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A corpus of GA4GH phenopackets: Case-level phenotyping for genomic diagnostics and discovery.

Daniel Danis·Michael J Bamshad·Yasemin Bridges·Andrés Caballero-Oteyza·Pilar Cacheiro·Leigh C Carmody·Leonardo Chimirri·Jessica X Chong·Ben Coleman·Raymond Dalgleish·Peter J Freeman·Adam S L Graefe·Tudor Groza·Peter Hansen·Julius O B Jacobsen·Adam Klocperk·Maaike Kusters·Markus S Ladewig·Allison J Marcello·Teresa Mattina·Christopher J Mungall·Monica C Munoz-Torres·Justin T Reese·Filip Rehburg·Bárbara C S Reis·Catharina Schuetz·Damian Smedley·Timmy Strauss·Jagadish Chandrabose Sundaramurthi·Sylvia Thun·Kyran Wissink·John F Wagstaff·David Zocche·Melissa A Haendel·Peter N Robinson
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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. 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.

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HumansPhenotypeGenomicsSoftwareDatabases, Geneticglobal alliance for genomics and healthhuman phenotype ontologyphenopacket schemaJournal Article

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Daniel Danis, Michael J Bamshad, Yasemin Bridges, Andrés Caballero-Oteyza, Pilar Cacheiro, Leigh C Carmody, Leonardo Chimirri, Jessica X Chong, Ben Coleman, Raymond Dalgleish, Peter J Freeman, Adam S L Graefe, Tudor Groza, Peter Hansen, Julius O B Jacobsen, Adam Klocperk, Maaike Kusters, Markus S Ladewig, Allison J Marcello, Teresa Mattina, Christopher J Mungall, Monica C Munoz-Torres, Justin T Reese, Filip Rehburg, Bárbara C S Reis, Catharina Schuetz, Damian Smedley, Timmy Strauss, Jagadish Chandrabose Sundaramurthi, Sylvia Thun, Kyran Wissink, John F Wagstaff, David Zocche, Melissa A Haendel, Peter N Robinson. 2024-10-10. A corpus of GA4GH phenopackets: Case-level phenotyping for genomic diagnostics and discovery.. https://doi.org/10.1016/j.xhgg.2024.100371

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