article Open AccessTop 1% cited
Identifying Mendelian disease genes with the Variant Effect Scoring Tool
BMC Genomics · 2013 · Vol. 14(S3) · pp. S3–S3
Hannah Carter✉(Johns Hopkins University)Christopher Douville(Johns Hopkins University)Peter D. Stenson(Cardiff University)D.N. Cooper(Cardiff University)Rachel Karchin(Johns Hopkins University)
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
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