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

Volume: 9, Issue: 1
Published: Sep 4, 2019
Abstract
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 benign and deleterious evidence in 5 in silico meta-predictors, as well as agreement of SIFT and PolyPhen2, and report the derived thresholds for the...
Paper Details
Title
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification
Published Date
Sep 4, 2019
Volume
9
Issue
1
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.