Brief Communication | Published:

Combining quantitative proteomics data processing workflows for greater sensitivity

Nature Methods volume 8, pages 481483 (2011) | Download Citation

Abstract

We here describe a normalization method to combine quantitative proteomics data. By merging the output of two popular quantification software packages, we obtained a 20% increase (on average) in the number of quantified human proteins without suffering from a loss of quality. Our integrative workflow is freely available through our user-friendly, open-source Rover software (http://compomics-rover.googlecode.com/).

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Acknowledgements

C.V.H. is supported by a grant of the Research Foundation–Flanders (project 3G003908). We thank B. Ghesquière, F. Impens and E. Timmerman for providing prepublication access during algorithm development to their now published data. We acknowledge the support of Ghent University (Multidisciplinary Research Partnership “Bioinformatics: from nucleotides to networks”) and EU 7th Framework Programme (contract 262067-PRIME-XS). K.G. and J.V. acknowledge funding from the Fund for Scientific Research–Flanders (Belgium) (project G.0042.07), the Concerted Research Actions (project BOF07/GOA/012) from Ghent University and the Interuniversity Attraction Poles (IUAP06).

Author information

Affiliations

  1. Department of Medical Protein Research, Vlaams Instituut voor Biotechnologie (VIB), Ghent, Belgium.

    • Niklaas Colaert
    • , Sven Degroeve
    • , An Staes
    • , Joël Vandekerckhove
    • , Kris Gevaert
    •  & Lennart Martens
  2. Department of Biochemistry, Ghent University, Ghent, Belgium.

    • Niklaas Colaert
    • , Sven Degroeve
    • , An Staes
    • , Joël Vandekerckhove
    • , Kris Gevaert
    •  & Lennart Martens
  3. Department of Management Information and Operations Management, Ghent University, Ghent, Belgium.

    • Christophe Van Huele

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Contributions

N.C. developed the combination algorithm and wrote the first draft of the manuscript. C.V.H. contributed to algorithm development and to manuscript writing. S.D. contributed to algorithm development and manuscript writing. A.S. assisted with data processing and manuscript writing. J.V. and K.G. supervised part of the work and contributed to manuscript writing. L.M. supervised the work, contributed to algorithm development and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Lennart Martens.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–3, Supplementary Table 1–2, Supplementary Data

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DOI

https://doi.org/10.1038/nmeth.1604

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