Using multiplexed functional data to reduce variant classification inequities in underrepresented populations
Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.
Authors
- Douglas M. Fowler (ORCID: https://orcid.org/0000-0001-7614-1713)
- James R. Lupski (ORCID: https://orcid.org/0000-0001-9907-9246)
- Alan F. Rubin (ORCID: https://orcid.org/0000-0003-1474-605X)
- Jennifer E. Posey (ORCID: https://orcid.org/0000-0003-4814-6765)
- Shawn Fayer (ORCID: https://orcid.org/0000-0003-1883-9069)
- Sharon E. Plon (ORCID: https://orcid.org/0000-0002-9626-0936)
- Lara A. Muffley (ORCID: https://orcid.org/0000-0002-3035-3339)
- Karynne Patterson (ORCID: https://orcid.org/0000-0002-0853-1231)
- Sriram Pendyala (ORCID: https://orcid.org/0000-0003-3395-3417)
- Carla Daniela Robles‐Espinoza (ORCID: https://orcid.org/0000-0003-3277-7466)
- Willow Coyote‐Maestas (ORCID: https://orcid.org/0000-0001-9614-5340)
- Eric Venner (ORCID: https://orcid.org/0000-0002-3319-6690)
- Lea M. Starita (ORCID: https://orcid.org/0000-0003-2870-5099)
- Moez Dawood (ORCID: https://orcid.org/0000-0003-0192-1277)
- Irene Gallego Romero (ORCID: https://orcid.org/0000-0003-1613-8998)
- Mason Post (ORCID: https://orcid.org/0009-0006-4768-662X)
- Richard A. Gibbs
- Divya Kalra (ORCID: https://orcid.org/0000-0001-6580-3785)
Institutions
- The University of Melbourne (AU)
- University of California, San Francisco (US)
- Baylor College of Medicine (US)
- Walter and Eliza Hall Institute of Medical Research (AU)
- University of Washington (US)
- Wellcome Sanger Institute (GB)
- Quantitative BioSciences (US)
- Brotman Baty Institute (US)
- Texas Children's Hospital (US)
- Baylor Genetics (US)
- University of Tartu (EE)
- St Vincents Institute of Medical Research (AU)
- Australian Catholic University (AU)
- Universidad Nacional Autónoma de México (MX)
Publication Details
- Journal
- Genome Medicine
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1186/s13073-024-01392-7
- Citations
- 19
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 10.46