Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics

Abstract Background The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools...

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Bibliographic Details
Main Authors: Corinna Ernst, Eric Hahnen, Christoph Engel, Michael Nothnagel, Jonas Weber, Rita K. Schmutzler, Jan Hauke
Format: Article
Language:English
Published: BMC 2018-03-01
Series:BMC Medical Genomics
Subjects:
BRCA
Classification
Missense variant
Prediction tools
Variant of uncertain significance
Online Access:http://link.springer.com/article/10.1186/s12920-018-0353-y

Internet

http://link.springer.com/article/10.1186/s12920-018-0353-y

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