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

Jacobsen, Julius O B; Baudis, Michael; Baynam, Gareth S; Beckmann, Jacques S; Beltran, Sergi; et al (2021). The GA4GH Phenopacket schema: A computable representation of clinical data for precision medicine. medRxiv 21266944, Cold Spring Harbor Laboratory.

Abstract

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 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.

Additional indexing

Item Type:Working Paper
Communities & Collections:07 Faculty of Science > Institute of Molecular Life Sciences
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:30 November 2021
Deposited On:12 Dec 2021 07:18
Last Modified:22 Sep 2023 12:29
Series Name:medRxiv
ISSN:0959-535X
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1101/2021.11.27.21266944
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  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

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