REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification

Many in silico predictors of genetic variant pathogenicity have been previously developed, but there is currently no standard application of these algorithms for variant assessment. Using 4,094 ClinVar-curated missense variants in clinically actionable genes, we evaluated the accuracy and yield of b...

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Detalles Bibliográficos
Autores principales: Tian, Yuan, Pesaran, Tina, Chamberlin, Adam, Fenwick, R. Bryn, Li, Shuwei, Gau, Chia-Ling, Chao, Elizabeth C., Lu, Hsiao-Mei, Black, Mary Helen, Qian, Dajun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726608/
https://www.ncbi.nlm.nih.gov/pubmed/31484976
http://dx.doi.org/10.1038/s41598-019-49224-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6726608/
https://www.ncbi.nlm.nih.gov/pubmed/31484976
http://dx.doi.org/10.1038/s41598-019-49224-8

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