O50: Multiscore, a gene ranker powered by artificial intelligence and real-world clinical data, shows high sensitivity in 10,000 exomes and genomes
Genome and exome analysis require a combination of genotype and phenotype informed strategies to allow only clinically relevant variants to be returned to the patient. Technical advances in bioinformatics, population genetics, and in silico predictors have honed our ability to elucidate the molecular strength of a variant. However, assessment of phenotype fit is complex and requires in-depth understanding of gene-disease relationships. We developed Multiscore, a gene prioritization tool powered by artificial intelligence, to facilitate gene-level predictions of phenotypic fit.
Authors
- Vincent D. Ustach (ORCID: https://orcid.org/0000-0001-8299-3998)
- Kevin J. Arvai (ORCID: https://orcid.org/0000-0001-8751-8918)
- Britt Johnson (ORCID: https://orcid.org/0000-0003-1883-5201)
- Kyle Retterer (ORCID: https://orcid.org/0000-0001-5252-2001)
- Vladimir G. Gainullin (ORCID: https://orcid.org/0000-0002-9969-3606)
- Nadav Topaz (ORCID: https://orcid.org/0000-0001-8782-5168)
- Francisca Millan Zamora
- Gabriele Richard (ORCID: https://orcid.org/0000-0003-1976-9672)
- Stephen McGee (ORCID: https://orcid.org/0000-0003-3553-0354)
- Maria Guillen Sacoto
- Rebecca I. Torene (ORCID: https://orcid.org/0000-0002-4370-3625)
- Kirsty McWalter (ORCID: https://orcid.org/0000-0002-1654-9036)
- Kristin G. Monaghan
- Timothy Laurent
- Matthew Greenberg
Institutions
- Unilabs (Norway) (NO)
- Exact Sciences (United States) (US)
Publication Details
- Journal
- Genetics in Medicine Open
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.gimo.2025.102477
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00