1
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Saha D, Iannuccelli M, Brun C, Zanzoni A, Licata L. The Intricacy of the Viral-Human Protein Interaction Networks: Resources, Data, and Analyses. Front Microbiol 2022; 13:849781. [PMID: 35531299 PMCID: PMC9069133 DOI: 10.3389/fmicb.2022.849781] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/11/2022] [Indexed: 11/18/2022] Open
Abstract
Viral infections are one of the major causes of human diseases that cause yearly millions of deaths and seriously threaten global health, as we have experienced with the COVID-19 pandemic. Numerous approaches have been adopted to understand viral diseases and develop pharmacological treatments. Among them, the study of virus-host protein-protein interactions is a powerful strategy to comprehend the molecular mechanisms employed by the virus to infect the host cells and to interact with their components. Experimental protein-protein interactions described in the scientific literature have been systematically captured into several molecular interaction databases. These data are organized in structured formats and can be easily downloaded by users to perform further bioinformatic and network studies. Network analysis of available virus-host interactomes allow us to understand how the host interactome is perturbed upon viral infection and what are the key host proteins targeted by the virus and the main cellular pathways that are subverted. In this review, we give an overview of publicly available viral-human protein-protein interactions resources and the community standards, curation rules and adopted ontologies. A description of the main virus-human interactome available is provided, together with the main network analyses that have been performed. We finally discuss the main limitations and future challenges to assess the quality and reliability of protein-protein interaction datasets and resources.
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Affiliation(s)
- Deeya Saha
- Aix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France
| | | | - Christine Brun
- Aix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France
- CNRS, Marseille, France
| | - Andreas Zanzoni
- Aix-Marseille Univ., Inserm, TAGC, UMR_S1090, Marseille, France
- *Correspondence: Andreas Zanzoni,
| | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
- Luana Licata,
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2
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Strömert P, Hunold J, Castro A, Neumann S, Koepler O. Ontologies4Chem: the landscape of ontologies in chemistry. PURE APPL CHEM 2022. [DOI: 10.1515/pac-2021-2007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
For a long time, databases such as CAS, Reaxys, PubChem or ChemSpider mostly rely on unique numerical identifiers or chemical structure identifiers like InChI, SMILES or others to link data across heterogeneous data sources. The retrospective processing of information and fragmented data from text publications to maintain these databases is a cumbersome process. Ontologies are a holistic approach to semantically describe data, information and knowledge of a domain. They provide terms, relations and logic to semantically annotate and link data building knowledge graphs. The application of standard taxonomies and vocabularies from the very beginning of data generation and along research workflows in electronic lab notebooks (ELNs), software tools, and their final publication in data repositories create FAIR data straightforwardly. Thus a proper semantic description of an investigation and the why, how, where, when, and by whom data was produced in conjunction with the description and representation of research data is a natural outcome in contrast to the retrospective processing of research publications as we know it. In this work we provide an overview of ontologies in chemistry suitable to represent concepts of research and research data. These ontologies are evaluated against several criteria derived from the FAIR data principles and their possible application in the digitisation of research data management workflows.
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Affiliation(s)
- Philip Strömert
- TIB – Leibniz Information Centre for Science and Technology , Welfengarten 1 B, 30167 Hannover , Germany
| | - Johannes Hunold
- TIB – Leibniz Information Centre for Science and Technology , Welfengarten 1 B, 30167 Hannover , Germany
| | - André Castro
- TIB – Leibniz Information Centre for Science and Technology , Welfengarten 1 B, 30167 Hannover , Germany
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry , Weinberg 3 , 06120 Halle , Germany
| | - Oliver Koepler
- TIB – Leibniz Information Centre for Science and Technology , Welfengarten 1 B, 30167 Hannover , Germany
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3
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Porras P, Orchard S, Licata L. IMEx Databases: Displaying Molecular Interactions into a Single, Standards-Compliant Dataset. Methods Mol Biol 2022; 2449:27-42. [PMID: 35507258 DOI: 10.1007/978-1-0716-2095-3_2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Molecular interaction databases aim to systematically capture and organize the experimental interaction information described in the scientific literature. These data can then be used to perform network analysis, to assign putative roles to uncharacterized proteins and to investigate their involvement in cellular pathways.This chapter gives a brief overview of publicly available molecular interaction databases and focuses on the members of the IMEx Consortium, on their curation policies and standard data formats. All of the goals achieved by IMEx databases over the last 15 years, the data types provided and the many different ways in which such data can be utilized by the research community, are described in detail. The IMEx databases curate molecular interaction data to the highest caliber, following a detailed curation model and supplying rich metadata by employing common curation rules and harmonized standards. The IMEx Consortium provides comprehensively annotated molecular interaction data integrated into a single, non-redundant, open access dataset.
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Affiliation(s)
- Pablo Porras
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sandra Orchard
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK
| | - Luana Licata
- Department of Biology, University of Rome Tor Vergata, Rome, Italy.
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4
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Calderone A, Iannuccelli M, Peluso D, Licata L. Using the MINT Database to Search Protein Interactions. ACTA ACUST UNITED AC 2021; 69:e93. [PMID: 31945268 DOI: 10.1002/cpbi.93] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The Molecular INTeractions Database (MINT) is a public database designed to store information about protein interactions. Protein interactions are extracted from scientific literature and annotated in the database by expert curators. Currently (October 2019), MINT contains information on more than 26,000 proteins and more than 131,600 interactions in over 30 model organisms. This article provides protocols for searching MINT over the Internet, using the new MINT Web Page. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Searching MINT over the internet Alternate Protocol: MINT visualizer Basic Protocol 2: Submitting interaction data.
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5
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Toward Increased Reliability, Transparency, and Accessibility in Cross-linking Mass Spectrometry. Structure 2020; 28:1259-1268. [PMID: 33065067 DOI: 10.1016/j.str.2020.09.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 09/02/2020] [Accepted: 09/24/2020] [Indexed: 01/09/2023]
Abstract
Cross-linking mass spectrometry (MS) has substantially matured as a method over the past 2 decades through parallel development in multiple labs, demonstrating its applicability to protein structure determination, conformation analysis, and mapping protein interactions in complex mixtures. Cross-linking MS has become a much-appreciated and routinely applied tool, especially in structural biology. Therefore, it is timely that the community commits to the development of methodological and reporting standards. This white paper builds on an open process comprising a number of events at community conferences since 2015 and identifies aspects of Cross-linking MS for which guidelines should be developed as part of a Cross-linking MS standards initiative.
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6
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Informed Use of Protein-Protein Interaction Data: A Focus on the Integrated Interactions Database (IID). Methods Mol Biol 2020; 2074:125-134. [PMID: 31583635 DOI: 10.1007/978-1-4939-9873-9_10] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Protein-protein interaction data is fundamental in molecular biology, and numerous online databases provide access to this data. However, the huge quantity, complexity, and variety of PPI data can be overwhelming, and rather than helping to address research problems, the data may add to their complexity and reduce interpretability. This protocol focuses on solutions for some of the main challenges of using PPI data, including accessing data, ensuring relevance by integrating useful annotations, and improving interpretability. While the issues are generic, we highlight how to perform such operations using Integrated Interactions Database (IID; http://ophid.utoronto.ca/iid ).
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7
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Hoffmann N, Rein J, Sachsenberg T, Hartler J, Haug K, Mayer G, Alka O, Dayalan S, Pearce JTM, Rocca-Serra P, Qi D, Eisenacher M, Perez-Riverol Y, Vizcaíno JA, Salek RM, Neumann S, Jones AR. mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics. Anal Chem 2019; 91:3302-3310. [PMID: 30688441 PMCID: PMC6660005 DOI: 10.1021/acs.analchem.8b04310] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 01/28/2019] [Indexed: 12/29/2022]
Abstract
Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.
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Affiliation(s)
- Nils Hoffmann
- Leibniz-Institut
für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Straße 6b, 44227 Dortmund, Germany
| | - Joel Rein
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom
| | - Timo Sachsenberg
- Applied Bioinformatics
Group, Center for Bioinformatics, University
of Tübingen, Sand
14, 72076 Tübingen, Germany
| | - Jürgen Hartler
- Institute of Computational Biotechnology, Graz University of Technology, Petersgasse 14, 8010 Graz, Austria
- Center
for Explorative Lipidomics, BioTechMed-Graz, 8010 Graz, Austria
| | - Kenneth Haug
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Gerhard Mayer
- Medizinisches Proteom Center (MPC), Ruhr-Universität
Bochum, Universitätsstraße
150, D-44801 Bochum, Germany
| | - Oliver Alka
- Applied Bioinformatics
Group, Center for Bioinformatics, University
of Tübingen, Sand
14, 72076 Tübingen, Germany
| | - Saravanan Dayalan
- Metabolomics Australia, The University
of Melbourne, Parkville, Victoria 3010, Australia
| | - Jake T. M. Pearce
- MRC-NIHR National Phenome Centre, Department of Surgery & Cancer, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philippe Rocca-Serra
- University of Oxford, e-Research Centre, 7 Keble Road, Oxford OX1
3QG, United Kingdom
| | - Da Qi
- BGI-Shenzhen, Shenzhen, 518083, People’s Republic of China
- Institute
of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
| | - Martin Eisenacher
- Medizinisches Proteom Center (MPC), Ruhr-Universität
Bochum, Universitätsstraße
150, D-44801 Bochum, Germany
| | - Yasset Perez-Riverol
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Reza M. Salek
- International Agency for Research on Cancer, 150 cours Albert Thomas, 69008 Lyon, France
| | - Steffen Neumann
- Department
of Stress and Developmental Biology, Leibniz
Institute of Plant Biochemistry, 06120 Halle, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig Deutscher, Platz
5e, 04103 Leipzig, Germany
| | - Andrew R. Jones
- Institute
of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, United Kingdom
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8
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Race AM, Römpp A. Error-Free Data Visualization and Processing through imzML and mzML Validation. Anal Chem 2018; 90:13378-13384. [PMID: 30220203 DOI: 10.1021/acs.analchem.8b03059] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Open data formats are key to facilitating data processing, sharing, and integration. The imzML format ( http://imzml.org/ ) has drastically improved these aspects of mass spectrometry imaging data. Efficient processing of data depends on data sets which are consistent and adhere to the specifications; however, this is not always the case. Here we present a validation tool for data stored in both imzML and the HUPO-PSI mass spectrometery counterpart, mzML, to identify any deviations from the published (i)mzML standard which could cause issues for the user when visualizing or processing data. The tool is released in two forms, a graphical user interface (GUI) for ease of use, and a command line version to fit into existing workflows and pipelines. When certain known issues are encountered, such as the presence of negative values for the location of the binary data, the validator resolves the issue automatically upon saving. The GUI version of the validator also allows editing of the metadata included within the (i)mzML files in order to resolve inconsistencies. We also present a means of performing conditional validation on the metadata within (i)mzML files, where user-defined rules are validated against depending on whether specific metadata are present (or not). For example, if the MALDI term is present, then additional rules related to MALDI (such as the requirement of inclusion of laser parameters) can be validated against this. This enables a flexible and more thorough automated validation of (i)mzML data. Such a system is necessary for validating data against more comprehensive sets of metadata such as minimum reporting guidelines or metadata requirements prior to submission and acceptance of data to data repositories. We demonstrate how this tool can be used to validate against the proposed minimum reporting guidelines in MSI as well as institute specific metadata criteria. The validator tool is endorsed for validation of imzML ( http://imzml.org/ ) and mzML ( http://www.psidev.info/mzml ) and is made available through the respective Web sites. The validator is also released as open source under Mozilla Public License 2.0 at https://gitlab.com/imzML/imzMLValidator .
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Affiliation(s)
- Alan M Race
- Chair of Bioanalytical Sciences and Food Analysis , University of Bayreuth , 95447 Bayreuth , Germany
| | - Andreas Römpp
- Chair of Bioanalytical Sciences and Food Analysis , University of Bayreuth , 95447 Bayreuth , Germany
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9
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Sivade Dumousseau M, Koch M, Shrivastava A, Alonso-López D, De Las Rivas J, Del-Toro N, Combe CW, Meldal BHM, Heimbach J, Rappsilber J, Sullivan J, Yehudi Y, Orchard S. JAMI: a Java library for molecular interactions and data interoperability. BMC Bioinformatics 2018; 19:133. [PMID: 29642846 PMCID: PMC5896107 DOI: 10.1186/s12859-018-2119-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 03/20/2018] [Indexed: 11/22/2022] Open
Abstract
Background A number of different molecular interactions data download formats now exist, designed to allow access to these valuable data by diverse user groups. These formats include the PSI-XML and MITAB standard interchange formats developed by Molecular Interaction workgroup of the HUPO-PSI in addition to other, use-specific downloads produced by other resources. The onus is currently on the user to ensure that a piece of software is capable of read/writing all necessary versions of each format. This problem may increase, as data providers strive to meet ever more sophisticated user demands and data types. Results A collaboration between EMBL-EBI and the University of Cambridge has produced JAMI, a single library to unify standard molecular interaction data formats such as PSI-MI XML and PSI-MITAB. The JAMI free, open-source library enables the development of molecular interaction computational tools and pipelines without the need to produce different versions of software to read different versions of the data formats. Conclusion Software and tools developed on top of the JAMI framework are able to integrate and support both PSI-MI XML and PSI-MITAB. The use of JAMI avoids the requirement to chain conversions between formats in order to reach a desired output format and prevents code and unit test duplication as the code becomes more modular. JAMI’s model interfaces are abstracted from the underlying format, hiding the complexity and requirements of each data format from developers using JAMI as a library.
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Affiliation(s)
- M Sivade Dumousseau
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - M Koch
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - A Shrivastava
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - D Alonso-López
- Cancer Research Center (CiC-IBMCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and Universidad de Salamanca (USAL), 37007, Salamanca, Spain
| | - J De Las Rivas
- Cancer Research Center (CiC-IBMCC, CSIC/USAL/IBSAL), Consejo Superior de Investigaciones Científicas (CSIC) and Universidad de Salamanca (USAL), 37007, Salamanca, Spain
| | - N Del-Toro
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - C W Combe
- Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - B H M Meldal
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK
| | - J Heimbach
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.,Department of Genetics, University of Cambridge, Cambridge, UK
| | - J Rappsilber
- Wellcome Trust Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3BF, UK.,Bioanalytics, Institute for Biotechnology, Technische Universität Berlin, 13355, Berlin, Germany
| | - J Sullivan
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.,Department of Genetics, University of Cambridge, Cambridge, UK
| | - Y Yehudi
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge, UK.,Department of Genetics, University of Cambridge, Cambridge, UK
| | - S Orchard
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, CB10 1SD, UK.
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10
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Martínez-Bartolomé S, Medina-Aunon JA, López-García MÁ, González-Tejedo C, Prieto G, Navajas R, Salazar-Donate E, Fernández-Costa C, Yates JR, Albar JP. PACOM: A Versatile Tool for Integrating, Filtering, Visualizing, and Comparing Multiple Large Mass Spectrometry Proteomics Data Sets. J Proteome Res 2018; 17:1547-1558. [DOI: 10.1021/acs.jproteome.7b00858] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Salvador Martínez-Bartolomé
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | | | | | | | - Gorka Prieto
- Department of Communications Engineering, University of the Basque Country (UPV/EHU), Bilbao 48013, Spain
| | - Rosana Navajas
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
| | | | - Carolina Fernández-Costa
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
- Immunology, Centro de Investigaciones Biomédicas (CINBIO), Centro singular de Investigación de Galicia: Instituto de Investigación Sanitaria Galicia Sur (IIS-GS), University of Vigo, Campus Universitario, s/n, Vigo 36310, Spain
| | - John R. Yates
- Department of Chemical Physiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Juan Pablo Albar
- Proteomics Laboratory, National Center for Biotechnology, CSIC, Madrid 28049, Spain
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11
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Schober D, Jacob D, Wilson M, Cruz JA, Marcu A, Grant JR, Moing A, Deborde C, de Figueiredo LF, Haug K, Rocca-Serra P, Easton J, Ebbels TMD, Hao J, Ludwig C, Günther UL, Rosato A, Klein MS, Lewis IA, Luchinat C, Jones AR, Grauslys A, Larralde M, Yokochi M, Kobayashi N, Porzel A, Griffin JL, Viant MR, Wishart DS, Steinbeck C, Salek RM, Neumann S. nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data. Anal Chem 2017; 90:649-656. [PMID: 29035042 DOI: 10.1021/acs.analchem.7b02795] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.
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Affiliation(s)
- Daniel Schober
- Leibniz Institute of Plant Biochemistry , Department of Stress and Developmental Biology, Weinberg 3, 06120 Halle, Germany
| | - Daniel Jacob
- INRA, Univ. Bordeaux , UMR1332 Fruit Biology and Pathology, Metabolome Facility of Bordeaux Functional Genomics Center, MetaboHUB, IBVM, Centre INRA Bordeaux, 71 av Edouard Bourlaux, F-33140 Villenave d'Ornon, France
| | - Michael Wilson
- Departments of Computing Sciences and Biological Sciences, University of Alberta , Edmonton, Canada T6G 2E8
| | - Joseph A Cruz
- Departments of Computing Sciences and Biological Sciences, University of Alberta , Edmonton, Canada T6G 2E8
| | - Ana Marcu
- Departments of Computing Sciences and Biological Sciences, University of Alberta , Edmonton, Canada T6G 2E8
| | - Jason R Grant
- Departments of Computing Sciences and Biological Sciences, University of Alberta , Edmonton, Canada T6G 2E8
| | - Annick Moing
- INRA, Univ. Bordeaux , UMR1332 Fruit Biology and Pathology, Metabolome Facility of Bordeaux Functional Genomics Center, MetaboHUB, IBVM, Centre INRA Bordeaux, 71 av Edouard Bourlaux, F-33140 Villenave d'Ornon, France
| | - Catherine Deborde
- INRA, Univ. Bordeaux , UMR1332 Fruit Biology and Pathology, Metabolome Facility of Bordeaux Functional Genomics Center, MetaboHUB, IBVM, Centre INRA Bordeaux, 71 av Edouard Bourlaux, F-33140 Villenave d'Ornon, France
| | - Luis F de Figueiredo
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, U.K
| | - Kenneth Haug
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, U.K
| | | | - John Easton
- School of Engineering, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K
| | - Timothy M D Ebbels
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , London, SW7 2AZ, U.K
| | - Jie Hao
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London , London, SW7 2AZ, U.K
| | - Christian Ludwig
- Institute of Metabolism and Systems Research, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K
| | - Ulrich L Günther
- Institute of Cancer and Genomic Sciences, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K
| | - Antonio Rosato
- Magnetic Resonance Center (CERM) and Department of Chemistry, University of Florence , 50019 Sesto Fiorentino, Florence, Italy
| | - Matthias S Klein
- Department of Biological Sciences, University of Calgary , 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Ian A Lewis
- Department of Biological Sciences, University of Calgary , 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM) and Department of Chemistry, University of Florence , 50019 Sesto Fiorentino, Florence, Italy
| | - Andrew R Jones
- Institute of Integrative Biology, University of Liverpool , Bioscience Building, Crown Street, Liverpool L69 7ZB, U.K
| | - Arturas Grauslys
- Institute of Integrative Biology, University of Liverpool , Bioscience Building, Crown Street, Liverpool L69 7ZB, U.K
| | - Martin Larralde
- Ecole Normale Supérieure Paris-Saclay , 61 Avenue du Président Wilson, 94230 Cachan, France
| | - Masashi Yokochi
- Institute for Protein Research (IPR), Osaka University , 3-2 Yamadaoka, Suita-shi, Osaka, 565-0871, Japan
| | - Naohiro Kobayashi
- Institute for Protein Research (IPR), Osaka University , 3-2 Yamadaoka, Suita-shi, Osaka, 565-0871, Japan
| | - Andrea Porzel
- Department of Bioorganic Chemistry, Leibniz Institute of Plant Biochemistry , 06120 Halle (Saale), Germany
| | - Julian L Griffin
- Department of Biochemistry, University of Cambridge , Downing Site, Cambridge CB2 1QW, U.K
| | - Mark R Viant
- School of Biosciences, University of Birmingham , Edgbaston, Birmingham B15 2TT, U.K
| | - David S Wishart
- Departments of Computing Sciences and Biological Sciences, University of Alberta , Edmonton, Canada T6G 2E8
| | - Christoph Steinbeck
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, U.K
| | - Reza M Salek
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, U.K
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry , Department of Stress and Developmental Biology, Weinberg 3, 06120 Halle, Germany
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12
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Abstract
Molecular interaction databases collect, organize, and enable the analysis of the increasing amounts of molecular interaction data being produced and published as we move towards a more complete understanding of the interactomes of key model organisms. The organization of these data in a structured format supports analyses such as the modeling of pairwise relationships between interactors into interaction networks and is a powerful tool for understanding the complex molecular machinery of the cell. This chapter gives an overview of the principal molecular interaction databases, in particular the IMEx databases, and their curation policies, use of standardized data formats and quality control rules. Special attention is given to the MIntAct project, in which IntAct and MINT joined forces to create a single resource to improve curation and software development efforts. This is exemplified as a model for the future of molecular interaction data collation and dissemination.
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13
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Vizcaíno JA, Mayer G, Perkins S, Barsnes H, Vaudel M, Perez-Riverol Y, Ternent T, Uszkoreit J, Eisenacher M, Fischer L, Rappsilber J, Netz E, Walzer M, Kohlbacher O, Leitner A, Chalkley RJ, Ghali F, Martínez-Bartolomé S, Deutsch EW, Jones AR. The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics. Mol Cell Proteomics 2017; 16:1275-1285. [PMID: 28515314 PMCID: PMC5500760 DOI: 10.1074/mcp.m117.068429] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 05/15/2017] [Indexed: 12/31/2022] Open
Abstract
The first stable version of the Proteomics Standards Initiative mzIdentML open data standard (version 1.1) was published in 2012-capturing the outputs of peptide and protein identification software. In the intervening years, the standard has become well-supported in both commercial and open software, as well as a submission and download format for public repositories. Here we report a new release of mzIdentML (version 1.2) that is required to keep pace with emerging practice in proteome informatics. New features have been added to support: (1) scores associated with localization of modifications on peptides; (2) statistics performed at the level of peptides; (3) identification of cross-linked peptides; and (4) support for proteogenomics approaches. In addition, there is now improved support for the encoding of de novo sequencing of peptides, spectral library searches, and protein inference. As a key point, the underlying XML schema has only undergone very minor modifications to simplify as much as possible the transition from version 1.1 to version 1.2 for implementers, but there have been several notable updates to the format specification, implementation guidelines, controlled vocabularies and validation software. mzIdentML 1.2 can be described as backwards compatible, in that reading software designed for mzIdentML 1.1 should function in most cases without adaptation. We anticipate that these developments will provide a continued stable base for software teams working to implement the standard. All the related documentation is accessible at http://www.psidev.info/mzidentml.
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Affiliation(s)
- Juan Antonio Vizcaíno
- From the ‡European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Gerhard Mayer
- §Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
| | - Simon Perkins
- ¶Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Harald Barsnes
- ‖Proteomics Unit, Department of Biomedicine, University of Bergen, Norway
- **Computational Biology Unit, Department of Informatics, University of Bergen, Norway
- ‡‡KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
| | - Marc Vaudel
- ‖Proteomics Unit, Department of Biomedicine, University of Bergen, Norway
- ‡‡KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway
- §§Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Yasset Perez-Riverol
- From the ‡European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Tobias Ternent
- From the ‡European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Julian Uszkoreit
- §Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
| | - Martin Eisenacher
- §Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
| | - Lutz Fischer
- ¶¶Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Juri Rappsilber
- ¶¶Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
- ‖‖Chair of Bioanalytics, Institute of Biotechnology Technische Universität Berlin, 13355 Berlin, Germany
| | - Eugen Netz
- Biomolecular Interactions group, Max Planck Institute for Developmental Biology, Tübingen D-72076, Germany
| | - Mathias Walzer
- Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany
| | - Oliver Kohlbacher
- Biomolecular Interactions group, Max Planck Institute for Developmental Biology, Tübingen D-72076, Germany
- Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany
- Dept. of Computer Science, University of Tübingen, Germany
- Quantitative Biology Center, University of Tübingen, Germany
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Auguste-Piccard-Hof 1, 8093 Zurich, Switzerland
| | - Robert J Chalkley
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, California, 94143
| | - Fawaz Ghali
- ¶Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Salvador Martínez-Bartolomé
- Department of Chemical Physiology, The Scripps Research Institute, 10550, N. Torrey Pines Rd., La Jolla, California, 92037
| | | | - Andrew R Jones
- ¶Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK;
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14
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Bittremieux W, Walzer M, Tenzer S, Zhu W, Salek RM, Eisenacher M, Tabb DL. The Human Proteome Organization-Proteomics Standards Initiative Quality Control Working Group: Making Quality Control More Accessible for Biological Mass Spectrometry. Anal Chem 2017; 89:4474-4479. [PMID: 28318237 DOI: 10.1021/acs.analchem.6b04310] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
To have confidence in results acquired during biological mass spectrometry experiments, a systematic approach to quality control is of vital importance. Nonetheless, until now, only scattered initiatives have been undertaken to this end, and these individual efforts have often not been complementary. To address this issue, the Human Proteome Organization-Proteomics Standards Initiative has established a new working group on quality control at its meeting in the spring of 2016. The goal of this working group is to provide a unifying framework for quality control data. The initial focus will be on providing a community-driven standardized file format for quality control. For this purpose, the previously proposed qcML format will be adapted to support a variety of use cases for both proteomics and metabolomics applications, and it will be established as an official PSI format. An important consideration is to avoid enforcing restrictive requirements on quality control but instead provide the basic technical necessities required to support extensive quality control for any type of mass spectrometry-based workflow. We want to emphasize that this is an open community effort, and we seek participation from all scientists with an interest in this field.
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Affiliation(s)
- Wout Bittremieux
- Department of Mathematics and Computer Science, University of Antwerp , Middelheimlaan 1, 2020 Antwerp, Belgium.,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital , Wilrijkstraat 10, 2650 Edegem, Belgium
| | - Mathias Walzer
- Department of Computer Science, University of Tübingen , Tübingen 72076, Germany.,Center for Bioinformatics, University of Tübingen , Tübingen 72074, Germany
| | - Stefan Tenzer
- Institute for Immunology, University Medical Center of the Johannes-Gutenberg University Mainz D 55131, Germany
| | - Weimin Zhu
- National Center for Protein Science , No. 38, Science Park Road, Changping District, Beijing 102206, China
| | - Reza M Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI) , Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
| | - Martin Eisenacher
- Medical Bioinformatics, Medizinisches Proteom-Center, Ruhr-University Bochum , Bochum 44801, Germany
| | - David L Tabb
- Division of Molecular Biology and Human Genetics, Stellenbosch University Faculty of Medicine and Health Sciences , Tygerberg Hospital, Francie Van Zijl Drive, Cape Town 7505, South Africa
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15
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Qi D, Zhang H, Fan J, Perkins S, Pisconti A, Simpson DM, Bessant C, Hubbard S, Jones AR. The mzqLibrary--An open source Java library supporting the HUPO-PSI quantitative proteomics standard. Proteomics 2015; 15:3152-62. [PMID: 26037908 PMCID: PMC4973685 DOI: 10.1002/pmic.201400535] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Revised: 05/02/2015] [Accepted: 05/29/2015] [Indexed: 12/02/2022]
Abstract
The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML‐based format, capable of representing data about two‐dimensional features from LC‐MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java‐based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)‐level quantification values from peptide‐level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC‐MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in‐built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq‐lib/.
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Affiliation(s)
- Da Qi
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Huaizhong Zhang
- The Faculty of Life Sciences, University of Manchester, Manchester, UK
| | - Jun Fan
- The School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
| | - Simon Perkins
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | | | - Deborah M Simpson
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Conrad Bessant
- The School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
| | - Simon Hubbard
- The Faculty of Life Sciences, University of Manchester, Manchester, UK
| | - Andrew R Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
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16
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Seymour SL, Farrah T, Binz PA, Chalkley RJ, Cottrell JS, Searle BC, Tabb DL, Vizcaíno JA, Prieto G, Uszkoreit J, Eisenacher M, Martínez-Bartolomé S, Ghali F, Jones AR. A standardized framing for reporting protein identifications in mzIdentML 1.2. Proteomics 2014; 14:2389-99. [PMID: 25092112 PMCID: PMC4384534 DOI: 10.1002/pmic.201400080] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Revised: 07/02/2014] [Accepted: 07/31/2014] [Indexed: 11/09/2022]
Abstract
Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software.
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Affiliation(s)
| | - Terry Farrah
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109, USA
| | - Pierre-Alain Binz
- Swiss-Prot group, Swiss Institute of Bioinformatics, Rue Michel-Servet 1, CH-1211 Geneva 4, Switzerland; current address: Service de Biomédecine, Centre Hospitalier Universitaire Vaudois CHUV, Rte du Bugnon 46, CH-1011 Lausanne
| | - Robert J. Chalkley
- Department of Pharmaceutical Chemistry, University of California, San Francisco, 600 16 Street, Genentech Hall, Room N474A, San Francisco, CA 94158, USA
| | | | - Brian C. Searle
- Proteome Software, Inc., 1340 SW Bertha Blvd, Suite 10, Portland, OR, 97219, USA
| | - David L. Tabb
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee 37232-8575, USA
- Jim Ayers Institute for Precancer Detection and Diagnosis, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee 37232-6840, USA
- Department of Biochemistry, Vanderbilt University Medical Center, Nashville, Tennessee 37232-0146, USA
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Proteomics Services Team, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Gorka Prieto
- Department of Communications Engineering, University of the Basque Country (UPV/EHU), Alda. Urquijo s/n Bilbao, 48013, Spain
| | - Julian Uszkoreit
- Medizinisches Proteom-Center, Ruhr-Universität Bochum, Universitätsstr. 150, D-44801 Bochum, Germany
| | - Martin Eisenacher
- Medizinisches Proteom-Center, Ruhr-Universität Bochum, Universitätsstr. 150, D-44801 Bochum, Germany
| | | | - Fawaz Ghali
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
| | - Andrew R. Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool, UK
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17
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Walzer M, Pernas LE, Nasso S, Bittremieux W, Nahnsen S, Kelchtermans P, Pichler P, van den Toorn HWP, Staes A, Vandenbussche J, Mazanek M, Taus T, Scheltema RA, Kelstrup CD, Gatto L, van Breukelen B, Aiche S, Valkenborg D, Laukens K, Lilley KS, Olsen JV, Heck AJR, Mechtler K, Aebersold R, Gevaert K, Vizcaíno JA, Hermjakob H, Kohlbacher O, Martens L. qcML: an exchange format for quality control metrics from mass spectrometry experiments. Mol Cell Proteomics 2014; 13:1905-13. [PMID: 24760958 PMCID: PMC4125725 DOI: 10.1074/mcp.m113.035907] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2013] [Revised: 03/13/2014] [Indexed: 12/22/2022] Open
Abstract
Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml.
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Affiliation(s)
- Mathias Walzer
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Lucia Espona Pernas
- §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland
| | - Sara Nasso
- ¶Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland; §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland
| | - Wout Bittremieux
- ‖Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; **Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium
| | - Sven Nahnsen
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Pieter Kelchtermans
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium; ¶¶Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol Belgium
| | - Peter Pichler
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Henk W P van den Toorn
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - An Staes
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Jonathan Vandenbussche
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Michael Mazanek
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Thomas Taus
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Richard A Scheltema
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany
| | - Christian D Kelstrup
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark
| | - Laurent Gatto
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, CB2 1GA, United Kingdom; Computational Proteomics Unit, Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge, CB2 1GA, UK
| | - Bas van Breukelen
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - Stephan Aiche
- Department of Mathematics and Computer Science, Freie Universität Berlin, Takustr. 9, 14195 Berlin, Germany
| | - Dirk Valkenborg
- ¶¶Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol Belgium; I-BioStat, Hasselt University, Belgium; CFP-CeProMa, University of Antwerp, Belgium
| | - Kris Laukens
- ‖Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; **Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Antwerp, Belgium
| | - Kathryn S Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, CB2 1GA, United Kingdom
| | - Jesper V Olsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3b, DK-2200 Copenhagen, Denmark
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584 CH Utrecht, Netherlands; Netherlands Proteomics Centre, Padualaan 8, 3584 CH Utrecht, Netherlands
| | - Karl Mechtler
- ‖‖Research Institute of Molecular Pathology (IMP), Dr. Bohr-Gasse 7, A-1030 Vienna, Austria; Institute of Molecular Biotechnology of the Austrian Academy of Science (IMBA), Dr. Bohr-Gasse 3, A-1030 Vienna, Austria
| | - Ruedi Aebersold
- §Department of Biology, Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule Zürich, 8092 Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland
| | - Kris Gevaert
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Oliver Kohlbacher
- From the ‡Applied Bioinformatics, Center for Bioinformatics, Quantitative Biology Center, and Dept. of Computer Science, University of Tuebingen, Germany
| | - Lennart Martens
- ‡‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium; §§Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium;
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18
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Bittremieux W, Kelchtermans P, Valkenborg D, Martens L, Laukens K. jqcML: An Open-Source Java API for Mass Spectrometry Quality Control Data in the qcML Format. J Proteome Res 2014; 13:3484-7. [DOI: 10.1021/pr401274z] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Affiliation(s)
- Wout Bittremieux
- Department
of Mathematics and Computer Science, University of Antwerp, Middelheimlaan
1, B-2020 Antwerp, Belgium
- Biomedical
Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Wilrijkstraat 10, B-2650 Antwerp, Belgium
| | - Pieter Kelchtermans
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium
| | - Dirk Valkenborg
- Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium
- CFP-CeProMa, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp, Belgium
- I-BioStat, Hasselt University, Agoralaan - Building D, B-3590 Diepenbeek, Belgium
| | - Lennart Martens
- Department
of Medical Protein Research, VIB, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
- Department
of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Albert Baertsoenkaai 3, B-9000 Ghent, Belgium
| | - Kris Laukens
- Department
of Mathematics and Computer Science, University of Antwerp, Middelheimlaan
1, B-2020 Antwerp, Belgium
- Biomedical
Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Wilrijkstraat 10, B-2650 Antwerp, Belgium
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19
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Qi D, Krishna R, Jones AR. The jmzQuantML programming interface and validator for the mzQuantML data standard. Proteomics 2014; 14:685-8. [PMID: 24453188 PMCID: PMC4016760 DOI: 10.1002/pmic.201300281] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Revised: 11/20/2013] [Accepted: 12/20/2013] [Indexed: 11/17/2022]
Abstract
The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data. We present a Java application programming interface (API) for mzQuantML called jmzQuantML. The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file. The API provides read and write capabilities, and is designed to be embedded in other software packages, enabling mzQuantML support to be added to proteomics software tools (http://code.google.com/p/jmzquantml/). The mzQuantML standard is designed around a multilevel validation system to ensure that files are structurally and semantically correct for different proteomics quantitative techniques. In this article, we also describe a Java software tool (http://code.google.com/p/mzquantml-validator/) for validating mzQuantML files, which is a formal part of the data standard.
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Affiliation(s)
- Da Qi
- Institute of Integrative Biology, University of Liverpool, UK
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20
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Martínez-Bartolomé S, Binz PA, Albar JP. The Minimal Information about a Proteomics Experiment (MIAPE) from the Proteomics Standards Initiative. Methods Mol Biol 2014; 1072:765-80. [PMID: 24136562 DOI: 10.1007/978-1-62703-631-3_53] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
During the last 10 years, the Proteomics Standards Initiative from the Human Proteome Organization (HUPO-PSI) has worked on defining standards for proteomics data representation as well as guidelines that state the minimum information that should be included when reporting a proteomics experiment (MIAPE). Such minimum information must describe the complete experiment, including both experimental protocols and data processing methods, allowing a critical evaluation of the whole process and the potential recreation of the work. In this chapter we describe the standardization work performed by the HUPO-PSI, and then we concentrate on the MIAPE guidelines, highlighting its importance when publishing proteomics experiments particularly in specialized proteomics journals. Finally, we describe existing bioinformatics resources that generate MIAPE compliant reports or that check proteomics data files for MIAPE compliance.
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21
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Mayer G, Jones AR, Binz PA, Deutsch EW, Orchard S, Montecchi-Palazzi L, Vizcaíno JA, Hermjakob H, Oveillero D, Julian R, Stephan C, Meyer HE, Eisenacher M. Controlled vocabularies and ontologies in proteomics: overview, principles and practice. BIOCHIMICA ET BIOPHYSICA ACTA 2014; 1844:98-107. [PMID: 23429179 PMCID: PMC3898906 DOI: 10.1016/j.bbapap.2013.02.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2012] [Revised: 02/05/2013] [Accepted: 02/09/2013] [Indexed: 11/30/2022]
Abstract
This paper focuses on the use of controlled vocabularies (CVs) and ontologies especially in the area of proteomics, primarily related to the work of the Proteomics Standards Initiative (PSI). It describes the relevant proteomics standard formats and the ontologies used within them. Software and tools for working with these ontology files are also discussed. The article also examines the "mapping files" used to ensure correct controlled vocabulary terms that are placed within PSI standards and the fulfillment of the MIAPE (Minimum Information about a Proteomics Experiment) requirements. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
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Affiliation(s)
- Gerhard Mayer
- Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
| | - Andrew R. Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK
| | - Pierre-Alain Binz
- SIB Swiss Institute of Bioinformatics, Swiss-Prot group, Rue Michel-Servet 1, CH-1211 Geneva 4, Switzerland
| | - Eric W. Deutsch
- Institute for Systems Biology, 401 Terry Avenue North, Seattle, WA 98109, USA
| | - Sandra Orchard
- EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | | | - Henning Hermjakob
- EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - David Oveillero
- EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Christian Stephan
- Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
- Kairos GmbH, Universitätsstraße 136, D-44799 Bochum, Germany
| | - Helmut E. Meyer
- Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
| | - Martin Eisenacher
- Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
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22
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Martens L. Resilience in the proteomics data ecosystem: how the field cares for its data. Proteomics 2013; 13:1548-50. [PMID: 23596016 DOI: 10.1002/pmic.201300118] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2013] [Accepted: 03/26/2013] [Indexed: 11/08/2022]
Abstract
The public dissemination of data is an integral part of the life sciences. In the field of proteomics too, data sharing has taken off over the last few years, with the first downstream uses of these data quickly gaining prominence. At the same time, the recent unfortunate demise of two repositories, NCBI Peptidome and ProteomeCommons Tranche, has shown the frailty of such data gathering efforts. Heroic efforts by the PRIDE and Peptidome teams to rescue the Peptidome data have now ensured their continued availability to the field, and alternatives have already been put in place for Tranche. But with public data increasingly at the hub of the life sciences, it is a good time to look at the proteomics data ecosystem in some more detail.
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Affiliation(s)
- Lennart Martens
- Department of Medical Protein Research, VIB, Ghent, Belgium.
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23
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Gu Q, Yu LR. Proteomics quality and standard: from a regulatory perspective. J Proteomics 2013; 96:353-9. [PMID: 24316359 DOI: 10.1016/j.jprot.2013.11.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2012] [Revised: 11/07/2013] [Accepted: 11/22/2013] [Indexed: 12/30/2022]
Abstract
Proteomics has emerged as a rapidly expanding field dealing with large-scale protein analyses. It is anticipated that proteomics data will be increasingly submitted to the U.S. Food and Drug Administration (FDA) for biomarker qualification or in conjunction with applications for the approval of drugs, medical devices, and other FDA-regulated consumer products. To date, however, no established guideline has been available regarding the generation, submission and assessment of the quality of proteomics data that will be reviewed by regulatory agencies for decision making. Therefore, this commentary is aimed at provoking some thoughts and debates towards developing a framework which can guide future proteomics data submission. The ultimate goal is to establish quality control standards for proteomics data generation and evaluation, and to prepare government agencies such as the FDA to meet future obligations utilizing proteomics data to support regulatory decision.
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Affiliation(s)
- Qiang Gu
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, USA
| | - Li-Rong Yu
- Division of Systems Biology, National Center for Toxicological Research, Food and Drug Administration, USA.
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24
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Van Roey K, Orchard S, Kerrien S, Dumousseau M, Ricard-Blum S, Hermjakob H, Gibson TJ. Capturing cooperative interactions with the PSI-MI format. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2013; 2013:bat066. [PMID: 24067240 PMCID: PMC3782717 DOI: 10.1093/database/bat066] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The complex biological processes that control cellular function are mediated by intricate networks of molecular interactions. Accumulating evidence indicates that these interactions are often interdependent, thus acting cooperatively. Cooperative interactions are prevalent in and indispensible for reliable and robust control of cell regulation, as they underlie the conditional decision-making capability of large regulatory complexes. Despite an increased focus on experimental elucidation of the molecular details of cooperative binding events, as evidenced by their growing occurrence in literature, they are currently lacking from the main bioinformatics resources. One of the contributing factors to this deficiency is the lack of a computer-readable standard representation and exchange format for cooperative interaction data. To tackle this shortcoming, we added functionality to the widely used PSI-MI interchange format for molecular interaction data by defining new controlled vocabulary terms that allow annotation of different aspects of cooperativity without making structural changes to the underlying XML schema. As a result, we are able to capture cooperative interaction data in a structured format that is backward compatible with PSI-MI–based data and applications. This will facilitate the storage, exchange and analysis of cooperative interaction data, which in turn will advance experimental research on this fundamental principle in biology. Database URL:http://psi-mi-cooperativeinteractions.embl.de/
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Affiliation(s)
- Kim Van Roey
- Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, D-69117 Heidelberg, Germany, Proteomics Services, EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK and UMR 5086 CNRS - Université Lyon 1, Institut de Biologie et Chimie des Protéines, 7 passage du Vercors, 69367 Lyon Cedex 07, France
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25
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Abstract
Summary: BioPAX is a community-developed standard language for biological pathway data. A key functionality required for efficient BioPAX data exchange is validation—detecting errors and inconsistencies in BioPAX documents. The BioPAX Validator is a command-line tool, Java library and online web service for BioPAX that performs >100 classes of consistency checks. Availability and implementation: The validator recognizes common syntactic errors and semantic inconsistencies and reports them in a customizable human readable format. It can also automatically fix some errors and normalize BioPAX data. Since its release, the validator has become a critical tool for the pathway informatics community, detecting thousands of errors and helping substantially increase the conformity and uniformity of BioPAX-formatted data. The BioPAX Validator is open source and released under LGPL v3 license. All sources, binaries and documentation can be found at sf.net/p/biopax, and the latest stable version of the web application is available at biopax.org/validator. Contact:igor.rodchenkov@utoronto.ca or gary.bader@utoronto.ca
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Affiliation(s)
- Igor Rodchenkov
- The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada and Computational Biology Center, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY, USA
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26
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Vaudel M, Sickmann A, Martens L. Introduction to opportunities and pitfalls in functional mass spectrometry based proteomics. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2013; 1844:12-20. [PMID: 23845992 DOI: 10.1016/j.bbapap.2013.06.019] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2012] [Revised: 06/05/2013] [Accepted: 06/25/2013] [Indexed: 10/26/2022]
Abstract
With the advent of mass spectrometry based proteomics, the identification of thousands of proteins has become commonplace in biology nowadays. Increasingly, efforts have also been invested toward the detection and localization of posttranslational modifications. It is furthermore common practice to quantify the identified entities, a task supported by a panel of different methods. Finally, the results can also be enriched with functional knowledge gained on the proteins, detecting for instance differentially expressed gene ontology terms or biological pathways. In this study, we review the resources, methods and tools available for the researcher to achieve such a quantitative functional analysis. These include statistics for the post-processing of identification and quantification results, online resources and public repositories. With a focus on free but user-friendly software, preferably also open-source, we provide a list of tools designed to help the researcher manage the vast amount of data generated. We also indicate where such applications currently remain lacking. Moreover, we stress the eventual pitfalls of every step of such studies. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.
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Affiliation(s)
- Marc Vaudel
- Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany; Proteomics Unit (PROBE), Department of Biomedicine, University of Bergen, Bergen, Norway.
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27
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Ghali F, Krishna R, Lukasse P, Martínez-Bartolomé S, Reisinger F, Hermjakob H, Vizcaíno JA, Jones AR. Tools (Viewer, Library and Validator) that facilitate use of the peptide and protein identification standard format, termed mzIdentML. Mol Cell Proteomics 2013; 12:3026-35. [PMID: 23813117 PMCID: PMC3820921 DOI: 10.1074/mcp.o113.029777] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The Proteomics Standards Initiative has recently released the mzIdentML data standard for representing peptide and protein identification results, for example, created by a search engine. When a new standard format is produced, it is important that software tools are available that make it straightforward for laboratory scientists to use it routinely and for bioinformaticians to embed support in their own tools. Here we report the release of several open-source Java-based software packages based on mzIdentML: ProteoIDViewer, mzidLibrary, and mzidValidator. The ProteoIDViewer is a desktop application allowing users to visualize mzIdentML-formatted results originating from any appropriate identification software; it supports visualization of all the features of the mzIdentML format. The mzidLibrary is a software library containing routines for importing data from external search engines, post-processing identification data (such as false discovery rate calculations), combining results from multiple search engines, performing protein inference, setting identification thresholds, and exporting results from mzIdentML to plain text files. The mzidValidator is able to process files and report warnings or errors if files are not correctly formatted or contain some semantic error. We anticipate that these developments will simplify adoption of the new standard in proteomics laboratories and the integration of mzIdentML into other software tools. All three tools are freely available in the public domain.
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Affiliation(s)
- Fawaz Ghali
- Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, United Kingdom
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28
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Gonzalez-Galarza FF, Qi D, Fan J, Bessant C, Jones AR. A tutorial for software development in quantitative proteomics using PSI standard formats. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2013; 1844:88-97. [PMID: 23584085 PMCID: PMC4008935 DOI: 10.1016/j.bbapap.2013.04.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Revised: 02/22/2013] [Accepted: 04/05/2013] [Indexed: 01/21/2023]
Abstract
The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan. A tutorial to help software developers use PSI standard formats. A description of programming interfaces and tools available. Code snippets and a basic graphical interface to assist understanding.
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29
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Mayer G, Montecchi-Palazzi L, Ovelleiro D, Jones AR, Binz PA, Deutsch EW, Chambers M, Kallhardt M, Levander F, Shofstahl J, Orchard S, Vizcaíno JA, Hermjakob H, Stephan C, Meyer HE, Eisenacher M. The HUPO proteomics standards initiative- mass spectrometry controlled vocabulary. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2013; 2013:bat009. [PMID: 23482073 PMCID: PMC3594986 DOI: 10.1093/database/bat009] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Controlled vocabularies (CVs), i.e. a collection of predefined terms describing a modeling domain, used for the semantic annotation of data, and ontologies are used in structured data formats and databases to avoid inconsistencies in annotation, to have a unique (and preferably short) accession number and to give researchers and computer algorithms the possibility for more expressive semantic annotation of data. The Human Proteome Organization (HUPO)–Proteomics Standards Initiative (PSI) makes extensive use of ontologies/CVs in their data formats. The PSI-Mass Spectrometry (MS) CV contains all the terms used in the PSI MS–related data standards. The CV contains a logical hierarchical structure to ensure ease of maintenance and the development of software that makes use of complex semantics. The CV contains terms required for a complete description of an MS analysis pipeline used in proteomics, including sample labeling, digestion enzymes, instrumentation parts and parameters, software used for identification and quantification of peptides/proteins and the parameters and scores used to determine their significance. Owing to the range of topics covered by the CV, collaborative development across several PSI working groups, including proteomics research groups, instrument manufacturers and software vendors, was necessary. In this article, we describe the overall structure of the CV, the process by which it has been developed and is maintained and the dependencies on other ontologies. Database URL: http://psidev.cvs.sourceforge.net/viewvc/psidev/psi/psi-ms/mzML/controlledVocabulary/psi-ms.obo
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Affiliation(s)
- Gerhard Mayer
- Medizinisches Proteom Center (MPC), Ruhr-Universität Bochum, D-44801 Bochum, Germany
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30
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Abstract
Molecular interaction databases are playing an ever more important role in our understanding of the biology of the cell. An increasing number of resources exist to provide these data and many of these have adopted the controlled vocabularies and agreed-upon standardised data formats produced by the Molecular Interaction workgroup of the Human Proteome Organization Proteomics Standards Initiative (HUPO PSI-MI). Use of these standards allows each resource to establish PSI Common QUery InterfaCe (PSICQUIC) service, making data from multiple resources available to the user in response to a single query. This cooperation between databases has been taken a stage further, with the establishment of the International Molecular Exchange (IMEx) consortium which aims to maximise the curation power of numerous data resources, and provide the user with a non-redundant, consistently annotated set of interaction data.
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Affiliation(s)
- Sandra Orchard
- EMBL Outstation - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
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31
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Côté RG, Griss J, Dianes JA, Wang R, Wright JC, van den Toorn HWP, van Breukelen B, Heck AJR, Hulstaert N, Martens L, Reisinger F, Csordas A, Ovelleiro D, Perez-Rivevol Y, Barsnes H, Hermjakob H, Vizcaíno JA. The PRoteomics IDEntification (PRIDE) Converter 2 framework: an improved suite of tools to facilitate data submission to the PRIDE database and the ProteomeXchange consortium. Mol Cell Proteomics 2012; 11:1682-9. [PMID: 22949509 PMCID: PMC3518121 DOI: 10.1074/mcp.o112.021543] [Citation(s) in RCA: 99] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The original PRIDE Converter tool greatly simplified the process of submitting mass spectrometry (MS)-based proteomics data to the PRIDE database. However, after much user feedback, it was noted that the tool had some limitations and could not handle several user requirements that were now becoming commonplace. This prompted us to design and implement a whole new suite of tools that would build on the successes of the original PRIDE Converter and allow users to generate submission-ready, well-annotated PRIDE XML files. The PRIDE Converter 2 tool suite allows users to convert search result files into PRIDE XML (the format needed for performing submissions to the PRIDE database), generate mzTab skeleton files that can be used as a basis to submit quantitative and gel-based MS data, and post-process PRIDE XML files by filtering out contaminants and empty spectra, or by merging several PRIDE XML files together. All the tools have both a graphical user interface that provides a dialog-based, user-friendly way to convert and prepare files for submission, as well as a command-line interface that can be used to integrate the tools into existing or novel pipelines, for batch processing and power users. The PRIDE Converter 2 tool suite will thus become a cornerstone in the submission process to PRIDE and, by extension, to the ProteomeXchange consortium of MS-proteomics data repositories.
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Affiliation(s)
- Richard G Côté
- Proteomics Services Team, EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
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32
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Jones AR, Eisenacher M, Mayer G, Kohlbacher O, Siepen J, Hubbard SJ, Selley JN, Searle BC, Shofstahl J, Seymour SL, Julian R, Binz PA, Deutsch EW, Hermjakob H, Reisinger F, Griss J, Vizcaíno JA, Chambers M, Pizarro A, Creasy D. The mzIdentML data standard for mass spectrometry-based proteomics results. Mol Cell Proteomics 2012. [PMID: 22375074 DOI: 10.1074/mcp.m111.014381 [epub ahead of print]] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2023] Open
Abstract
We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.
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Affiliation(s)
- Andrew R Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZJ, UK.
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33
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Jones AR, Eisenacher M, Mayer G, Kohlbacher O, Siepen J, Hubbard SJ, Selley JN, Searle BC, Shofstahl J, Seymour SL, Julian R, Binz PA, Deutsch EW, Hermjakob H, Reisinger F, Griss J, Vizcaíno JA, Chambers M, Pizarro A, Creasy D. The mzIdentML data standard for mass spectrometry-based proteomics results. Mol Cell Proteomics 2012; 11:M111.014381. [PMID: 22375074 PMCID: PMC3394945 DOI: 10.1074/mcp.m111.014381] [Citation(s) in RCA: 148] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2011] [Revised: 12/20/2011] [Indexed: 11/06/2022] Open
Abstract
We report the release of mzIdentML, an exchange standard for peptide and protein identification data, designed by the Proteomics Standards Initiative. The format was developed by the Proteomics Standards Initiative in collaboration with instrument and software vendors, and the developers of the major open-source projects in proteomics. Software implementations have been developed to enable conversion from most popular proprietary and open-source formats, and mzIdentML will soon be supported by the major public repositories. These developments enable proteomics scientists to start working with the standard for exchanging and publishing data sets in support of publications and they provide a stable platform for bioinformatics groups and commercial software vendors to work with a single file format for identification data.
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Affiliation(s)
- Andrew R Jones
- Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZJ, UK.
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34
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Orchard S, Kerrien S, Abbani S, Aranda B, Bhate J, Bidwell S, Bridge A, Briganti L, Brinkman FSL, Brinkman F, Cesareni G, Chatr-aryamontri A, Chautard E, Chen C, Dumousseau M, Goll J, Hancock REW, Hancock R, Hannick LI, Jurisica I, Khadake J, Lynn DJ, Mahadevan U, Perfetto L, Raghunath A, Ricard-Blum S, Roechert B, Salwinski L, Stümpflen V, Tyers M, Uetz P, Xenarios I, Hermjakob H. Protein interaction data curation: the International Molecular Exchange (IMEx) consortium. Nat Methods 2012; 9:345-50. [PMID: 22453911 DOI: 10.1038/nmeth.1931] [Citation(s) in RCA: 385] [Impact Index Per Article: 32.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The International Molecular Exchange (IMEx) consortium is an international collaboration between major public interaction data providers to share literature-curation efforts and make a nonredundant set of protein interactions available in a single search interface on a common website (http://www.imexconsortium.org/). Common curation rules have been developed, and a central registry is used to manage the selection of articles to enter into the dataset. We discuss the advantages of such a service to the user, our quality-control measures and our data-distribution practices.
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Affiliation(s)
- Sandra Orchard
- European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, UK.
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35
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Deutsch EW, Chambers M, Neumann S, Levander F, Binz PA, Shofstahl J, Campbell DS, Mendoza L, Ovelleiro D, Helsens K, Martens L, Aebersold R, Moritz RL, Brusniak MY. TraML--a standard format for exchange of selected reaction monitoring transition lists. Mol Cell Proteomics 2012; 11:R111.015040. [PMID: 22159873 PMCID: PMC3322582 DOI: 10.1074/mcp.r111.015040] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2011] [Revised: 12/02/2011] [Indexed: 11/06/2022] Open
Abstract
Targeted proteomics via selected reaction monitoring is a powerful mass spectrometric technique affording higher dynamic range, increased specificity and lower limits of detection than other shotgun mass spectrometry methods when applied to proteome analyses. However, it involves selective measurement of predetermined analytes, which requires more preparation in the form of selecting appropriate signatures for the proteins and peptides that are to be targeted. There is a growing number of software programs and resources for selecting optimal transitions and the instrument settings used for the detection and quantification of the targeted peptides, but the exchange of this information is hindered by a lack of a standard format. We have developed a new standardized format, called TraML, for encoding transition lists and associated metadata. In addition to introducing the TraML format, we demonstrate several implementations across the community, and provide semantic validators, extensive documentation, and multiple example instances to demonstrate correctly written documents. Widespread use of TraML will facilitate the exchange of transitions, reduce time spent handling incompatible list formats, increase the reusability of previously optimized transitions, and thus accelerate the widespread adoption of targeted proteomics via selected reaction monitoring.
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Affiliation(s)
- Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, USA.
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36
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Medina-Aunon JA, Martínez-Bartolomé S, López-García MA, Salazar E, Navajas R, Jones AR, Paradela A, Albar JP. The ProteoRed MIAPE web toolkit: a user-friendly framework to connect and share proteomics standards. Mol Cell Proteomics 2012; 10:M111.008334. [PMID: 21983993 DOI: 10.1074/mcp.m111.008334] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
The development of the HUPO-PSI's (Proteomics Standards Initiative) standard data formats and MIAPE (Minimum Information About a Proteomics Experiment) guidelines should improve proteomics data sharing within the scientific community. Proteomics journals have encouraged the use of these standards and guidelines to improve the quality of experimental reporting and ease the evaluation and publication of manuscripts. However, there is an evident lack of bioinformatics tools specifically designed to create and edit standard file formats and reports, or embed them within proteomics workflows. In this article, we describe a new web-based software suite (The ProteoRed MIAPE web toolkit) that performs several complementary roles related to proteomic data standards. First, it can verify that the reports fulfill the minimum information requirements of the corresponding MIAPE modules, highlighting inconsistencies or missing information. Second, the toolkit can convert several XML-based data standards directly into human readable MIAPE reports stored within the ProteoRed MIAPE repository. Finally, it can also perform the reverse operation, allowing users to export from MIAPE reports into XML files for computational processing, data sharing, or public database submission. The toolkit is thus the first application capable of automatically linking the PSI's MIAPE modules with the corresponding XML data exchange standards, enabling bidirectional conversions. This toolkit is freely available at http://www.proteored.org/MIAPE/.
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37
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Helsens K, Brusniak MY, Deutsch E, Moritz RL, Martens L. jTraML: an open source Java API for TraML, the PSI standard for sharing SRM transitions. J Proteome Res 2011; 10:5260-3. [PMID: 21967198 PMCID: PMC3208355 DOI: 10.1021/pr200664h] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
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We here present jTraML, a Java API for the Proteomics Standards Initiative TraML data standard. The library provides fully functional classes for all elements specified in the TraML XSD document, as well as convenient methods to construct controlled vocabulary-based instances required to define SRM transitions. The use of jTraML is demonstrated via a two-way conversion tool between TraML documents and vendor specific files, facilitating the adoption process of this new community standard. The library is released as open source under the permissive Apache2 license and can be downloaded from http://jtraml.googlecode.com. TraML files can also be converted online at http://iomics.ugent.be/jtraml. The jTraML library provides a freely available and permissively licensed open source Java API for creating and parsing TraML files, the PSI standard for communicating SRM assays. We also used jTraML to build command line and Web applications that convert vendor specific files to TraML and vice versa.
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Affiliation(s)
- Kenny Helsens
- Department of Medical Protein Research, VIB , Ghent, Belgium
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Martens L. Data management in mass spectrometry-based proteomics. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2011; 728:321-32. [PMID: 21468958 DOI: 10.1007/978-1-61779-068-3_21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Mass spectrometry-based proteomics has made the transition from the analysis of a single or only a few proteins per experiment to a high-throughput platform for discovery/validation that can analyze several hundreds to thousands of proteins in a single experiment. This increase in analytical capability hinged on four main components: (1) innovative methodologies, (2) improved instruments, (3) ready availability of comprehensive protein sequence databases, and (4) development of sophisticated software algorithms to match fragmentation mass spectra against these databases. But as the throughput of the approach increased, so did the necessity to manage and automate the data processing workflow. Indeed, modern instruments generate tens of thousands of fragmentation spectra per hour, providing a substantial bioinformatics challenge. This chapter provides insight into the specifics of this challenge, by looking at a typical workflow, the data types and user roles involved, and a broad overview of available software solutions. Finally, the increasingly important link between a local data management system and the global, centralized dissemination of proteomics data is discussed.
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Affiliation(s)
- Lennart Martens
- Department of Medical Protein Science, Universiteit Gent - VIB, B-9000 Gent, Belgium.
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Eisenacher M, Schnabel A, Stephan C. Quality meets quantity - quality control, data standards and repositories. Proteomics 2011; 11:1031-6. [DOI: 10.1002/pmic.201000441] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2010] [Revised: 11/03/2010] [Accepted: 11/03/2010] [Indexed: 12/23/2022]
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Isserlin R, El-Badrawi RA, Bader GD. The Biomolecular Interaction Network Database in PSI-MI 2.5. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2011; 2011:baq037. [PMID: 21233089 PMCID: PMC3021793 DOI: 10.1093/database/baq037] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The Biomolecular Interaction Network Database (BIND) is a major source of curated biomolecular interactions, which has been unmaintained for the last few years, a trend which will eventually result in the loss of a significant amount of unique biomolecular interaction information, mostly as database identifiers become out of date. To help reverse this trend, we converted BIND to a standard format, Proteomics Standard Initiative-Molecular Interaction 2.5, starting from the last curated data release (from 2005) available in a custom XML format and made the core components (interactions and complexes) plus additional valuable curated information available for download (http://download.baderlab.org/BINDTranslation/). Major work during the conversion process was required to update out of date molecule identifiers resulting in a more comprehensive conversion of BIND, by measures including number of species and interactor types covered, than what is currently accessible elsewhere. This work also highlights issues of data modeling, controlled vocabulary adoption and data cleaning that can serve as a general case study on the future compatibility of interaction databases. Database URL: http://download.baderlab.org/BINDTranslation/
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Affiliation(s)
- Ruth Isserlin
- The Donnelly Centre, University of Toronto, ON, Canada
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Abstract
The groundwork allowing the systematic capture of proteomics data has now largely been completed, with the design and publication of exchange formats and interchange standards by the Human Proteome Organisation Proteomics Standards Initiative (HUPO-PSI). Our focus can now shift to gathering the ever-increasing amounts of generated data, and finding novel ways to catalog and present it so that a deeper understanding of basic science, health, and disease can be gained by scientists mining these increasingly rich resources.
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Martens L, Chambers M, Sturm M, Kessner D, Levander F, Shofstahl J, Tang WH, Römpp A, Neumann S, Pizarro AD, Montecchi-Palazzi L, Tasman N, Coleman M, Reisinger F, Souda P, Hermjakob H, Binz PA, Deutsch EW. mzML--a community standard for mass spectrometry data. Mol Cell Proteomics 2011; 10:R110.000133. [PMID: 20716697 PMCID: PMC3013463 DOI: 10.1074/mcp.r110.000133] [Citation(s) in RCA: 451] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2010] [Revised: 07/26/2010] [Indexed: 12/27/2022] Open
Abstract
Mass spectrometry is a fundamental tool for discovery and analysis in the life sciences. With the rapid advances in mass spectrometry technology and methods, it has become imperative to provide a standard output format for mass spectrometry data that will facilitate data sharing and analysis. Initially, the efforts to develop a standard format for mass spectrometry data resulted in multiple formats, each designed with a different underlying philosophy. To resolve the issues associated with having multiple formats, vendors, researchers, and software developers convened under the banner of the HUPO PSI to develop a single standard. The new data format incorporated many of the desirable technical attributes from the previous data formats, while adding a number of improvements, including features such as a controlled vocabulary with validation tools to ensure consistent usage of the format, improved support for selected reaction monitoring data, and immediately available implementations to facilitate rapid adoption by the community. The resulting standard data format, mzML, is a well tested open-source format for mass spectrometer output files that can be readily utilized by the community and easily adapted for incremental advances in mass spectrometry technology.
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Affiliation(s)
- Lennart Martens
- From the ‡Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium
- §Department of Biochemistry, Ghent University, B-9000 Ghent, Belgium
| | | | - Marc Sturm
- ‖Eberhard Karls University, 72074, Tübingen, Germany
| | - Darren Kessner
- **University of Southern California, Los Angeles, CA, 90089, USA
| | - Fredrik Levander
- ‡‡Department of Immunotechnology and CREATE Health, Lund University, 22362, Lund, Sweden
| | - Jim Shofstahl
- §§Thermo Fisher Scientific, San Jose, CA, 95134, USA
| | | | | | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry, 06120 Halle, Germany
| | | | - Luisa Montecchi-Palazzi
- EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB101SD, UK
| | | | | | - Florian Reisinger
- EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB101SD, UK
| | - Puneet Souda
- University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Henning Hermjakob
- EMBL Outstation, European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB101SD, UK
| | - Pierre-Alain Binz
- Geneva Bioinformatics (GeneBio) SA, 1206 Geneva, Switzerland and Swiss Institute of Bioinformatics, Geneva, Switzerland
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Gibson F, Hoogland C, Martinez-Bartolomé S, Medina-Aunon JA, Albar JP, Babnigg G, Wipat A, Hermjakob H, Almeida JS, Stanislaus R, Paton NW, Jones AR. The gel electrophoresis markup language (GelML) from the Proteomics Standards Initiative. Proteomics 2010; 10:3073-81. [PMID: 20677327 PMCID: PMC3193076 DOI: 10.1002/pmic.201000120] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2010] [Accepted: 06/09/2010] [Indexed: 11/11/2022]
Abstract
The Human Proteome Organisation's Proteomics Standards Initiative has developed the GelML (gel electrophoresis markup language) data exchange format for representing gel electrophoresis experiments performed in proteomics investigations. The format closely follows the reporting guidelines for gel electrophoresis, which are part of the Minimum Information About a Proteomics Experiment (MIAPE) set of modules. GelML supports the capture of metadata (such as experimental protocols) and data (such as gel images) resulting from gel electrophoresis so that laboratories can be compliant with the MIAPE Gel Electrophoresis guidelines, while allowing such data sets to be exchanged or downloaded from public repositories. The format is sufficiently flexible to capture data from a broad range of experimental processes, and complements other PSI formats for MS data and the results of protein and peptide identifications to capture entire gel-based proteome workflows. GelML has resulted from the open standardisation process of PSI consisting of both public consultation and anonymous review of the specifications.
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Affiliation(s)
- Frank Gibson
- School of Computing Science, Newcastle University, Newcastle, UK
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Orchard S, Albar JP, Deutsch EW, Eisenacher M, Binz PA, Hermjakob H. implementing data standards: a report on the HUPOPSI workshop September 2009, Toronto, Canada. Proteomics 2010; 10:1895-8. [PMID: 20623474 DOI: 10.1002/pmic.201090034] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The plenary session of the Proteomics Standards Initiative of the Human Proteome Organisation at the 8th Annual HUPO World Congress updated the delegates on the current status of the ongoing work of this group. The mass spectrometry group reviewed the progress of mzML since its release last year and detailed new work on providing a common format for SRM/MRM transition lists (TraML). The implementation of mzIdentML, for describing the output of proteomics search engines, was outlined and the release of a new web service PSICQUIC, which allows users to simultaneously search multiple interaction databases, was announced. Finally, the audience participated in a lively debate, discussing both the benefits of these standard formats and issues with their adoption and use in a research environment.
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Affiliation(s)
- Sandra Orchard
- EMBL Outstation - European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
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Côté RG, Reisinger F, Martens L. jmzML, an open-source Java API for mzML, the PSI standard for MS data. Proteomics 2010; 10:1332-5. [PMID: 20127693 DOI: 10.1002/pmic.200900719] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
We here present jmzML, a Java API for the Proteomics Standards Initiative mzML data standard. Based on the Java Architecture for XML Binding and XPath-based XML indexer random-access XML parser, jmzML can handle arbitrarily large files in minimal memory, allowing easy and efficient processing of mzML files using the Java programming language. jmzML also automatically resolves internal XML references on-the-fly. The library (which includes a viewer) can be downloaded from http://jmzml.googlecode.com.
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Affiliation(s)
- Richard G Côté
- EMBL Outstation, European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK
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Orchard S, Aranda B, Hermjakob H. The publication and database deposition of molecular interaction data. ACTA ACUST UNITED AC 2010; Chapter 25:25.3.1-25.3.13. [PMID: 20393973 DOI: 10.1002/0471140864.ps2503s60] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Depositing data to a public domain interaction database not only improves the quality and quantity of interactions available to the user community, but also increases the visibility of the data, with members of the International Molecular Exchange (IMEx) databases making the information available in all participating resources. Datasets submitted prior to publication will be issued an accession number that may be included in a publication and which increases user accessibility to the data. No dataset is too small for submission, and the database curators will provide assistance in ensuring the information is correctly represented. This unit provides several alternative protocols to assist the author in preparing and submitting data as an integral part of the manuscript-preparation process. Which method the author selects is largely dictated by the amount of data to be deposited. In addition, two support protocols describe assignment of unambiguous accession numbers and use of controlled vocabulary terms.
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Affiliation(s)
- Sandra Orchard
- European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
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