Hierarchical clustering of shotgun proteomics data

Molecular and Cellular Proteomics

Volumn 10, Issue 6, 2011, Pages

  Koskinen, Ville R ^a   Emery, Patrick A ^a   Creasy, David M ^a   Cottrell, John S ^a  

^a Matrix Science Ltd   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CYTOCHROME B5; CYTOCHROME B5 REDUCTASE; CYTOCHROME P450 1A2; CYTOCHROME P450 3A11; ESTERASE; GLUCURONOSYLTRANSFERASE; GLUTATHIONE TRANSFERASE; RETINOL DEHYDROGENASE; RIBOSOMAL PROTEIN L1; PEPTIDE FRAGMENT;

ANIMAL EXPERIMENT; ARTICLE; FUNCTIONAL PROTEOMICS; GENE CLUSTER; GENETIC ALGORITHM; MOUSE; NONHUMAN; NUCLEOTIDE SEQUENCE; PHYLOGENETIC TREE; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN EXPRESSION; ALGORITHM; AMINO ACID SEQUENCE; CHEMICAL STRUCTURE; CHEMISTRY; CLUSTER ANALYSIS; COMPUTER SIMULATION; METHODOLOGY; MOLECULAR GENETICS; MOLECULAR WEIGHT; PROTEIN DATABASE; PROTEOMICS; SEQUENCE ANALYSIS; TANDEM MASS SPECTROMETRY;

ALGORITHMS; AMINO ACID SEQUENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; DATABASES, PROTEIN; MODELS, MOLECULAR; MOLECULAR SEQUENCE DATA; MOLECULAR WEIGHT; PEPTIDE FRAGMENTS; PROTEOMICS; SEQUENCE ANALYSIS, PROTEIN; TANDEM MASS SPECTROMETRY;

EID: 79957982498     PISSN: 15359476     EISSN: 15359484     Source Type: Journal    
DOI: 10.1074/mcp.M110.003822     Document Type: Article

References (35)

1. Nesvizhskii, A. I., and Aebersold, R. (2005) Interpretation of shotgun proteomic data - The protein inference problem. Mol. Cell. Proteomics 4, 1419-1440
2. Li, N., Wu, S. F., Zhu, Y. P., and Yang, X. M. (2009) The progress of protein quality control methods in shotgun proteomics. Prog. Biochem. Biophys. 36, 668-675
3. Yang, X., Dondeti, V., Dezube, R., Maynard, D. M., Geer, L. Y., Epstein, J., Chen, X., Markey, S. P., and Kowalak, J. A. (2004) DBParser: web-based software for shotgun proteomic data analyses. J. Proteome Res. 3, 1002-1008
4. Slotta, D. J., McFarland, M. A., and Markey, S. P. (2010) MassSieve: Panning MS/MS peptide data for proteins. Proteomics 10, 3035-3039
5. Kristensen, D. B., Brønd, J. C., Nielsen, P. A., Andersen, J. R., Sørensen, O. T., Jørgensen, V., Budin, K., Matthiesen, J., Venø, P., Jespersen, H. M., Ahrens, C. H., Schandorff, S., Ruhoff, P. T., Wisniewski, J. R., Bennett, K. L., and Podtelejnikov, A. V. (2004) Experimental Peptide Identification Repository (EPIR): An integrated peptide-centric platform for validation and mining of tandem mass spectrometry data. Mol. Cell. Proteomics 3, 1023-1038
6. Resing, K. A., Meyer-Arendt, K., Mendoza, A. M., Aveline-Wolf, L. D., Jonscher, K. R., Pierce, K. G., Old, W. M., Cheung, H. T., Russell, S., Wattawa, J. L., Goehle, G. R., Knight, R. D., and Ahn, N. G. (2004) Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics. Anal. Chem. 76, 3556-3568
7. Tabb, D. L., McDonald, W. H., and Yates, J. R., 3rd (2002) DTASelect and contrast: Tools for assembling and comparing protein identifications from shotgun proteomics. J. Proteome Res. 1, 21-26
8. Stephan, C., Reidegeld, K. A., Hamacher, M., van, Hall, A., Marcus, K., Taylor, C., Jones, P., Müller, M., Apweiler, R., Martens, L., Körting, G., Chamrad, D. C., Thiele, H., Blüggel, M., Parkinson, D., Binz, P. A., Lyall, A., and Meyer, H. E. (2006) Automated reprocessing pipeline for search- ing heterogeneous mass spectrometric data of the HUPO brain proteome project pilot phase. Proteomics 6, 5015-5029
9. Zhang, B., Chambers, M. C., and Tabb, D. L. (2007) Proteomic parsimony through bipartite graph analysis improves accuracy and transparency. J. Proteome Res. 6, 3549-3557
10. Ma, Z. Q., Dasari, S., Chambers, M. C., Litton, M. D., Sobecki, S. M., Zimmerman, L. J., Halvey, P. J., Schilling, B., Drake, P. M., Gibson, B. W., and Tabb, D. L. (2009) IDPicker 2.0: Improved protein assembly with high discrimination peptide identification Filtering. J. Proteome Res. 8, 3872-3881
11. Weatherly, D. B., Atwood, J. A., 3rd, Minning, T. A., Cavola, C., Tarleton, R. L., and Orlando, R. (2005) A heuristic method for assigning a false-discovery rate for protein identifications from Mascot database search results. Mol. Cell. Proteomics 4, 762-772
12. Moore, R. E., Young, M. K., and Lee, T. D. (2002) Qscore: An algorithm for evaluating SEQUEST database search results. J. Am. Soc. Mass Spectrom. 13, 378-386
13. Kislinger, T., Rahman, K., Radulovic, D., Cox, B., Rossant, J., and Emili, A. (2003) PRISM, a generic large scale proteomic investigation strategy for mammals. Mol. Cell. Proteomics 2, 96-106
14. Nesvizhskii, A. I., Keller, A., Kolker, E., and Aebersold, R. (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646-4658
15. Sadygov, R. G., Liu, H., and Yates, J. R. (2004) Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases. Anal. Chem. 76, 1664-1671
16. Feng, J., Naiman, D. Q., and Cooper, B. (2007) Probability model for assessing proteins assembled from peptide sequences inferred from tandem mass spectrometry data. Anal. Chem. 79, 3901-3911
17. Price, T. S., Lucitt, M. B., Wu, W., Austin, D. J., Pizarro, A., Yocum, A. K., Blair, I. A., FitzGerald, G. A., and Grosser, T. (2007) EBP, a program for protein identification using multiple tandem mass spectrometry datasets. Mol. Cell. Proteomics 6, 527-536
18. Shi, J. H., and Wu, F. X. (2009) Protein inference by assembling peptides identified from tandem mass spectra. Curr. Bioinf. 4, 226-233
19. Kuster, B., Schirle, M., Mallick, P., and Aebersold, R. (2005) Scoring proteomes with proteotypic peptide probes. Nat. Rev. Mol. Cell Biol. 6, 577-583
20. Li, Y. F., Arnold, R. J., Li, Y., Radivojac, P., Sheng, Q., and Tang, H. (2009) A Bayesian approach to protein inference problem in shotgun proteomics. J. Comput. Biol. 16, 1183-1193
21. Li, J., Zimmerman, L. J., Park, B. H., Tabb, D. L., Liebler, D. C., and Zhang, B. (2009). Network-assisted protein identification and data interpretation in shotgun proteomics. Mol. Syst. Biol. 5, http://dx.doi. org/10.1038/msb.2009.54
22. Gupta, N., and Pevzner, P. A. (2009) False discovery rates of protein identifications: a strike against the two-peptide rule. J. Proteome Res. 8, 4173-4181
23. Grobei, M. A., Qeli, E., Brunner, E., Rehrauer, H., Zhang, R., Roschitzki, B., Basler, K., Ahrens, C. H., and Grossniklaus, U. (2009) Deterministic protein inference for shotgun proteomics data provides new insights into Arabidopsis pollen development and function. Genome Res. 19, 1786-1800
24. Qeli, E., and Ahrens, C. H. (2010) Peptide Classifier for protein inference and targeted quantitative proteomics. Nat. Biotechnol. 28, 647-650
25. Reiter, L., Claassen, M., Schrimpf, S. P., Jovanovic, M., Schmidt, A., Buhmann, J. M., Hengartner, M. O., and Aebersold, R. (2009) Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry. Mol. Cell. Proteomics 8, 2405-2417
26. Cochrane, G. R., and Galperin, M. Y. (2010) The 2010 Nucleic Acids Research database issue and online database collection: a community of data resources. Nucleic Acids Res. 38, D1-D4
27. Duncan, M. W., Aebersold, R., and Caprioli, R. M. (2010) The pros and cons of peptide-centric proteomics. Nat. Biotechnol. 28, 659-664
28. Sayers, E. W., Barrett, T., Benson, D. A., Bolton, E., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., Dicuccio, M., Federhen, S., Feolo, M., Geer, L. Y., Helmberg, W., Kapustin, Y., Landsman, D., Lipman, D. J., Lu, Z., Madden, T. L., Madej, T., Maglott, D. R., Marchler-Bauer, A., Miller, V., Mizrachi, I., Ostell, J., Panchenko, A., Pruitt, K. D., Schuler, G. D., Sequeira, E., Sherry, S. T., Shumway, M., Sirotkin, K., Slotta, D., Souvorov, A., Starchenko, G., Tatusova, T. A., Wagner, L., Wang, Y., John, Wilbur, W., Yaschenko, E., and Ye, J. (2010) Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 38, D5-16
29. Alm, R., Johansson, P., Hjerno, K., Emanuelsson, C., Ringnér, M., and Häkkinen, J. (2006) Detection and identification of protein isoforms using cluster analysis of MALDI-MS mass spectra. J. Proteome Res. 5, 785-792
30. Seymour, S. L., Lane, W. S., Nesvizhskii, A. I., Searle, B., Tabb, D. L., and Kowalak, J. A. (2008) RG11 ABRF iPRG2008 Study: assessing the quality and consistency of protein reporting on a common dataset. J. Biomol. Tech. 19, 88-93
31. Searle, B. C. (2010) Scaffold: A bioinformatic tool for validating MS/MS-based proteomic studies. Proteomics 10, 1265-1269
32. Seymour, S. L. (2010) Assessing and interpreting protein identifications. J. Biomol. Tech. 21, S12
33. Ishihama, Y., Oda, Y., Tabata, T., Sato, T., Nagasu, T., Rappsilber, J., and Mann, M. (2005) Exponentially modified protein abundance index (em- PAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol. & Cell. Proteomics 4, 1265-1272 (Pubitemid 41448714)
34. Larkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., Valentin, F., Wallace, I. M., Wilm, A., Lopez, R., Thompson, J. D., Gibson, T. J., and Higgins, D. G. (2007) ClustalW and ClustalX version 2. Bioinformatics 23, 2947-2948
35. Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. (2001) Introduction to Algorithms, 2nd Ed., MIT Press and McGraw-Hill, Cambridge, MA