DIA-Umpire: Comprehensive computational framework for data-independent acquisition proteomics

Nature Methods

Volumn 12, Issue 3, 2015, Pages 258-264

  Tsou, Chih Chiang ^a   Avtonomov, Dmitry ^a   Larsen, Brett ^b   Tucholska, Monika ^b   Choi, Hyungwon ^c   Gingras, Anne Claude ^b,d   Nesvizhskii, Alexey I ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^b MOUNT SINAI HOSPITAL   (Canada)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^d UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CASEIN KINASE II; CYCLIN DEPENDENT KINASE 9; CYCLIN T; INITIATION FACTOR; INITIATION FACTOR 3; INITIATION FACTOR 4; INITIATION FACTOR 4A; MESSENGER RNA; PEPTIDE FRAGMENT; POLYADENYLIC ACID BINDING PROTEIN; PROTEIN PRECURSOR; PROTEOME; RNA BINDING PROTEIN; RNA HELICASE; SMALL NUCLEAR RNA; UBIQUITIN; UNCLASSIFIED DRUG; PROTEIN;

ARTICLE; BINDING AFFINITY; CHROMATOGRAPHY; COMPUTER PROGRAM; DATA BASE; DATA EXTRACTION; DATA INDEPENDENT ACQUISITION; HUMAN; HUMAN CELL; INFORMATION PROCESSING; LIMIT OF QUANTITATION; LIQUID CHROMATOGRAPHY; MEASUREMENT ACCURACY; PEPTIDE LIBRARY; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN BINDING; PROTEIN PURIFICATION; PROTEOMICS; QUANTITATIVE ANALYSIS; SEARCH ENGINE; TANDEM MASS SPECTROMETRY; WORKFLOW; ALGORITHM; MASS SPECTROMETRY; METABOLOMICS; PROCEDURES; PROTEIN DATABASE; SOFTWARE;

ALGORITHMS; DATABASES, PROTEIN; HUMANS; MASS SPECTROMETRY; METABOLOMICS; PEPTIDE FRAGMENTS; PROTEINS; PROTEOMICS; SOFTWARE; WORKFLOW;

EID: 84923838580     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/nmeth.3255     Document Type: Article

References (50)

1. Bantscheff, M., Lemeer, S., Savitski, M.M. & Kuster, B. Quantitative mass spectrometry in proteomics: critical review update from 2007 to the present. Anal. Bioanal. Chem. 404, 939-965 (2012
2. Nesvizhskii, A.I. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J. Proteomics 73, 2092-2123 (2010
3. Bailey, D.J., McDevitt, M.T., Westphall, M.S., Pagliarini, D.J. & Coon, J.J. Intelligent data acquisition blends targeted and discovery methods. J. Proteome Res. 13, 2152-2161 (2014
4. Weisbrod, C.R., Eng, J.K., Hoopmann, M.R., Baker, T. & Bruce, J.E. Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification. J. Proteome Res. 11, 1621-1632 (2012
5. Michalski, A., Cox, J. & Mann, M. More than 100, 000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS. J. Proteome Res. 10, 1785-1793 (2011
6. Gillet, L.C., et al. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell. Proteomics 11, O111.016717 (2012
7. Tate, S., Larsen, B., Bonner, R. & Gingras, A.C. Label-free quantitative proteomics trends for protein-protein interactions. J. Proteomics 81, 91-101 (2013
8. Venable, J.D., Dong, M.Q., Wohlschlegel, J., Dillin, A. & Yates, J.R. Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 1, 39-45 (2004
9. Silva, J.C., Gorenstein, M.V., Li, G.Z., Vissers, J.P. & Geromanos, S.J. Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol. Cell. Proteomics 5, 144-156 (2006
10. Panchaud, A., et al. Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Anal. Chem. 81, 6481-6488 (2009
11. Geiger, T., Cox, J. & Mann, M. Proteomics on an Orbitrap benchtop mass spectrometer using all-ion fragmentation. Mol. Cell. Proteomics 9, 2252-2261 (2010
12. Egertson, J.D., et al. Multiplexed MS/MS for improved data-independent acquisition. Nat. Methods 10, 744-746 (2013
13. Distler, U., et al. Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics. Nat. Methods 11, 167-170 (2014
14. Purvine, S., Eppel, J.T., Yi, E.C. & Goodlett, D.R. Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3, 847-850 (2003
15. Colangelo, C.M., Chung, L., Bruce, C. & Cheung, K.H. Review of software tools for design and analysis of large scale MRM proteomic datasets. Methods 61, 287-298 (2013
16. Röst, H.L., et al. OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data. Nat. Biotechnol. 32, 219-223 (2014
17. Rosenberger, G., et al. A repository of assays to quantify 10, 000 human proteins by SWATH-MS. Sci. Data 1, 140031 (2014
18. Li, G.Z., et al. Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics 9, 1696-1719 (2009
19. Pak, H., et al. Clustering and filtering tandem mass spectra acquired in data-independent mode. J. Am. Soc. Mass Spectrom. 24, 1862-1871 (2013
20. Craig, R., Cortens, J.P. & Beavis, R.C. Open source system for analyzing, validating, and storing protein identification data. J. Proteome Res. 3, 1234-1242 (2004
21. Eng, J.K., Jahan, T.A. & Hoopmann, M.R. Comet: an open-source MS/MS sequence database search tool. Proteomics 13, 22-24 (2013
22. Kim, S., et al. The generating function of CID, ETD, and CID/ETD pairs of tandem mass spectra: applications to database search. Mol. Cell. Proteomics 9, 2840-2852 (2010
23. 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. 74, 5383-5392 (2002
24. Shteynberg, D., et al. iProphet: multi-level integrative analysis of shotgun proteomic data improves peptide and protein identification rates and error estimates. Mol. Cell. Proteomics 10, M111.007690 (2011
25. Nesvizhskii, A.I., Keller, A., Kolker, E. & Aebersold, R. A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646-4658 (2003
26. Lambert, J.P., et al. Mapping differential interactomes by affinity purification coupled with data-independent mass spectrometry acquisition. Nat. Methods 10, 1239-1245 (2013
27. Lam, H., et al. Building consensus spectral libraries for peptide identification in proteomics. Nat. Methods 5, 873-875 (2008
28. Reiter, L., et al. mProphet: automated data processing and statistical validation for large-scale SRM experiments. Nat. Methods 8, 430-435 (2011
29. Liu, Y., et al. Glycoproteomic analysis of prostate cancer tissues by SWATH mass spectrometry discovers N-Acylethanolamine acid amidase and protein tyrosine kinase 7 as signatures for tumor aggressiveness. Mol. Cell. Proteomics 13, 1753-1768 (2014
30. Schwanhäusser, B., et al. Global quantification of mammalian gene expression control. Nature 473, 337-342 (2011
31. Ludwig, C., Claassen, M., Schmidt, A. & Aebersold, R. Estimation of absolute protein quantities of unlabeled samples by selected reaction monitoring mass spectrometry. Mol. Cell. Proteomics 11, M111.013987 (2012
32. Collins, B.C., et al. Quantifying protein interaction dynamics by SWATH mass spectrometry: application to the 14-3-3 system. Nat. Methods 10, 1246-1253 (2013
33. Nesvizhskii, A.I. Computational and informatics strategies for identification of specific protein interaction partners in affinity purification mass spectrometry experiments. Proteomics 12, 1639-1655 (2012
34. Choi, H., et al. SAINT: probabilistic scoring of affinity purification-mass spectrometry data. Nat. Methods 8, 70-73 (2011
35. Choi, H., Glatter, T., Gstaiger, M. & Nesvizhskii, A.I. SAINT-MS1: protein-protein interaction scoring using label-free intensity data in affinity purification-mass spectrometry experiments. J. Proteome Res. 11, 2619-2624 (2012
36. Chatr-Aryamontri, A., et al. The BioGRID interaction database: 2013 update. Nucleic Acids Res. 41, D816-D823 (2013
37. Jeronimo, C., et al. Systematic analysis of the protein interaction network for the human transcription machinery reveals the identity of the 7SK capping enzyme. Mol. Cell 27, 262-274 (2007
38. Prakash, A., et al. Hybrid data acquisition and processing strategies with increased throughput and selectivity: pSMART analysis for global qualitative and quantitative analysis. J. Proteome Res. 13, 5415-5430 (2014
39. MacLean, B., et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966-968 (2010
40. Chambers, M.C., et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat. Biotechnol. 30, 918-920 (2012
41. Tautenhahn, R., Bottcher, C. & Neumann, S. Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics 9, 504 (2008
42. Nesvizhskii, A.I., et al. Dynamic spectrum quality assessment and iterative computational analysis of shotgun proteomic data: toward more efficient identification of post-Translational modifications, sequence polymorphisms, and novel peptides. Mol. Cell. Proteomics 5, 652-670 (2006
43. Kryuchkov, F., Verano-Braga, T., Hansen, T.A., Sprenger, R.R. & Kjeldsen, F. Deconvolution of mixture spectra and increased throughput of peptide identification by utilization of intensified complementary ions formed in tandem mass spectrometry. J. Proteome Res. 12, 3362-3371 (2013
44. Deutsch, E.W., et al. A guided tour of the Trans-Proteomic Pipeline. Proteomics 10, 1150-1159 (2010
45. Tsou, C.C., et al. IDEAL-Q, an automated tool for label-free quantitation analysis using an efficient peptide alignment approach and spectral data validation. Mol. Cell. Proteomics 9, 131-144 (2010
46. Lam, H., Deutsch, E.W. & Aebersold, R. Artificial decoy spectral libraries for false discovery rate estimation in spectral library searching in proteomics. J. Proteome Res. 9, 605-610 (2010
47. Cox, J., Michalski, A. & Mann, M. Software lock mass by two-dimensional minimization of peptide mass errors. J. Am. Soc. Mass Spectrom. 22, 1373-1380 (2011
48. Barsnes, H., et al. compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics 12, 70 (2011
49. Escher, C., et al. Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics 12, 1111-1121 (2012
50. Vizcaíno, J.A., et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat. Biotechnol. 32, 223-226 (2014