Joint IHEC/ENCODE project “EpiShare“ selected as a Global Alliance for Genomics and Health 2019 Driver ProjectFebruary 05, 2019
In the face of a rapidly growing pool of high-quality epigenomic datasets generated and made available by initiatives around the globe, accessing and securely sharing epigenomic data remains a major challenge.
Aiming to enhance the accessibility of epigenomic datasets to facilitate further discovery and integrative analysis, IHEC and the IHEC-associated Encyclopedia of DNA Elements (ENCODE) have initiated the EpiShare project, which has now been named a Global Alliance for Genomics and Health (GA4GH) 2019 Driver Project.
Led by IHEC Working Group Chairs Guillaume Bourque (Integrative Analysis) and Yann Joly (Bioethics) – both leading experts on genomics at McGill – EpiShare will build on existing GA4GH tools, standards and online resources such as the IHEC Data Portal to develop methods and tools to easily and securely store, access, and navigate available epigenomic data. Moreover, the project will also enable the launch of multi-omics analyses on controlled-access datasets, while ensuring compliance with privacy legislation and international ethical standards. In an article recently published in the McGill Reporter Bourque and Joly share their views on why an improved sharing of epigenomic datasets is critical for the advancement of health research and personalized medicine in the future.
IHEC officially joined GA4GH as an organizational member in 2017. GA4GH is an international, nonprofit coalition of nearly 500 leading organizations and more than 1000 individuals committed to improving human health through effective and responsible sharing of genomic and clinical data. A key component of its mission is to develop and showcase tangible, innovative standards and tools that respond to particular needs of the community and help advance the field of genomic medicine and science. GA4GH Driver Projects work collaboratively to develop and pilot GA4GH standards for sharing genomic and health-related data.
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