CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

Abstract Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a...

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Bibliographic Details
Main Authors: Shuang Li, K. Joeri van der Velde, Dick de Ridder, Aalt D. J. van Dijk, Dimitrios Soudis, Leslie R. Zwerwer, Patrick Deelen, Dennis Hendriksen, Bart Charbon, Marielle E. van Gijn, Kristin Abbott, Birgit Sikkema-Raddatz, Cleo C. van Diemen, Wilhelmina S. Kerstjens-Frederikse, Richard J. Sinke, Morris A. Swertz
Format: Article
Language:English
Published: BMC 2020-08-01
Series:Genome Medicine
Subjects:
Variant pathogenicity prediction
Machine learning
Exome sequencing
Molecular consequence
Allele frequency
Clinical genetics
Online Access:http://link.springer.com/article/10.1186/s13073-020-00775-w

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http://link.springer.com/article/10.1186/s13073-020-00775-w

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