proteome Project: Results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database. Proteomics 2005, 5, 3226-3245.
26. Zhang, Z. Prediction of low-energy collision-induced dissociation spectra of peptides. Anal. Chem. 2004, 76, 3908-3922.
27. Yen, C.-Y.; Meyer-Arendt, K.; Eichelberger, B.; Sun, S.; Houel, S.; Old, W. M.; Knight, R.; Ahn, N. G.; Hunter, L. E.; Resing, K. A. A simulated MS/MS library for spectrum-to-spectrum searching in large scale identification of proteins. Mol. Cell. Proteomics 2009, 8, 857-869.
28. Feng, J.; Naiman, D. Q.; Cooper, B. Probability-based pattern recognition and statistical framework for randomization: modeling tandem mass spectrum/peptide sequence false match frequencies. Bioinformatics 2007, 23, 2210-2217.
29. Colinge, J.; Masselot, A.; Giron, M.; Dessingy, T.; Magnin, J. OLAV: Towards high-throughput tandem mass spectrometry data identification. Proteomics 2003, 3, 1454-1463.