ClinGen API platform for classification of human genetic variants
In this commentary, we describe how the Clinical Genome Resource's (ClinGen's) application programming interface-based microservices accelerate growth and dissemination of knowledge about human genetic variation. By exposing findable, accessible, interoperable, reusable, and AI-ready variant data, ClinGen lays a foundation for next-generation software applications, AI systems, and variant classification workflows.
Authors
- Gloria Cheung
- Sharon E. Plon (ORCID: https://orcid.org/0000-0002-9626-0936)
- Christine G. Preston
- Keyang Yu (ORCID: https://orcid.org/0000-0002-3880-9396)
- Kevin Riehle (ORCID: https://orcid.org/0000-0003-4888-2404)
- Bryan Wulf
- Mark E. Mandell
- Jessie Arce (ORCID: https://orcid.org/0000-0001-8750-9579)
- Teri E. Klein (ORCID: https://orcid.org/0000-0001-5527-6475)
- Miroslav Milinkov
- Andrew R. Jackson
- Dubravka Jevtic
- Malachi Griffith
- Novak Martinovic
- Aleksandar Mihajlovic
- Deborah I. Ritter
- Marina Distefano
- Melissa S. Cline
- Tierra Farris
- Aleksandar Milosavljevic
- Nevena Vucinic
- Alan F. Rubin
- Arturo Alejandro Zuniga
- Neethu Shah
- Matt W. Wright
- Obi L. Griffith
Institutions
- Broad Institute (US)
- Baylor College of Medicine (US)
- University of California, Santa Cruz (US)
- Walter and Eliza Hall Institute of Medical Research (AU)
- Washington University in St. Louis (US)
- Brooklyn Technical High School (US)
- Baylor Genetics (US)
- Stanford University (US)
Publication Details
- Journal
- Cell Genomics
- Published
- 2026-04-01
- DOI
- https://doi.org/10.1016/j.xgen.2026.101211
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Human Genome Research Institute
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
- Common Fund