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Identifying Mendelian disease genes with the Variant Effect Scoring Tool

BMC Genomics · 2013 · Vol. 14(S3) · pp. S3–S3
Hannah CarterChristopher DouvillePeter D. StensonD.N. CooperRachel Karchin

Abstract

Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us.

Genomics and Rare DiseasesGenomic variations and chromosomal abnormalitiesGenomics and Phylogenetic StudiesExome sequencingMissense mutationGeneticsExomeBiologyGeneComputational biologyBioinformaticsPhenotype

MeSH terms

AlgorithmsArtificial IntelligenceHumansROC CurveComputational BiologyArea Under CurveMutation, MissenseGenetic Diseases, InbornDatabases, GeneticExome

Funding

  • National Science Foundation
  • National Institutes of Health
Citations
606
FWCI
13.45
field-weighted impact
References
58
Percentile
99%
vs. same field & year
Citations per year
Cited by
REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants
The American Journal of Human Genetics · 2016 · 2,867 citations
References
A method and server for predicting damaging missense mutations
Nature Methods · 2010 · 13,461 citations
The Sequence Alignment/Map format and SAMtools
Bioinformatics · 2009 · 66,208 citations
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1995 · 106,483 citations
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