Literature DB >> 30311379

ClinGen advancing genomic data-sharing standards as a GA4GH driver project.

Lena Dolman1, Angela Page2, Lawrence Babb3, Robert R Freimuth4, Harindra Arachchi2,5, Chris Bizon6, Matthew Brush7, Marc Fiume1,8, Melissa Haendel7,9, David P Hansen10, Aleksandar Milosavljevic11, Ronak Y Patel11, Piotr Pawliczek11, Andrew D Yates12, Heidi L Rehm2,5,13.   

Abstract

The Clinical Genome Resource (ClinGen)'s work to develop a knowledge base to support the understanding of genes and variants for use in precision medicine and research depends on robust, broadly applicable, and adaptable technical standards for sharing data and information. To forward this goal, ClinGen has joined with the Global Alliance for Genomics and Health (GA4GH) to support the development of open, freely-available technical standards and regulatory frameworks for secure and responsible sharing of genomic and health-related data. In its capacity as one of the 15 inaugural GA4GH "Driver Projects," ClinGen is providing input on the key standards needs of the global genomics community, and has committed to participate on GA4GH Work Streams to support the development of: (1) a standard model for computer-readable variant representation; (2) a data model for linking variant data to annotations; (3) a specification to enable sharing of genomic variant knowledge and associated clinical interpretations; and (4) a set of best practices for use of phenotype and disease ontologies. ClinGen's participation as a GA4GH Driver Project will provide a robust environment to test drive emerging genomic knowledge sharing standards and prove their utility among the community, while accelerating the construction of the ClinGen evidence base.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  data sharing; genomic knowledge; phenotype ontology; standards; variant annotation; variant representation

Mesh:

Year:  2018        PMID: 30311379      PMCID: PMC6188700          DOI: 10.1002/humu.23625

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


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