Identifying Mendelian disease genes with the variant effect scoring tool.

ABSTRACT:

Background

Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease.

Results

We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for priorit

SUBMITTER: Carter H 

PROVIDER: S-EPMC3665549 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature