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Sci. Signal., 15 February 2011
Vol. 4, Issue 160, p. pe7
[DOI: 10.1126/scisignal.2001839]

PERSPECTIVES

Effective Representation and Storage of Mass Spectrometry–Based Proteomic Data Sets for the Scientific Community

Jesper V. Olsen1* and Matthias Mann1,2*

1 Center for Protein Research, University of Copenhagen, Faculty of Health Sciences, Blegdamsvej 3b, DK-2200 Copenhagen N, Denmark.
2 Department for Proteomics and Cell Signaling, Max Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

Abstract: Mass spectrometry–based proteomics has emerged as a technology of choice for global analysis of cell signaling networks. However, reporting and sharing of MS data are often haphazard, limiting the usefulness of proteomics to the signaling community. We argue that raw data should always be provided with proteomics studies together with detailed peptide and protein identification and quantification information. Statistical criteria for peptide identification and their posttranslational modifications have largely been established for individual projects. However, the current practice of indiscriminately incorporating these individual results into databases such as UniProt is problematic. Because of the vast differences in underlying data quality, we advocate a differentiated annotation of data by level of reliability. Requirements for the reporting of quantitative data are being developed, but there are few mechanisms for community-wide sharing of these data.

* E-mail: jesper.olsen{at}cpr.ku.dk (J.V.O.); mmann{at}biochem.mpg.de (M.M.)

Citation: J. V. Olsen, M. Mann, Effective Representation and Storage of Mass Spectrometry–Based Proteomic Data Sets for the Scientific Community. Sci. Signal. 4, pe7 (2011).

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THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES:
Analysis of High Accuracy, Quantitative Proteomics Data in the MaxQB Database.
C. Schaab, T. Geiger, G. Stoehr, J. Cox, and M. Mann (2012)
Mol. Cell. Proteomics 11, M111.014068
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