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The GA4GH Phenopacket schema: A computable representation of clinical data for precision medicine [article]

Julius OB Jacobsen, Michael Baudis, Gareth S Baynam, Jacques S Beckmann, Sergi Beltran, Tiffany J Callahan, Christopher G Chute, Melanie Courtot, Daniel Danis, Olivier Elemento, Robert R Freimuth, Michael A Gargano (+35 others)
2021 medRxiv   pre-print

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https://web.archive.org/web/20220201005158/https://www.medrxiv.org/content/medrxiv/early/2021/11/30/2021.11.27.21266944.full.pdf

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Despite great strides in the development and wide acceptance of standards for exchanging structured information about genomic variants, there is no corresponding standard for exchanging phenotypic data, and this has impeded the sharing of phenotypic information for computational analysis. Here, we introduce the Global Alliance for Genomics and Health (GA4GH) Phenopacket schema, which supports exchange of computable longitudinal case-level phenotypic information for diagnosis and research of all
more » ... types of disease including Mendelian and complex genetic diseases, cancer, and infectious diseases. To support translational research, diagnostics, and personalized healthcare, phenopackets are designed to be used across a comprehensive landscape of applications including biobanks, databases and registries, clinical information systems such as Electronic Health Records, genomic matchmaking, diagnostic laboratories, and computational tools. The Phenopacket schema is a freely available, community-driven standard that streamlines exchange and systematic use of phenotypic data and will facilitate sophisticated computational analysis of both clinical and genomic information to help improve our understanding of diseases and our ability to manage them.
doi:10.1101/2021.11.27.21266944 fatcat:rv7ksvht45dn5idczjwxdgjy5y
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Julius OB Jacobsen, Michael Baudis, Gareth S Baynam, Jacques S Beckmann, Sergi Beltran, Tiffany J Callahan, Christopher G Chute, Melanie Courtot, Daniel Danis, Olivier Elemento, Robert R Freimuth, Michael A Gargano, Tudor Groza, Ada Hamosh, Nomi L Harris, Rajaram Kaliyaperumal, Aly Khalifa, Peter M Krawitz, Sebastian Koehler, Brian J Laraway, Heikki Lehvaeslaiho, Kent C Lloyd, Leslie Matalonga, Julie A McMurry, Alejandro Metke-Jimenez, Christopher J Mungall, Monica C Munoz-Torres, Soichi Ogishima, Anastasios Papakonstantinou, Davide Piscia, Nikolas Pontikos, Nuria Queralt-Rosinach, Marco Roos, Paul N Schofield, Anastasios Siapos, Damian Smedley, Lindsay D Smith, Robin Steinhaus, Jagadish Chandrabose Sundaramurthi, Emilia M Swietlik, Sylvia Thun, Nicole A Vasilevsky, Alex H Wagner, Jeremy L Warner, Claus Weiland, Melissa A Haendel, Peter N Robinson. "The GA4GH Phenopacket schema: A computable representation of clinical data for precision medicine." medRxiv (2021)