Abstract
BackgroundSharing 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.ResultsThe 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.ConclusionsVarioML 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.
Highlights
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
Elements can be extended by adding new schema elements: Phenotype is an example of an observation element which reuse properties from the ontology term element
JSON is the common data serialization format recognized as the lingua franca for data exchange over the web, proven to be faster and consume fewer resources than XML [61]
Summary
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. Cost-effective sequencing, paired with variant discovery, promises to make early detection and intervention accessible for the millions of individuals with genetic diseases. Realizing this potential is blocked by the problem of integrating and coordinating the steps towards “a pipeline leading from discovery to delivery” [4]. The GEN2PHEN project was initiated in 2008 to unify human and model organism genetic variation databases, and remove the obstacles to translation of variant data from laboratory to clinic to public [5]. This has involved attempting to unify the divergent data representations of various database communities
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