The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

VarioML framework for comprehensive variation data representation and exchange

På svenska

Author

  • Myles Byrne
  • Ivo F. A. C. Fokkema
  • Owen Lancaster
  • Tomasz Adamusiak
  • Anni Ahonen-Bishopp
  • David Atlan
  • Christophe Beroud
  • Michael Cornell
  • Raymond Dalgleish
  • Andrew Devereau
  • George P. Patrinos
  • Morris A. Swertz
  • Peter E. M. Taschner
  • Gudmundur A. Thorisson
  • Mauno Vihinen
  • Anthony J. Brookes
  • Juha Muilu
Show all

Summary, in English

Background: Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. Results: The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e. g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. Conclusions: VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

Publishing year

2012

Language

English

Publication/Series

BMC Bioinformatics

Volume

13

Issue

254

Document type

Journal article

Publisher

BioMed Central (BMC)

Topic

  • Bioinformatics and Systems Biology

Keywords

  • LSDB
  • Variation database curation
  • Data collection
  • Distribution

Status

Published

Research group

  • Protein Bioinformatics

ISBN/ISSN/Other

  • ISSN: 1471-2105