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The MaxQuant computational platform for mass spectrometry-based shotgun proteomics

Tyanova, Stefka, Temu, Tikira, Cox, Juergen·2016·Nature Protocols

DOI 10.1038/nprot.2016.136

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MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Self-citation
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 2×
“44| Set the minimum FDR at which a protein group should be accepted.”
Background
Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ
Cox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.031591 · Cited by 5,180
Self-citation
Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401
Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
MultiNotch MS3 Enables Accurate, Sensitive, and Multiplexed Detection of Differential Expression across Cancer Cell Line Proteomes
McAlister, G. C., Nusinow, D. P., Jedrychowski, M. P., Wühr, M., Huttlin, E. L., Erickson, B. K., Rad, R., Haas, W., & Gygi, S. P. (2014) · Analytical Chemistry · doi:10.1021/ac502040v · Cited by 1,263
Comparative Proteomic Analysis of Eleven Common Cell Lines Reveals Ubiquitous but Varying Expression of Most Proteins
Geiger, T., Wehner, A., Schaab, C., Cox, J., & Mann, M. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.014050 · Cited by 797
Self-citation
A “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards
Wiśniewski, J. R., Hein, M. Y., Cox, J., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.037309 · Cited by 690
Self-citation
More than 100,000 Detectable Peptide Species Elute in Single Shotgun Proteomics Runs but the Majority is Inaccessible to Data-Dependent LC−MS/MS
Michalski, A., Cox, J., & Mann, M. (2011) · Journal of Proteome Research · doi:10.1021/pr101060v · Cited by 685
Self-citation
Increasing the Multiplexing Capacity of TMTs Using Reporter Ion Isotopologues with Isobaric Masses
McAlister, G. C., Huttlin, E. L., Haas, W., Ting, L., Jedrychowski, M. P., Rogers, J. C., Kuhn, K., Pike, I., Grothe, R. A., Blethrow, J. D., et al. (2012) · Analytical Chemistry · doi:10.1021/ac301572t · Cited by 605

Show all 14 references

Research works printed but not linked: 31

Hein, M.Y., Sharma, K., Cox, J. & Mann, M. in Handbook of Systems Biology (eds. Walhout, A.J.M., Vidal, M. & Dekker, J.) 3–25 (Academic Press, San Diego, CA, 2013). · DOI
Cox, J. & Mann, M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu. Rev. Biochem. 80, 273–299 (2011). · DOI · Paper page
Neuhauser, N., Michalski, A., Cox, J. & Mann, M. Expert system for computer-assisted annotation of MS/MS spectra. Mol. Cell. Proteomics 11, 1500–1509 (2012). · DOI
Tyanova, S. et al. Visualization of LC–MS/MS proteomics data in MaxQuant. Proteomics 15, 1453–1456 (2015). · DOI · Paper page
Cox, J. & Mann, M. Computational principles of determining and improving mass precision and accuracy for proteome measurements in an Orbitrap. J. Am. Soc. Mass Spectrom. 20, 1477–1485 (2009). · DOI
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). · DOI
Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011). · DOI
Olsen, J.V. et al. Higher-energy C-trap dissociation for peptide modification analysis. Nat. Methods 4, 709–712 (2007). · DOI · Paper page
Michalski, A., Neuhauser, N., Cox, J. & Mann, M. A systematic investigation into the nature of tryptic HCD spectra. J. Proteome Res. 11, 5479–5491 (2012). · DOI
Mikesh, L.M. et al. The utility of ETD mass spectrometry in proteomic analysis. Biochim. Biophys. Acta 1764, 1811–1822 (2006). · DOI · Paper page
Frese, C.K. et al. Unambiguous phosphosite localization using electron-transfer/higher-energy collision dissociation (EThcD). J. Proteome Res. 12, 1520–1525 (2013). · DOI
Spivak, M., Weston, J., Bottou, L., Kall, L. & Noble, W.S. Improvements to the percolator algorithm for peptide identification from shotgun proteomics data sets. J. Proteome Res. 8, 3737–3745 (2009). · DOI · Paper page
Tyanova, S., Mann, M. & Cox, J. MaxQuant for in-depth analysis of large SILAC datasets. Methods Mol. Biol. 1188, 351–364 (2014). · DOI
Boersema, P.J., Raijmakers, R., Lemeer, S., Mohammed, S. & Heck, A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484–494 (2009). · DOI · Paper page
Thompson, A. et al. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75, 1895–1904 (2003). · DOI · Paper page
Imamura, H., Wakabayashi, M. & Ishihama, Y. Analytical strategies for shotgun phosphoproteomics: status and prospects. Semin. Cell Dev. Biol. 23, 836–842 (2012). · DOI
Zhou, H. et al. Enhancing the identification of phosphopeptides from putative basophilic kinase substrates using Ti (IV) based IMAC enrichment. Mol. Cell. Proteomics 10, M110 006452 (2011). · DOI
Sharma, K. et al. Ultradeep human phosphoproteome reveals a distinct regulatory nature of tyr and ser/thr-based signaling. Cell Rep. 8, 1583–1594 (2014). · DOI · Paper page
Savitski, M.M., Nielsen, M.L. & Zubarev, R.A. ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures. Mol. Cell. Proteomics 5, 935–948 (2006). · DOI
Chick, J.M. et al. A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides. Nat. Biotechnol. 33, 743–749 (2015). · DOI · Paper page
Neuhauser, N. et al. High performance computational analysis of large-scale proteome data sets to assess incremental contribution to coverage of the human genome. J. Proteome Res. 12, 2858–2868 (2013). · DOI
Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 9, 731–740 (2016). · DOI · Paper page
Deeb, S.J. et al. Machine learning based classification of diffuse large B-cell lymphoma patients by their protein expression profiles. Mol. Cell. Proteomics 14, 2947–2960 (2015). · DOI
Cox, J. & Mann, M. 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data. BMC Bioinformatics 13 (Suppl. 16), S12 (2012). · DOI · Paper page
Robles, M.S., Cox, J. & Mann, M. In-vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism. PLoS Genet. 10, e1004047 (2014). · DOI · Paper page
Geiger, T., Cox, J. & Mann, M. Proteomics on an Orbitrap benchtop mass spectrometer using all-ion fragmentation. Mol. Cell. Proteomics 9, 2252–2261 (2010). · DOI · Paper page
MacLean, B. et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968 (2010). · DOI · Paper page
Keshishian, H. et al. Multiplexed, quantitative workflow for sensitive biomarker discovery in plasma yields novel candidates for early myocardial injury. Mol. Cell. Proteomics 14, 2375–2393 (2015). · DOI
Chen, Z.A., Fischer, L., Cox, J. & Rappsilber, J. Quantitative cross-linking/mass spectrometry using isotope-labeled cross-linkers and MaxQuant. Mol. Cell. Proteomics (2016). · DOI
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). · DOI · Paper page
Olsen, J.V. et al. Quantitative phosphoproteomics reveals widespread full phosphorylation site occupancy during mitosis. Sci. Signal. 3, ra3 (2010). · DOI · Paper page

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Self-citation

Authors: Tyanova, S., Temu, T., & Cox, J.
Venue: Nature Protocols
Publisher: Springer Science and Business Media LLC
Published: 2016-10-27
Volume: 11
Issue: 12
Pages: 2301-2319
ISSN: 1750-2799 (ISSN-L)
1754-2189
DOI: 10.1038/nprot.2016.136
OpenAlex: W2544360569
Cited by: 4,797
References: 14
FWCI: 86.78
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)

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