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. 2020 Jan 8;48(D1):D1145-D1152.
doi: 10.1093/nar/gkz984.

The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics

Eric W Deutsch  1 , Nuno Bandeira  2   3   4 , Vagisha Sharma  5 , Yasset Perez-Riverol  6 , Jeremy J Carver  2   3   4 , Deepti J Kundu  6 , David García-Seisdedos  6 , Andrew F Jarnuczak  6 , Suresh Hewapathirana  6 , Benjamin S Pullman  2   3   4 , Julie Wertz  2   3   4 , Zhi Sun  1 , Shin Kawano  7   8 , Shujiro Okuda  9 , Yu Watanabe  9 , Henning Hermjakob  6   10 , Brendan MacLean  5 , Michael J MacCoss  5 , Yunping Zhu  10 , Yasushi Ishihama  11 , Juan A Vizcaíno  6
Affiliations

The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics

Eric W Deutsch et al. Nucleic Acids Res. .

Abstract

The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) has standardized data submission and dissemination of mass spectrometry proteomics data worldwide since 2012. In this paper, we describe the main developments since the previous update manuscript was published in Nucleic Acids Research in 2017. Since then, in addition to the four PX existing members at the time (PRIDE, PeptideAtlas including the PASSEL resource, MassIVE and jPOST), two new resources have joined PX: iProX (China) and Panorama Public (USA). We first describe the updated submission guidelines, now expanded to include six members. Next, with current data submission statistics, we demonstrate that the proteomics field is now actively embracing public open data policies. At the end of June 2019, more than 14 100 datasets had been submitted to PX resources since 2012, and from those, more than 9 500 in just the last three years. In parallel, an unprecedented increase of data re-use activities in the field, including 'big data' approaches, is enabling novel research and new data resources. At last, we also outline some of our future plans for the coming years.

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Figures

Figure 1.
Figure 1.
Overview figure including the current ProteomeXchange data workflow and additional bioinformatics resources that are currently re-using proteomics data.
Figure 2.
Figure 2.
Number of submitted datasets per month to PX resources, ranging from May 2012 to June 2019.
Figure 3.
Figure 3.
Summary of metrics for datasets available in all ProteomeXchange resources (as of 30 June 2019).
See this image and copyright information in PMC

References

    1. Vizcaino J.A., Deutsch E.W., Wang R., Csordas A., Reisinger F., Rios D., Dianes J.A., Sun Z., Farrah T., Bandeira N. et al. .. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat. Biotechnol. 2014; 32:223–226. - PMC - PubMed
    1. Deutsch E.W., Csordas A., Sun Z., Jarnuczak A., Perez-Riverol Y., Ternent T., Campbell D.S., Bernal-Llinares M., Okuda S., Kawano S. et al. .. The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public data deposition. Nucleic Acids Res. 2017; 45:D1100–D1106. - PMC - PubMed
    1. Perez-Riverol Y., Csordas A., Bai J., Bernal-Llinares M., Hewapathirana S., Kundu D.J., Inuganti A., Griss J., Mayer G., Eisenacher M. et al. .. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 2019; 47:D442–D450. - PMC - PubMed
    1. Farrah T., Deutsch E.W., Kreisberg R., Sun Z., Campbell D.S., Mendoza L., Kusebauch U., Brusniak M.Y., Huttenhain R., Schiess R. et al. .. PASSEL: the PeptideAtlas SRMexperiment library. Proteomics. 2012; 12:1170–1175. - PMC - PubMed
    1. Deutsch E.W., Lam H., Aebersold R.. PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows. EMBO Rep. 2008; 9:429–434. - PMC - PubMed

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