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A corpus of GA4GH phenopackets: Case-level phenotyping for genomic diagnostics and discovery
D. Danis, MJ. Bamshad, Y. Bridges, A. Caballero-Oteyza, P. Cacheiro, LC. Carmody, L. Chimirri, JX. Chong, B. Coleman, R. Dalgleish, PJ. Freeman, ASL. Graefe, T. Groza, P. Hansen, JOB. Jacobsen, A. Klocperk, M. Kusters, MS. Ladewig, AJ. Marcello,...
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
Grantová podpora
R01 HD103805
NICHD NIH HHS - United States
NLK
Directory of Open Access Journals
od 2020
PubMed Central
od 2020
ROAD: Directory of Open Access Scholarly Resources
od 2020
- MeSH
- algoritmy MeSH
- databáze genetické MeSH
- fenotyp * MeSH
- genomika * metody MeSH
- lidé MeSH
- software * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 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.
Berlin Institute of Health at Charité Universitätsmedizin Berlin Berlin Germany
Brotman Baty Institute for Precision Medicine 1959 NE Pacific Street Box 357657 Seattle WA 98195 USA
Clinic for Immunology and Rheumatology Hanover Medical School Hanover Germany
Department of Biomedical Informatics University of Colorado Anschutz Medical Campus Aurora CO USA
Department of Genetics Genomics and Cancer Sciences University of Leicester Leicester UK
Department of Ophthalmology University Clinic Marburg Campus Fulda Fulda Germany
Division of Informatics Imaging and Data Science The University of Manchester Manchester UK
ELLIS European Laboratory for Learning and Intelligent Systems
German Center for Child and Adolescent Health partner site Leipzig Dresden Dresden Germany
Medica Genetics University of Catania Italy Catania Italy
Morgagni Foundation and Clinic Catania Italy
North West Thames Regional Genetics Service Northwick Park and St Mark's Hospitals London UK
Rare Care Centre Perth Children's Hospital Nedlands WA 6009 Australia
RESiST Cluster of Excellence 2155 Hanover Medical School Hanover Germany
Telethon Kids Institute Nedlands WA 6009 Australia
The Jackson Laboratory for Genomic Medicine 10 Discovery Drive Farmington CT 06032 USA
University College London Institute of Child Health London UK
University of North Carolina at Chapel Hill Chapel Hill NC USA
Utrecht University Utrecht the Netherlands
William Harvey Research Institute Queen Mary University of London London UK
Citace poskytuje Crossref.org
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