ArticleAmerican journal of human genetics2026
GA4GH phenopacket-driven characterization of genotype-phenotype correlations in Mendelian disorders.
Article in American journal of human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Building an Interoperable Rare Disease Multi-omic Resource: The GREGoR Data Model and Dataset.bioRxiv : the preprint server for biology · 2026Article
- Proceedings of the second Artificial Intelligence in Primary Immunodeficiency (AIPI) meeting.The Journal of allergy and clinical immunology · 2026Article
- RareLink: scalable REDCap-based framework for rare disease interoperability linking international registries to FHIR and Phenopackets.NPJ genomic medicine · 2025Article
- Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability.medRxiv : the preprint server for health sciences · 2025Article
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34 authors.
Funding
Abstract
Comprehensively characterizing genotype-phenotype correlations (GPCs) in Mendelian disease would create new opportunities for improving clinical management and understanding disease biology. However, heterogeneous approaches to data sharing, reuse, and analysis have hindered progress in the field. We developed Genotype-Phenotype Statistical Evaluation of Associations (GPSEA), a software package that leverages the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema to represent case-level clinical and genetic data about individuals. GPSEA applies an independent filtering strategy to boost statistical power to detect categorical GPCs represented by Human Phenotype Ontology terms. GPSEA additionally enables visualization and analysis of continuous phenotypes, clinical severity scores, and survival data such as age of onset of disease or clinical manifestations. We applied GPSEA to 85 cohorts with 6,179 previously published individuals with variants in one of 81 genes associated with 122 Mendelian diseases and identified 253 significant GPCs, with 48 cohorts having at least one statistically significant GPC. These results highlight the power of standardized representations of clinical data for scalable discovery of GPCs in Mendelian disease.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.