A corpus of GA4GH Phenopackets: case-level phenotyping for genomic diagnostics and discovery

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Daniel Danis - , Charité – Universitätsmedizin Berlin (Author)
  • Michael J Bamshad - , Children's Hospital and Regional Medical Center Seattle (Author)
  • Yasemin Bridges - , Queen Mary University of London (Author)
  • Pilar Cacheiro - , Queen Mary University of London (Author)
  • Leigh C Carmody - , The Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA. (Author)
  • Jessica X Chong - , University of Washington (Author)
  • Ben Coleman - , The Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA. (Author)
  • Raymond Dalgleish - , University of Leicester (Author)
  • Peter J Freeman - , University of Manchester (Author)
  • Adam S L Graefe - , Charité – Universitätsmedizin Berlin (Author)
  • Tudor Groza - , Telethon Kids Institute, Nedlands, WA 6009, Australia. (Author)
  • Julius O B Jacobsen - , Queen Mary University of London (Author)
  • Adam Klocperk - , Charles University Prague, University Hospital Motol (Author)
  • Maaike Kusters - , University College London (Author)
  • Markus S Ladewig - , Klinikum Fulda gAG (Author)
  • Anthony J Marcello - , University of Washington (Author)
  • Teresa Mattina - , Morgagni foundation and Clinic, Catania, Italy. (Author)
  • Christopher J Mungall - , Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. (Author)
  • Monica C Munoz-Torres - , University of Colorado Anschutz Medical Campus (Author)
  • Justin T Reese - , Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. (Author)
  • Filip Rehburg - , Charité – Universitätsmedizin Berlin (Author)
  • Bárbara C S Reis - , High Complexity Laboratory, National Institute of Women's, Children's and Adolescents' Health Fernandes Figueira, Rio de Janeiro, Brazil. (Author)
  • Catharina Schuetz - , Department of Paediatrics, University Hospital Carl Gustav Carus Dresden, University Center for Rare Diseases (Author)
  • Damian Smedley - , Queen Mary University of London (Author)
  • Timmy Strauss - , Department of Paediatrics, University Hospital Carl Gustav Carus Dresden, University Center for Rare Diseases (Author)
  • Jagadish Chandrabose Sundaramurthi - , The Jackson Institute for Genomic Medicine, 10 Discovery Drive, Farmington CT 06032, USA. (Author)
  • Sylvia Thun - , Charité – Universitätsmedizin Berlin (Author)
  • Kyran Wissink - , Utrecht University (Author)
  • John F Wagstaff - , University of Leicester (Author)
  • David Zocche - , North West Thames Regional Genetics Service, Northwick Park & St Mark's Hospitals, London, UK. (Author)
  • Melissa A Haendel - , University of North Carolina at Chapel Hill (Author)
  • Peter N Robinson - , ELLIS-European Laboratory for Learning and Intelligent Systems. (Author)

Abstract

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present phenopacket-store. Version 0.1.12 of phenopacket-store includes 4916 phenopackets representing 277 Mendelian and chromosomal diseases associated with 236 genes, and 2872 unique pathogenic alleles curated from 605 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

Details

Original languageEnglish
JournalmedRxiv : the preprint server for health sciences
Publication statusPublished - 29 May 2024
Peer-reviewedYes

External IDs

PubMedCentral PMC11160806
ORCID /0009-0003-6519-0482/work/162845242
medrxiv 10.1101/2024.05.29.24308104_v1
unpaywall 10.1101/2024.05.29.24308104