Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

PeptideShaker enables reanalysis of MS-derived proteomics data sets

Nature Biotechnology volume 33, pages 22–24 (2015)Cite this article

Subjects

To the Editor:

Mass spectrometry (MS)-based proteomics is commonly used to identify and quantify the hundreds to thousands of proteins that are present in complex biological samples. Widespread data sharing via publicly accessible repositories, such as PRIDE1, has now become standard practice, aided by robust user-oriented tools for data submission2,3 and inspection4 and bolstered by the advent of the ProteomeXchange initiative5. Importantly, repository data sharing has enabled the first high-profile studies in which the repurposing of publicly available proteomics data has revealed new biological insights6,7.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: PeptideShaker data-analysis cycle.
Figure 2: The PeptideShaker overview tab, showing all proteins in the data set, along with the peptides and peptide-to-spectrum matches for the selected protein and peptide.

References

  1. Martens, L. et al. Proteomics 5, 3537–3545 (2005).

    Article  CAS  Google Scholar 

  2. Côté, R.G. et al. Mol. Cell. Proteomics 11, 1682–1689 (2012).

    Article  Google Scholar 

  3. Barsnes, H., Vizcaíno, J.A., Eidhammer, I. & Martens, L. Nat. Biotechnol. 27, 598–599 (2009).

    Article  CAS  Google Scholar 

  4. Wang, R. et al. Nat. Biotechnol. 30, 135–137 (2012).

    Article  Google Scholar 

  5. Vizcaíno, J.A. et al. Nat. Biotechnol. 32, 223–226 (2014).

    Article  Google Scholar 

  6. Matic, I., Ahel, I. & Hay, R.T. Nat. Methods 9, 771–772 (2012).

    Article  CAS  Google Scholar 

  7. Hahne, H., Moghaddas Gholami, A. & Kuster, B. Mol. Cell. Proteomics 11, 843–850 (2012).

    Article  CAS  Google Scholar 

  8. Editors. Nat. Biotechnol. 31, 857 (2013).

  9. Martin, S.F. et al. J. Proteomics 88, 41–46 (2013).

    Article  CAS  Google Scholar 

  10. Elias, J.E. & Gygi, S.P. Nat. Methods 4, 207–214 (2007).

    Article  CAS  Google Scholar 

  11. Shteynberg, D., Nesvizhskii, A.I., Moritz, R.L. & Deutsch, E.W. Mol. Cell. Proteomics 12, 2383–2393 (2013).

    Article  CAS  Google Scholar 

  12. Nesvizhskii, A.I. J. Proteomics 73, 2092–2123 (2010).

    Article  CAS  Google Scholar 

  13. Nesvizhskii, A.I. & Aebersold, R. Mol. Cell Proteomics 4, 1419–1440 (2005).

    Article  CAS  Google Scholar 

  14. Vaudel, M. et al. J. Proteome Res. 11, 5065–5071 (2012).

    Article  CAS  Google Scholar 

  15. Barsnes, H., Eidhammer, I. & Martens, L. Proteomics 11, 1181–1188 (2011).

    Article  CAS  Google Scholar 

  16. Paik, Y.K. et al. Nat. Biotechnol. 30, 221–223 (2012).

    Article  CAS  Google Scholar 

  17. Jones, A.R. et al. Mol. Cell. Proteomics 11, M111.014381 (2012).

    Article  Google Scholar 

  18. Goecks, J., Nekrutenko, A., Taylor, J. & Galaxy, T. Genome Biol. 11, R86 (2010).

    Article  Google Scholar 

  19. Vaudel, M., Barsnes, H., Berven, F.S., Sickmann, A. & Martens, L. Proteomics 11, 996–999 (2011).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

M.V., R.P.Z., J.M.B. and A.S. gratefully acknowledge the financial support by the Ministerium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen and by the Bundesministerium für Bildung und Forschung. L.M. acknowledges the support of Ghent University (Multidisciplinary Research Partnership “Bioinformatics: from nucleotides to networks”), the PRIME-XS project, grant agreement number 262067, and the 'ProteomeXchange' project, grant agreement number 260558, both funded by the European Union 7th Framework Program. H.B. is supported by the Research Council of Norway. The study was supported by the Kristian Gerhard Jebsen Foundation. The authors would like to thank the PRIDE team for help regarding the use of the PRIDE archive web services and for validation of the PRIDE export formats. Finally, our thanks to all PeptideShaker users for thorough testing of the software and for coming up with valuable suggestions for improvements.

Author information

Authors and Affiliations

  1. Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany

    Marc Vaudel, Julia M Burkhart, René P Zahedi & Albert Sickmann

  2. Department of Biomedicine, Proteomics Unit, University of Bergen, Bergen, Norway

    Marc Vaudel, Eystein Oveland, Frode S Berven & Harald Barsnes

  3. Department of Clinical Medicine, University of Bergen, Bergen, Norway

    Eystein Oveland

  4. Department of Clinical Medicine, The KG Jebsen Centre for MS Research, University of Bergen, Bergen, Norway

    Eystein Oveland & Frode S Berven

  5. Department of Neurology, The Norwegian Multiple Sclerosis Competence Centre, Haukeland University Hospital, Bergen, Norway

    Frode S Berven

  6. Department of Medical Protein Research, VIB, Ghent, Belgium

    Lennart Martens

  7. Department of Biochemistry, Ghent University, Ghent, Belgium

    Lennart Martens

  8. Computational Biology Unit, University of Bergen, Norway

    Harald Barsnes

Authors
  1. Marc Vaudel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julia M Burkhart
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. René P Zahedi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Eystein Oveland
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Frode S Berven
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Albert Sickmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lennart Martens
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Harald Barsnes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.V. and H.B. did all of the programming and participated in writing the manuscript. R.P.Z., J.M.B., E.O., F.S.B. and A.S. contributed ideas, performed testing and participated in writing the manuscript. L.M. supervised the programming, provided ideas and participated in writing the manuscript. All authors participated in the preparation of the manuscript.

Corresponding author

Correspondence to Lennart Martens.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Note

Supplementary Note 1 (PDF 4403 kb)

Supplementary Software

PeptideShaker source code as a zip file (ZIP 16668 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vaudel, M., Burkhart, J., Zahedi, R. et al. PeptideShaker enables reanalysis of MS-derived proteomics data sets. Nat Biotechnol 33, 22–24 (2015). https://doi.org/10.1038/nbt.3109

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.3109

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing