ProteinLasso: A Lasso regression approach to protein inference problem in shotgun proteomics

Computational Biology and Chemistry

Volumn 43, Issue , 2013, Pages 46-54

  Huang, Ting ^a   Gong, Haipeng ^a   Yang, Can ^b   He, Zengyou ^a  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^b YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Coordinate descent; Ensemble learning; Lasso; Protein inference; Proteomics

Indexed keywords

COORDINATE DESCENT; DATA SETS; DETECTABILITY; ENSEMBLE LEARNING; IDENTIFICATION ACCURACY; IDENTIFICATION OF PROTEINS; INFERENCE ALGORITHM; INFERENCE PROBLEM; LASSO; PARAMETER SELECTION; PARAMETER SPECIFICATION; PROTEOMICS; PROTEOMICS RESEARCH; REGRESSION PROBLEM; RUNNING EFFICIENCY; SHOTGUN PROTEOMICS; SOURCE CODES;

ALGORITHMS; IDENTIFICATION (CONTROL SYSTEMS); INFERENCE ENGINES; MOLECULAR BIOLOGY; PEPTIDES;

PROBLEM SOLVING;

PEPTIDE;

ALGORITHM; ARTICLE; CHEMISTRY; HUMAN; PROTEIN DATABASE; PROTEOMICS; REGRESSION ANALYSIS; SEQUENCE ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; DATABASES, PROTEIN; HUMANS; MODELS, STATISTICAL; PEPTIDES; PROTEOMICS; REGRESSION ANALYSIS; SEQUENCE ANALYSIS, PROTEIN;

EID: 84873384484     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiolchem.2012.12.008     Document Type: Article

References (44)

1. P. Alves, R.J. Arnold, M.V. Novotny, P. Radivojac, J.P. Reilly, and H. Tang Advancement in protein inference from shotgun proteomics using peptide detectability Pacific Symposium on Biocomputing 2007 409 420
2. M. Bern, and D. Goldberg Improved ranking functions for protein and modification-site identifications Journal of Computational Biology 15 7 2008 705 719
3. W.P. Blackstock, and M.P. Weir Proteomics: quantitative and physical mapping of cellular proteins Trends in Biotechnology 17 3 1999 121 127 (Pubitemid 29348464)
4. D.N. Chakravarti, B. Chakravarti, and I. Moutsatsos Informatic tools for proteome profiling Biotechniques Suppl. 32 2002 4 15
5. V. Dancik, T.A. Addona, and K.R. Clauser De novo peptide sequencing via tandem mass spectrometry Journal of Computational Biology 6 3-4 1999 327 342
6. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani Least angle regression The Annals of Statistics 32 2 2004 407 499 (Pubitemid 41250302)
7. J.K. Eng, A.L. McCormack, and J.R. Yates An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database Journal of American Society for Mass Spectrometry 5 11 1994 976 989
8. J. Feng, D.Q. Naiman, and B. Cooper Probability model for assessing proteins assembled from peptides sequences inferred from tandem mass spectrometry data Analytical Chemistry 79 10 2007 3901 3911 (Pubitemid 46799089)
9. D. Fenyo Identifying the proteome: software tools Current Opinion in Biotechnology 11 4 2000 391 395 (Pubitemid 30598933)
10. J. Friedman, T. Hastie, H. Hoeing, and R. Tibshirani Pathwise coordinate optimization The Annals of Applied Statistics 2 1 2007 302 332
11. J. Friedman, T. Hastie, and R. Tibshirani Regularization paths for generalized linear models via coordinate descent Journal of Statistical Software 33 1 2010 1 22
12. S. Gerster, E. Qeli, C.H. Ahrens, and P. Buhlmann Protein and gene model inference based on statistical modeling in k-partite graphs Proceedings of the National Academy of Sciences of United States of America 107 27 2010 12101 12106
13. M.A. Grobei, E. Qeli, E. Brunner, H. Rehrauer, R. Zhang, B. Roschitzki, K. Basler, C.H. Ahrens, and U. Grossniklaus Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function Genome Research 19 10 2009 1786 1800
14. Z. He, C. Yang, and W. Yu A partial set covering model for protein mixture identification using mass spectrometry data IEEE/ACM Transactions on Computational Biology and Bioinformatics 8 2 2011 368 380
15. T. Huang, J. Wang, W. Yu, and Z. He Protein inference: a review Briefings in Bioinformatics 13 5 2012 586 614
16. P. Kearney, H. Butler, K. Eng, and P. Hugo Protein identification and peptide expression resolver: harmonizing protein identification with protein expression data Journal of Proteome Research 7 1 2008 234 244 (Pubitemid 351171136)
17. A. Keller, A.I. Nesvizhskii, E. Kolker, and R. Aebersold Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search Analytical Chemistry 74 20 2002 5383 5392 (Pubitemid 35215372)
18. J. Klimek, J.S. Eddes, and L. Hohmann The standard protein mix database: a diverse data set to assist in the production of improved peptide and protein identification software tools Journal of Proteome Research 7 1 2008 96 103 (Pubitemid 351171120)
19. J. Li, L.J. Zimmerman, B.-H. Park, D.L. Tabb, D.C. Liebler, and B. Zhang Network-assisted protein identification and data interpretation in shotgun proteomics Molecular Systems Biology 5 2009 303
20. Q. Li, M. MacCoss, and M. Stephens A nested mixture model for protein identification using mass spectrometry The Annals of Applied Statistics 4 2 2010 962 987
21. Y.F. Li, R.J. Arnold, Y. Li, P. Radivojac, Q. Sheng, and H. Tang A Bayesian approach to protein inference problem in shotgun proteomics Journal of Computational Biology 16 8 2009 1 11
22. Y.F. Li, and P. Radivojac Computational approaches to protein inference in shotgun proteomics BMC Bioinformatics 13 Suppl. 16 2012 S4
23. B. Lu, A. Motoyama, C. Ruse, J. Venable, and J.R. Yates Improving protein identification sensitivity by combining MS and MS/MS information for shotgun proteomics using LTQ-Orbitrap high mass accuracy data Analytical Chemistry 80 6 2008 2018 2025 (Pubitemid 351458047)
24. Z.-Q. Ma, S. Dasari, M.C. Chambers, M. Litton, S.M. Sobecki, L. Zimmerman, P.J. Halvey, B. Schilling, P.M. Drake, B.W. Gibson, and D.L. Tabb IDPicker 2.0: improved protein assembly with high discrimination peptide identification filtering Journal of Proteome Research 8 8 2009 3872 3881
25. R.E. Moore, M.K. Young, and T.D. Lee Qscore: an algorithm for evaluating sequest database search results Journal of American Society for Mass Spectrometry 13 4 2002 378 386 (Pubitemid 34280088)
26. A.I. Nesvizhskii, A. Keller, E. Kolker, and R. Aebersold A statistical model for identifying proteins by tandem mass spectrometry Analytical Chemistry 75 17 2003 4646 4658 (Pubitemid 37082259)
27. D.N. Perkins, D.J. Pappin, D.M. Creasy, and J.S. Cottrell Probability-based protein identification by searching sequence databases using mass spectrometry data Electrophoresis 20 18 1999 3551 3567 (Pubitemid 30007252)
28. T.S. Price, M.B. Lucitt, W. Wu, D.J. Austin, A. Pizarro, A.K. Yocum, I.A. Blair, G.A. FitzGerald, and T. Grosser EBP: protein identification using multiple tandem mass spectrometry datasets Molecular & Cellular Proteomics 6 3 2007 527 536 (Pubitemid 46554546)
29. E. Qeli, and C.H. Ahrens PeptideClassifier for protein inference and targeted quantitative proteomics Nature Biotechnology 28 7 2010 647 650
30. S.R. Ramakrishnan, C. Vogel, T. Kwon, L.O. Penalva, E.M. Marcotte, and D.P. Miranker Mining gene functional networks to improve mass-spectrometry based protein identification Bioinformatics 25 22 2009 2955 2961
31. S.R. Ramakrishnan, C. Vogel, J.T. Prince, R. Wang, Z. Li, L.O. Penalva, M. Myers, E.M. Marcotte, and D.P. Miranker Integrating shotgun proteomics and mRNA expression data to improve protein identification Bioinformatics 25 11 2009 1397 1403
32. R.G. Sadygov, H. Liu, and J.R. Yates Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases Analytical Chemistry 76 6 2004 1664 1671 (Pubitemid 38338411)
33. B.C. Searle Scaffold: A bioinformatic tool for validating MS/MS-based proteomic studies Proteomics 10 6 2010 1265 1269
34. O. Serang, M.J. MacCoss, and W.S. Noble Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data Journal of Proteome Research 9 10 2010 5346 5357
35. C. Shen, Z. Wang, G. Shankar, X. Zhang, and L. Li A hierarchical statistical model to assess the confidence of peptides and proteins inferred from tandem mass spectrometry Bioinformatics 24 2 2008 202 208
36. D.J. Slotta, M.A. McFarland, and S.P. Markey MassSieve: panning MS/MS peptide data for proteins Proteomics 10 16 2010 3035 3039
37. M. Spivak, J. Weston, M.J. MacCoss, and W.S. Noble Direct maximization of protein identifications from tandem mass spectra Molecular & Cellular Proteomics 11 2 2012 M111.012161
38. D.L. Tabb, H. McDonald, and J.R. Yates DTASelect and contrast: tools for assembling and comparing protein identifications from shotgun proteomics Journal of Proteome Research 1 1 2002 21 26
39. H. Tang, R.J. Arnold, P. Alves, Z. Xun, D.E. Clemmer, M.V. Novotny, J.P. Reilly, and P. Radivojac A computational approach toward label-free protein quantification using predicted peptide detectability Bioinformatics 22 14 2006 e481 e488
40. R. Tibshirani Regression shrinkage and selection via the lasso Journal of the Royal Statistical Society. Series B (Methodological) 58 1 1996 267 288
41. O. Vitek Getting started in computational mass spectrometry-based proteomics PLoS Computational Biology 5 5 2009 e1000366
42. D.B. Weatherly, J.A. Atwood, T.A. Minning, C. Cavola, R.L. Tarleton, and R. Orlando A heuristic method for assigning a false-discovery rate for protein identifications from mascot database search results Molecular & Cellular Proteomics 4 6 2005 762 772 (Pubitemid 40873005)
43. X. Yang, V. Dondeti, R. Dezube, D.M. Maynard, L.Y. Geer, J. Epstein, X. Chen, S.P. Markey, and J.A. Kowalak DBParser: web-based software for shotgun proteomic data analyses Journal of Proteome Research 3 5 2004 1002 1008 (Pubitemid 39425657)
44. B. Zhang, M.C. Chambers, and D.L. Tabb Proteomic parsimony through bipartite graph analysis improves accuracy and transparency Journal of Proteome Research 6 9 2007 3549 3557 (Pubitemid 47522746)