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      ProteomeXchange provides globally co-ordinated proteomics data submission and dissemination

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          Abstract

          To the Editor There is a growing trend towards public dissemination of proteomics data, which is facilitating the assessment, reuse, comparative analyses and extraction of new findings from published data 1, 2 . This process has been mainly driven by journal publication guidelines and funding agencies. However, there is a need for better integration of public repositories and coordinated sharing of all the pieces of information needed to represent a full mass spectrometry (MS)–based proteomics experiment. Your July 2009 editorial “Credit where credit is overdue” 3 exposed the situation in the proteomics field, where full data disclosure is still not common practise. Olsen and Mann 4 identified different levels of information in the typical experiment, starting from raw data and going through peptide identification and quantification, protein identifications and ratios and the resulting biological conclusions. All of these levels should be captured and properly annotated in public databases, using the existing MS proteomics repositories for the MS data (raw data, identification and quantification results) and metadata, whereas the resulting biological information should be integrated in protein knowledgebases, such as UniProt 5 . A recent editorial in Nature Methods 6 again highlighted the need for a stable repository for raw MS proteomics data. In this Correspondence, we report on the first implementation of the ProteomeXchange consortium, an integrated framework for submission and dissemination of MS-based proteomics data. Among the existing MS proteomics repositories with a broad target audience, the PRIDE (PRoteomics IDEntifications) database 7 (European Bioinformatics Institute, EBI, Cambridge, UK; http://www.ebi.ac.uk/pride) and PeptideAtlas 8 (Institute for Systems Biology, ISB, Seattle, USA; http://www.peptideatlas.org) are two of the most prominent. Both are mainly focused on tandem MS (MS/MS) data storage. Whereas PRIDE represents the information as originally analysed by the researcher (thus constituting a primary resource), data in PeptideAtlas are reprocessed through a common pipeline (the Trans-Proteomic Pipeline) to provide a uniformly analyzed view on the data with a focus on low protein false discovery rates (constituting a secondary resource). In addition, ISB has set up the first repository for SRM data, PASSEL 9 (PeptideAtlas SRM Experiment Library, http://www.peptideatlas.org/passel/). There are other resources dedicated to storing MS proteomics data, each of them with different focuses and functionalities, for instance GPMDB (where data are reprocessed using the search engine X!Tandem) 10 . At a higher abstraction level, resources like UniProt and neXtProt are integrating proteomics results into a wider context of functional annotation from many different sources, including antibody-based methods. Although most of the proteomics resources mentioned have existed for a long time, they have acted independently with limited coordination of their activities. As a result, data providers were unclear to which repository they should submit their dataset, and in what form, with choices ranging from full raw data to highly processed identifications and quantifications. In addition, no repository could store both raw data and results. Similar issues arose for data consumers, who could not always find the data supporting a protein modification in UniProt, or know whether a particular dataset from PRIDE had been integrated into PeptideAtlas. The ProteomeXchange (PX) consortium (http://www.proteomexchange.org) was formed in 2006 (ref. 11) to overcome these challenges, developing from a loose collaboration into an international consortium of major stakeholders in the domain, comprising, among others, primary (PRIDE, PASSEL) and secondary resources (PeptideAtlas, UniProt), proteomics bioinformaticians, investigators (including some involved in the HUPO Human Proteome Project), and representatives from journals regularly publishing proteomics data (Supplementary Notes, section 7). The aim of the ProteomeXchange consortium is to provide a common framework and infrastructure for the cooperation of proteomics resources by defining and implementing consistent, harmonised, user-friendly data deposition and exchange procedures among the major public proteomics repositories. ProteomeXchange provides unified data submission for multiple MS data types and delivers different ‘views’ of the deposited data, such as the raw data suitable for reprocessing, the author-generated identifications and highly filtered composite results in resources like UniProt, all linked by a universal shared identifier. Authors are able to cite the resulting ProteomeXchange accession number for datasets reported in their publications. As such, a dataset (with appropriate metadata) is becoming publishable per se and can be tracked if used by various consumers in different publications. Individual resources can join ProteomeXchange by implementing the ProteomeXchange data submission and dissemination guidelines, and metadata requirements. In the current version (http://www.proteomexchange.org/concept), the mandatory information comprises: (i) mass spectrometer output files (raw data, either in a binary format, or in a standard open format such as mzML); (ii) processed identification results (two submission modes are available, see below); and (iii) sufficient metadata to provide a suitable biological and technological background, including method information such as transition lists in the case of SRM data. Other types of information, such as peak list files (processed versions of mass spectra most often used in the identification process) and quantification results can also be provided. Two main MS proteomics workflows are now fully supported: tandem MS and SRM data (Fig. 1 and Supplementary Fig. 1). PRIDE acts as the initial submission point for MS/MS data, whereas PASSEL is the initial submission point for SRM data. It is expected that in most cases, one ProteomeXchange dataset will correspond to data from one publication, and it will be clearly linked to it. However, this concept is flexible and a mechanism for grouping different ProteomeXchange datasets is also available, for example for large-scale collaborative studies. At present, two different submission modes are available for MS/MS data: - ‘Complete submission’: this requires peptide and protein identification results to be fully supported and integrated in the receiving repository (PRIDE at present). The search engine output files (plus the associated spectra) must therefore first be converted to PRIDE XML or mzIdentML format (a process supported by several popular and user-friendly tools, Supplementary Notes, section 5). Complete submissions make the data fully available for querying, and thus maximise the potential for data re-use in MS. This in turn increases the visibility of the associated publication. A DOI (Digital Object Identifier) is assigned to each dataset, allowing formalized credit to be given to submitters and their principal investigators, through a citation index, as proposed in your editorial 3 . - ‘Partial submission’: For these submissions, peptide or protein identification results cannot be integrated in PRIDE because data converters and exporters to the supported formats are not yet available. In this case, search engine output files can be directly provided in their original format. Although partial submissions are searchable by their metadata, they are not fully searchable by results such as protein identifiers, and will not receive a DOI. However, partial submissions are important as they allow data from novel experimental approaches to be deposited into the ProteomeXchange resources, rather than having to reject these until the workflows have been mapped into a representation in PRIDE or another ProteomeXchange partner. For the submission of MS/MS datasets, a stand-alone, open-source Java tool has been made available, the ‘ProteomeXchange submission tool’ (http://www.proteomexchange.org/submission) (Supplementary Notes section 5, Supplementary Figs. 2–10). The tool allows interactive submission of small datasets as well as large- scale batch submissions. For SRM datasets, a web form (http://www.peptideatlas.org/submit) can be used for submission to PASSEL. Similar to the guidelines stated above for MS/MS datasets, PASSEL submissions require mass spectrometer output files, study metadata, peptide reagents, analysis result files and the actual SRM transition lists, the information that drives the instrument data acquisition. Once datasets are submitted, they are checked by a curator and then loaded into the main PASSEL database, which facilitates interactive exploration of the data and results. The submitted information and files can selectively be made available to journal editors and reviewers during manuscript peer review. Once the manuscript is accepted for publication or the submitter informs the receiving repository directly, the data will be publicly released (Fig. 1). At this point, the availability of the dataset, as well as basic metadata, will be disseminated through a public RSS feed (http://groups.google.com/group/proteomexchange/feed/rss_v2_0_msgs.xml). The RSS feed includes a link to an XML message (ProteomeXchange XML), which is created by the receiving repository (Supplementary Notes, section 3), and made available from ProteomeCentral, the portal for all public ProteomeXchange datasets (http://proteomecentral.proteomexchange.org) (Supplementary Notes, section 2). Repositories such as PeptideAtlas or GPMDB as well as any interested end users can subscribe to this RSS feed and trigger actions, including incorporation of the data into local resources, re-processing or biological analysis. This reprocessing is already occurring in practice. For example, two ProteomeXchange datasets (PXD000134 and PXD000157) have been used in the latest build of the human proteome in PeptideAtlas, and PXD000013 (ref. 12) was reprocessed and nominated as technical dataset of the year 2012 by GPMDB (http://www.thegpm.org/dsotw_2012.html - 201210071). ProteomeXchange started to accept regular submissions in June 2012. By the beginning of August 2013, 373 ProteomeXchange datasets have been submitted (consisting of 341 tandem MS and 32 SRM datasets, Fig. 2), a total of ~25 TB of data. The largest submission so far (currently still private) comprised 5 TB of data. For a current list of the publicly available datasets, see http://proteomecentral.proteomexchange.org/. In summary, ProteomeXchange provides an infrastructure for efficient and reliable public dissemination of proteomics data, supporting crucial validation, analysis and reuse. By providing and linking different interpretations of the data we aim to maximise dataset visibility as well as their potential benefit to different communities. Citability and traceability are addressed through the assignment of DOIs and a common identifier space. The consortium is open to the participation of additional resources (Supplementary Notes, Section 9). Although all repositories depend on continuous funding for continuous operation, the ProteomeXchange core repositories PRIDE and PeptideAtlas are well established, with first publications in 2005 (ref. 7,8), and have strong institutional backing (Supplementary Notes, section 8), ensuring that the data will remain reliably available for the foreseeable future. We are confident that the ProteomeXchange infrastructure will support the growing trend towards public availability of proteomics data, maximising its benefit to the scientific community through increased ease of access, greater ability to re-assess interpretations and extract further biological insight, and greater citation rates for the submitters. Supplementary Material 1

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          Most cited references 13

          • Record: found
          • Abstract: found
          • Article: not found

          Open source system for analyzing, validating, and storing protein identification data.

          This paper describes an open-source system for analyzing, storing, and validating proteomics information derived from tandem mass spectrometry. It is based on a combination of data analysis servers, a user interface, and a relational database. The database was designed to store the minimum amount of information necessary to search and retrieve data obtained from the publicly available data analysis servers. Collectively, this system was referred to as the Global Proteome Machine (GPM). The components of the system have been made available as open source development projects. A publicly available system has been established, comprised of a group of data analysis servers and one main database server.
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            • Record: found
            • Abstract: found
            • Article: not found

            PRIDE: the proteomics identifications database.

            The advent of high-throughput proteomics has enabled the identification of ever increasing numbers of proteins. Correspondingly, the number of publications centered on these protein identifications has increased dramatically. With the first results of the HUPO Plasma Proteome Project being analyzed and many other large-scale proteomics projects about to disseminate their data, this trend is not likely to flatten out any time soon. However, the publication mechanism of these identified proteins has lagged behind in technical terms. Often very long lists of identifications are either published directly with the article, resulting in both a voluminous and rather tedious read, or are included on the publisher's website as supplementary information. In either case, these lists are typically only provided as portable document format documents with a custom-made layout, making it practically impossible for computer programs to interpret them, let alone efficiently query them. Here we propose the proteomics identifications (PRIDE) database (http://www.ebi.ac.uk/pride) as a means to finally turn publicly available data into publicly accessible data. PRIDE offers a web-based query interface, a user-friendly data upload facility, and a documented application programming interface for direct computational access. The complete PRIDE database, source code, data, and support tools are freely available for web access or download and local installation.
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              • Record: found
              • Abstract: found
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              PASSEL: the PeptideAtlas SRMexperiment library.

              Public repositories for proteomics data have accelerated proteomics research by enabling more efficient cross-analyses of datasets, supporting the creation of protein and peptide compendia of experimental results, supporting the development and testing of new software tools, and facilitating the manuscript review process. The repositories available to date have been designed to accommodate either shotgun experiments or generic proteomic data files. Here, we describe a new kind of proteomic data repository for the collection and representation of data from selected reaction monitoring (SRM) measurements. The PeptideAtlas SRM Experiment Library (PASSEL) allows researchers to easily submit proteomic data sets generated by SRM. The raw data are automatically processed in a uniform manner and the results are stored in a database, where they may be downloaded or browsed via a web interface that includes a chromatogram viewer. PASSELenables cross-analysis of SRMdata, supports optimization of SRMdata collection, and facilitates the review process of SRMdata. Further, PASSELwill help in the assessment of proteotypic peptide performance in a wide array of samples containing the same peptide, as well as across multiple experimental protocols. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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                Author and article information

                Contributors
                Journal
                9604648
                20305
                Nat Biotechnol
                Nat. Biotechnol.
                Nature biotechnology
                1087-0156
                1546-1696
                5 February 2014
                10 March 2014
                10 September 2014
                : 32
                : 3
                : 223-226
                Affiliations
                [1 ]European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
                [2 ]Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109, USA
                [3 ]Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, CA, USA
                [4 ]Swiss-Prot Group, SIB Swiss Institute of Bioinformatics, 1 Rue Michel-Servet, 1211 Geneva 4, Switzerland
                [5 ]University of Lausanne, Lausanne, Switzerland and Center for Integrative Genomics, University of Lausanne, 1005 Lausanne, Switzerland
                [6 ]Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
                [7 ]Medizinisches Proteom-Center, Ruhr-Universität Bochum, Universitätsstr. 150, D-44801 Bochum, Germany
                [8 ]Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QR, United Kingdom
                [9 ]Integromics SL, Santiago Grisolia, 2, Tres Cantos, 28760, Madrid, Spain
                [10 ]Department of Pharmaceutical Chemistry, University of California San Francisco, CA 94158, USA
                [11 ]Wiley-VCH Verlag, Boschstraße 12, 69469 Weinheim, Germany
                [12 ]ProteoRed-ISCIII, National National Center for Biotechnology-CSIC, Madrid, Spain
                [13 ]Center for Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109-2218, USA
                [14 ]Department of Medical Protein Research, VIB, A. Baertsoenkaai 3 B-9000 Ghent, Belgium
                [15 ]Department of Biochemistry, Ghent University, A. Baertsenkaai 3 B-9000 Ghent, Belgium
                [16 ]Institute of Integrative Biology, University of Liverpool, UK, L697ZB
                Author notes
                [17]

                Both authors contributed equally to the manuscript.

                Article
                NIHMS549897
                10.1038/nbt.2839
                3986813
                24727771

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