Disease-specific variant pathogenicity prediction significantly improves variant interpretation in inherited cardiac conditions

PURPOSE: Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequence...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaolei, Walsh, Roddy, Whiffin, Nicola, Buchan, Rachel, Midwinter, William, Wilk, Alicja, Govind, Risha, Li, Nicholas, Ahmad, Mian, Mazzarotto, Francesco, Roberts, Angharad, Theotokis, Pantazis I., Mazaika, Erica, Allouba, Mona, de Marvao, Antonio, Pua, Chee Jian, Day, Sharlene M., Ashley, Euan, Colan, Steven D., Michels, Michelle, Pereira, Alexandre C., Jacoby, Daniel, Ho, Carolyn Y., Olivotto, Iacopo, Gunnarsson, Gunnar T., Jefferies, John L., Semsarian, Chris, Ingles, Jodie, O’Regan, Declan P., Aguib, Yasmine, Yacoub, Magdi H., Cook, Stuart A., Barton, Paul J. R., Bottolo, Leonardo, Ware, James S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790749/
https://www.ncbi.nlm.nih.gov/pubmed/33046849
http://dx.doi.org/10.1038/s41436-020-00972-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7790749/
https://www.ncbi.nlm.nih.gov/pubmed/33046849
http://dx.doi.org/10.1038/s41436-020-00972-3

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