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A cross-platform toolkit for mass spectrometry and proteomics

Nature Biotechnology volume 30, pages 918–920 (2012)Cite this article

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To the Editor:

Mass spectrometry–based proteomics has become an important component of biological research. Numerous proteomics methods have been developed to identify and quantify the proteins in biological and clinical samples1, identify pathways affected by endogenous and exogenous perturbations2 and characterize protein complexes3. Despite successes, the interpretation of vast proteomics data sets remains a challenge. There have been several calls for improvements and standardization of proteomics data analysis frameworks, as well as for an application-programming interface for proteomics data access4,5. In response, we present here the ProteoWizard Toolkit, a robust set of open-source, software libraries and applications designed to facilitate proteomics research. The libraries implement the first-ever, noncommercial, unified data access interface for proteomics, bridging field-standard open formats and all common vendor formats. In addition, diverse software classes enable rapid development of vendor-agnostic proteomics software. Additionally, ProteoWizard projects and applications, building upon the core libraries, are becoming standard tools for enabling significant proteomics inquiries.

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Figure 1: Design of ProteoWizard.

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Acknowledgements

This work is supported by the Wunderkinder Foundation, Redstone Family Foundation and Canary Foundation, and the National Cancer Institute and US National Institutes of Health grants and contracts P41 RR011823, CCNE-TR 5U54CA119367, CCNE-T 1U54CA151459, PSOC-MCSTART 5U54CA143907, R01CA126218 and U24CA126479. R.L.M. and C.P. have been supported by National Science Foundation MRI grant No. 0923536. L.G. has been supported by the European Union 7th Framework Program PRIME-XS project, grant agreement number 262067. The authors also thank the ProteoWizard developer community and TPP developer community for their contributions to the project and manuscript.

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Author notes

  1. Matthew C Chambers, Brendan Maclean and Robert Burke: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA

    Matthew C Chambers & David L Tabb

  2. Department of Genome Sciences, University of Washington, Seattle, Washington, USA

    Brendan Maclean, Jarrett Egertson, Nicholas Shulman, Barbara Frewen, Tahmina A Baker & Michael MacCoss

  3. Center for Applied Molecular Medicine, University of Southern California, Los Angeles, California, USA

    Robert Burke, Daniel L Ruderman, Katherine Hoff, Darren Kessner, Lisa Flashner, Kian Kani, Jonathan E Katz, David B Agus & Parag Mallick

  4. Canary Center for Cancer Early Detection, Stanford University, Stanford, California, USA

    Dario Amodei & Parag Mallick

  5. Department of Stress & Developmental Biology, Leibniz Institute for Plant Biochemistry, Halle (Saale), Germany

    Steffen Neumann

  6. Proteomics Services, Cambridge Centre for Proteomics, Cambridge, England

    Laurent Gatto

  7. Genome Biology, EMBL Heidelberg, Germany

    Bernd Fischer

  8. Insilicos, Seattle, Washington, USA

    Brian Pratt & Natalie Tasman

  9. Institute for Systems Biology, Seattle, Washington, USA

    Mi-Youn Brusniak, Christopher Paulse, Eric W Deutsch & Robert L Moritz

  10. Matrix Science, Boston, Massachusetts, USA

    David Creasy

  11. USC Stevens Institute for Innovation, University of Southern California, Los Angeles, California, USA

    Chris Moulding & Krisztina Holly

  12. AB SCIEX, Foster City, California, USA

    Sean L Seymour, Lydia M Nuwaysir & Brent Lefebvre

  13. Agilent Technologies, Santa Clara, California, USA

    Frank Kuhlmann & Joe Roark

  14. Bruker Daltonik GmbH, Bremen, Germany

    Paape Rainer & Suckau Detlev

  15. Thermo Fisher Scientific, San Jose, California, USA

    Tina Hemenway & Andreas Huhmer

  16. Waters Corporation, Manchester, UK

    James Langridge

  17. LabKey Software, Seattle, Washington, USA

    Brian Connolly, Trey Chadick & Josh Eckels

Authors
  1. Matthew C Chambers
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  2. Brendan Maclean
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  7. Laurent Gatto
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  10. Jarrett Egertson
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  18. Christopher Paulse
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  20. Lisa Flashner
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  21. Kian Kani
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  22. Chris Moulding
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  23. Sean L Seymour
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  24. Lydia M Nuwaysir
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  26. Frank Kuhlmann
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  27. Joe Roark
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  28. Paape Rainer
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  29. Suckau Detlev
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  30. Tina Hemenway
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  31. Andreas Huhmer
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  32. James Langridge
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  33. Brian Connolly
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  34. Trey Chadick
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  35. Krisztina Holly
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  36. Josh Eckels
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  37. Eric W Deutsch
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  38. Robert L Moritz
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  39. Jonathan E Katz
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  40. David B Agus
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  41. Michael MacCoss
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  42. David L Tabb
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  43. Parag Mallick
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Corresponding author

Correspondence to Parag Mallick.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Text 1–3, Supplementary Examples 1–5 and Supplementary Tables 1–4 (PDF 1272 kb)

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Chambers, M., Maclean, B., Burke, R. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol 30, 918–920 (2012). https://doi.org/10.1038/nbt.2377

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