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International audience; To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

This report summarizes the proceedings of the one day BioSharing meeting held at the Intelligent Systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://biosharing.org.

The XML-based Real-Time PCR Data Markup Language (RDML) has been developed by the RDML consortium (http://www.rdml.org) to enable straightforward exchange of qPCR data and related information between qPCR instruments and third party data analysis software, between colleagues and collaborators and between experimenters and journals or public repositories. We here also propose data related guidelines as a subset of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) to guarantee inclusion of key data information when reporting experimental results.

This article summarizes the motivation for, and the proceedings of, the first ISA-TAB workshop held December 6–8, 2007, at the EBI, Cambridge, UK. This exploratory workshop, organized by members of the Microarray Gene Expression Data (MGED) Society's Reporting Structure for Biological Investigations (RSBI) working group, brought together a group of developers of a range of collaborative systems to discuss the use of a common format to address the pressing need of reporting and communicating data and metadata from biological, biomedical, and environmental studies employing combinations of genomics, transcriptomics, proteomics, and metabolomics technologies along with more conventional methodologies. The expertise of the participants comprised database development, data management, and hands-on experience in the development of data communication standards. The workshop's outcomes are set to help formalize the proposed Investigation, Study, Assay (ISA)-TAB tab-delimited format for representing and c...

In this article we present the activities of the Ontology Working Group (OWG) under the Metabolomics Standards Initiative (MSI) umbrella. Our endeavour aims to synergise the work of several communities, where independent activities are underway to develop terminologies and databases for metabolomics investigations. We have joined forces to rise to the challenges associated with interpreting and integrating experimental process and data across disparate sources (software and databases, private and public). Our focus is to support the activities of the other MSI working groups by developing a common semantic framework to enable metabolomics-user communities to consistently annotate the experimental process and to enable meaningful exchange of datasets. Our work is accessible via a public webpage and a draft ontology has been posted under the Open Biological Ontology umbrella. At the very outset, we have agreed to minimize duplications across omics domains through extensive liaisons with other communities under the OBO Foundry. This is work in progress and we welcome new participants willing to volunteer their time and expertise to this open effort.

This briefing lays out the initial objectives and intent of the Data Exchange Working Group of the Metabolomics Standards Initiative (MSI), which operates under the aegis of the Metabolomics Society. The MSI has now reached a significant milestone in publishing a complete set of draft reporting requirements, simultaneously providing to the Data Exchange Working Group a set of drivers that function, for our purposes, as a series of specifications of the data and metadata that the products endorsed or developed by the Data Exchange Working Group should be able to effectively contain. We here describe our view of the existing resources that can be put to use, the ‘functionality gaps’ that need to be filled and the way in which we envisage these existing and planned resources fitting together to provide a framework that firstly, answers the needs of the metabolomics community and secondly, addresses the issues raised by the prospect of integrating metabolomics workflow descriptions and data with that from other domains, such as proteomics, genomics and transcriptomics.

Groups representing a number of domains in the life sciences have been developing specifications and resources for the description and transmission of data, including those produced by (high-throughput) omics technologies. Although these developments are individually valuable, there is now a need for coordination to avoid the problem of a multiplicity of competing candidate standards. Three ongoing collaborative projects (FuGE, OBI and MIBBI) offer the promise of support for truly integrated, cross-domain informatics solutions. This article briefly summarizes the status quo with respect to biological and biomedical data standards, and offers an assessment of coming developments.

Amongst other functions, the Human Proteome Organization's Proteomics Standards Initiative (HUPO PSI) facilitates the generation by the proteomics community of guidelines that specify the appropriate level of detail to provide when describing the various components of a proteomics experiment. These guidelines are codified as the MIAPE (Minimum Information About a Proteomics Experiment) specification, the first modules of which are now finalized. This primer describes the structure and scope of MIAPE, places it in context amongst reporting specifications for other domains, briefly discusses related informatics resources and closes by considering the ramifications for the proteomics community.

The theme of the third annual Spring workshop of the HUPO-PSI was "proteomics and beyond" and its underlying goal was to reach beyond the boundaries of the proteomics community to interact with groups working on the similar issues of developing interchange standards and minimal reporting requirements. Significant developments in many of the HUPO-PSI XML interchange formats, minimal reporting requirements and accompanying controlled vocabularies were reported, with many of these now feeding into the broader efforts of the Functional Genomics Experiment (FuGE) data model and Functional Genomics Ontology (FuGO) ontologies.

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the “semantic glue” to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.

The autumn workshop of the Proteomics Standards Initiative of the Human Proteomics Organisation met to further advance the development of the existing standards in the fields of molecular interactions and mass spectrometry. In addition, new areas were addressed, in particular developing standards for the description and exchange of data from gel electrophoresis experiments. The General Proteomics Standards group is now working closely with the FuGE (Functional Genomics Experiment) efforts to define a general standard in which to encode data that will enable a systems biology approach to data analysis. Common to all these efforts is the field of protein modifications, and work has been initiated to establish an ontology in this field that can be used by both workers in the field of proteomics and the wider scientific community.

The spring workshop of the HUPO-PSI convened in Siena to further progress the data standards which are already making an impact on data exchange and deposition in the field of proteomics. Separate work groups pushed forward existing XML standards for the exchange of Molecular Interaction data (PSI-MI, MIF) and Mass Spectrometry data (PSI-MS, mzData) whilst significant progress was made on PSI-MS' mzIdent, which will allow the capture of data from analytical tools such as peak list search engines. A new focus for PSI (GPS, gel electrophoresis) was explored; as was the need for a common representation of protein modifications by all workers in the field of proteomics and beyond. All these efforts are contextualised by the work of the General Proteomics Standards workgroup; which in addition to the MIAPE reporting guidelines, is continually evolving an object model (PSI-OM) from which will be derived the general standard XML format for exchanging data between researchers, and for submission to repositories or journals.

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

Development of high-throughput genomic and postgenomic technologies has caused a change in approaches to data handling and processing ( 1 ). One biological sample might be used to generate many kinds of “big” data in parallel, such as genome sequence (genomics), patterns of gene and protein expression (transcriptomics and proteomics), and metabolite concentrations and fluxes (metabolomics). Extensive computer manipulations are required for even basic analyses of such data; the challenges mount further when two or more studies' outputs must be compared or integrated.

In 2005, the Metabolomics Standards Initiative has been formed. An outline and general introduction is provided to inform about the history, structure, working plan and intentions of this initiative. Comments on any of the suggested minimal reporting standards are welcome to be sent to the open email list Msi-workgroups-feedback@lists.sourceforge.net

Since its conception in April 2002, the Human Proteome Organisation Proteomics Standards Initiative has contributed to the development of community standards for proteomics in a collaborative and very dynamic manner, resulting in the publication and increasing adoption of a number of interchange formats and controlled vocabularies. Repositories supporting these formats are being established or are already operational. In parallel with this, minimum reporting requirement have been developed and are now maturing to the point where they have been submitted for journal publication after prolonged exposure to community-input via the PSI website.

The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.

The need for common standards in the field of proteomics, to allow the transfer and public domain deposition of proteomic data, is now widely recognized. The Proteomics Standards Initiative (PSI) s...

The increasing volume of proteomics data currently being generated by increasingly high-throughput methodologies has led to an increasing need for methods by which such data can be accurately described, stored and exchanged between experimental researchers and data repositories. Work by the Proteomics Standards Initiative of the Human Proteome Organisation has laid the foundation for the development of standards by which experimental design can be described and data exchange facilitated. The progress of these efforts, and the direct benefits already accruing from them, were described at a plenary session of the 3(rd) Annual HUPO congress. Parallel sessions allowed the three work groups to present their progress to interested parties and to collect feedback from groups already implementing the available formats.

This chapter introduces the problems experimentalists in all sectors face in utilizing third party data sets given the unhelpful wealth of formats and terminologies and the consequent mountain of technical frameworks needed to achieve data interoperability. We argue on the importance of a complementary set of open standards, the challenges we must overcome and the role the BioSharing effort is set to play. As an example of progress, we present the open source ISA software solution in action during the curation of the InnoMed PredTox data set, along with its growing active developer and user community, including academia and industrial sectors, such as The Novartis Institutes for BioMedical Research and Janssen Research & Development.

The functionality of the proteins used in biological experiments is very often not assessed at all. Our initiative is aimed at making the scientific community aware about this problem and proposes a first checklist for data reporting. doi:10.4056/sigs.1834511

To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data.

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.

Summary: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories. Availability and Implementation: Software, documentation, case studies and implementations at http://www.isa-tools.org Contact: isatools@googlegroups.com

Fuelled by the fruits of the genome sequencing projects that are defining the complete sets of genes, transcripts, and proteins within an organism and the advent of highly multiplex technologies capable of measuring thousands to millions of biomolecules per sample in one assay, functional genomics studies are enabling new approaches for studying biological systems. A single experiment can generate very large amounts of raw data as well as summaries in the form of lists of sequences, genes, proteins, metabolites, SNPs, etc. which have been identified by various analytical tests. Managing, reporting, and integrating the results from these experiments present challenges to researchers and bioinformaticians in this relatively young field because the standards and conventions developed for single-gene or single-protein studies do not accommodate the needs of functional genomics studies (Boguski 1999). Functional genomics technologies and their applications are evolving rapidly, and there is widespread awareness of the need for, and value of, standards in the life sciences community. Not only do the widely-adopted standards help scientists and data analysts utilize the ever-growing mountain of functional genomics data sets better, they also are essential for the application of functional genomics approaches in healthcare environments. This chapter provides an introduction to the major functional genomics standards initiatives in the domains of genomics, transcriptomics, proteomics, and metabolomics, thereby providing a summary of goals, example applications, and references for further information. It also covers the application of standards in healthcare settings, where functional genomics technologies are having an increasing impact. New standards and organizations may come along in the future that will augment or ­supersede the ones described here. Interested readers are invited to further explore the s­tandards mentioned in this chapter (as well as others not mentioned) and keep up with the latest developments by visiting the website http://biostandards.info.

International audience; the MIAPE Gel Electrophoresis (MIAPE-GE) guidelines specify the minimum information that should be provided when reporting the use of n-dimensional gel electrophoresis in a proteomics experiment. Developed through a joint effort between the gel-based analysis working group of the Human Proteome Organisation's Proteomics Standards Initiative (HUPO-PSI; http://www.psidev.info/) and the wider proteomics community, they constitute one part of the overall Minimum Information about a Proteomics Experiment (MIAPE) documentation system published last August in Nature Biotechnology

International audience

The extent of linkage disequilibrium (LD) is an important factor when designing experiments for mapping disease or trait loci using LD mapping methods. It depends on the population history and hence is a characteristic of each population. Here, we have assessed the extent of LD in a sub-isolate of the general Sardinian population (775 members of one village) using 22 polymorphic markers on chromosome 19. We found high levels of disequilibrium that extended to 8 cM, when based on D', and 11 cM when based on the significance level of the allelic association. The fact that conclusions based on both methods are similar suggests that the estimates are quite robust. We have also shown, through a simple resampling technique, that small sample sizes can overestimate both the mean value of D' and its variance up to a factor of about 2 and 16, respectively, when the number of diplotypes (the pair of haplotypes that compose the genotype) decreased from 186 to 26. We evaluated the effect on D' of the depth of the pedigree available when using phased founders, and compared the estimates with those obtained when using unphased founders, and also the effect of grouping alleles on the value of D' and the significance level. Owing to the high sampling variance of LD, we recommend the use of at least 200 unrelated individuals when characterizing the extent of LD

With the quantity of genomic data increasing at an exponential rate, it is imperative that these data be captured electronically, in a standard format. Standardization activities must proceed within the auspices of open-access and international working bodies. To tackle the issues surrounding the development of better descriptions of genomic investigations, we have formed the Genomic Standards Consortium (GSC). Here, we introduce the minimum information about a genome sequence (MIGS) specification with the intent of promoting participation in its development and discussing the resources that will be required to develop improved mechanisms of metadata capture and exchange. As part of its wider goals, the GSC also supports improving the 'transparency' of the information contained in existing genomic databases.

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.

A number of research groups are generating standard mechanisms and prescriptions for reporting various kinds of biological and biomedical experiments. The motives for this generation include concern about the longevity of data sets (and the robustness of conclusions built upon them), the desire to integrate data from diverse scientific disciplines, and the facility to productively mine accrued data. The pharmaceutical industry continues to play a significant role in the genesis and development of such standards, in conjunction with technology vendors and academia. This review describes the context and nature of the new candidate standards and discusses their relevance to drug discovery and development.

Both the generation and the analysis of proteomics data are now widespread, and high-throughput approaches are commonplace. Protocols continue to increase in complexity as methods and technologies evolve and diversify. To encourage the standardized collection, integration, storage and dissemination of proteomics data, the Human Proteome Organization's Proteomics Standards Initiative develops guidance modules for reporting the use of techniques such as gel electrophoresis and mass spectrometry. This paper describes the processes and principles underpinning the development of these modules; discusses the ramifications for various interest groups such as experimentalists, funders, publishers and the private sector; addresses the issue of overlap with other reporting guidelines; and highlights the criticality of appropriate tools and resources in enabling 'MIAPE-compliant' reporting.

In 2005, the Metabolomics Standards Initiative has been formed. An outline and general introduction is provided to inform about the history, structure, working plan and intentions of this initiative. Comments on any of the suggested minimal reporting standards are welcome to be sent to the open email list Msi-workgroups-feedback@lists.sourceforge.net. © Springer Science+Business Media, LLC 2007.

The newly available techniques for sensitive proteome analysis and the resulting amount of data require a new bioinformatics focus on automatic methods for spectrum reprocessing and peptide/protein validation. Manual validation of results in such studies is not feasible and objective enough for quality relevant interpretation. The necessity for tools enabling an automatic quality control is, therefore, important to produce reliable and comparable data in such big consortia as the Human Proteome Organization Brain Proteome Project. Standards and well-defined processing pipelines are important for these consortia. We show a way for choosing the right database model, through collecting data, processing these with a decoy database and end up with a quality controlled protein list merged from several search engines, including a known false-positive rate.

This article describes the origins, working practices and various development projects of the HUman Proteome Organisation's Proteomics Standards Initiative (HUPO PSI), specifically, our work on reporting requirements, data exchange formats and controlled vocabulary terms. We also offer our view of the two functional genomics projects in which the PSI plays a role (FuGE and FuGO), discussing their impact on our process and laying out the benefits we see as accruing, both to the PSI and to biomedical science as a whole as a result of their widespread acceptance. This paper is part of the special issue of OMICS on data standards.

Metabolite concentrations in cellular systems are very much dependent on the physiological, environmental, and genetic status of an organism and are regarded as the ultimate result of cellular regulation, resulting in the visible phenotypes. Therefore, the comprehensive analysis of metabolite levels and fluxes renders a suitable tool for assessing the degree of perturbation in biological systems. Lessons derived from development of other OMICS areas (genomics, proteomics, and transcriptomics) have shown that large-scale comparisons and interpretations will require the re-use of data over long periods of time and by multiple laboratories with different expertise and backgrounds. Reaching this goal will require standardization of reporting structures of metabolomic studies for journal publication purposes, for regulatory deposition, and for database dissemination. An initiative by the Metabolomics Society is presented that aims to define important aspects of metabolomic workflows. These include biological study designs, chemical analysis, and data processing, as well as the ontologies that are necessary in this framework. © Mary Ann Liebert, Inc.

PRIDE, the 'PRoteomics IDEntifications database' (http://www.ebi.ac.uk/pride) is a database of protein and peptide identifications that have been described in the scientific literature. These identifications will typically be from specific species, tissues and subcellular locations, perhaps under specific disease conditions. Any post-translational modifications that have been identified on individual peptides can be described. These identifications may be annotated with supporting mass spectra. At the time of writing, PRIDE includes the full set of identifications as submitted by individual laboratories participating in the HUPO Plasma Proteome Project and a profile of the human platelet proteome submitted by the University of Ghent in Belgium. By late 2005 PRIDE is expected to contain the identifications and spectra generated by the HUPO Brain Proteome Project. Proteomics laboratories are encouraged to submit their identifications and spectra to PRIDE to support their manuscript submissions to proteomics journals. Data can be submitted in PRIDE XML format if identifications are included or mzData format if the submitter is depositing mass spectra without identifications. PRIDE is a web application, so submission, searching and data retrieval can all be performed using an internet browser. PRIDE can be searched by experiment accession number, protein accession number, literature reference and sample parameters including species, tissue, sub-cellular location and disease state. Data can be retrieved as machine-readable PRIDE or mzData XML ( the latter for mass spectra without identifications), or as human-readable HTML.

The pilot phase of the HUPO Plasma Proteome Project (PPP) is an international collaboration to catalog the protein composition of human blood plasma and serum by analyzing standardized aliquots of reference serum and plasma specimens using a variety of experimental techniques. Data management for this project included collection, integration, analysis, and dissemination of findings from participating organizations world-wide. Accomplishing this task required a communication and coordination infrastructure specific enough to support meaningful integration of results from all participants, but flexible enough to react to changing requirements and new insights gained during the course of the project and to allow participants with varying informatics capabilities to contribute. Challenges included integrating heterogeneous data, reducing redundant information to minimal identification sets, and data annotation. Our data integration workflow assembles a minimal and representative set of protein identifications, which account for the contributed data. It accommodates incomplete concordance of results from different laboratories, ambiguity and redundancy in contributed identifications, and redundancy in the protein sequence databases. Recommendations of the PPP for future large-scale proteomics endeavors are described.

The generation of proteomic data is becoming ever more high throughput. Both the technologies and experimental designs used to generate and analyze data are becoming increasingly complex. The need for methods by which such data can be accurately described, stored and exchanged between experimenters and data repositories has been recognized. Work by the Proteome Standards Initiative of the Human Proteome Organization has laid the foundation for the development of standards by which experimental design can be described and data exchange facilitated. The Minimum Information About a Proteomic Experiment data model describes both the scope and purpose of a proteomics experiment and encompasses the development of more specific interchange formats such as the mzData model of mass spectrometry. The eXtensible Mark-up Language-MI data interchange format, which allows exchange of molecular interaction data, has already been published and major databases within this field are supplying data downloads in this format.

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

Background Proteomics is rapidly evolving into a high-throughput technology, in which substantial and systematic studies are conducted on samples from a wide range of physiological, developmental, or pathological conditions. Reference maps from 2D gels are widely circulated. However, there is, as yet, no formally accepted standard representation to support the sharing of proteomics data, and little systematic dissemination of comprehensive proteomic data sets. Results This paper describes the design, implementation and use of a Proteome Experimental Data Repository (PEDRo), which makes comprehensive proteomics data sets available for browsing, searching and downloading. It is also serves to extend the debate on the level of detail at which proteomics data should be captured, the sorts of facilities that should be provided by proteome data management systems, and the techniques by which such facilities can be made available. Conclusions The PEDRo database provides access to a collection of comprehensive descriptions of experimental data sets in proteomics. Not only are these data sets interesting in and of themselves, they also provide a useful early validation of the PEDRo data model, which has served as a starting point for the ongoing standardisation activity through the Proteome Standards Initiative of the Human Proteome Organisation.