Regulatory Single-Nucleotide Variant Predictor Increases Predictive Performance of Functional Regulatory Variants.

ABSTRACT: In silico methods for detecting functionally relevant genetic variants are important for identifying genetic markers of human inherited disease. Much research has focused on protein-coding variants since coding regions have well-defined physicochemical and functional properties. However, many bioinformatics tools are not applicable to variants outside coding regions. Here, we increase the classification performance of our regulatory single-nucleotide variant predictor (RSVP) for variants that cause regulatory abnormalities from an AUC of 0.90-0.97 by incorporating genomic regions identified by the ENCODE project into RSVP. RSVP is comparable to a recently published tool, Genome-Wide Annotation of Variants (GWAVA); both RSVP and GWAVA perform better on regulatory variants than a traditional

SUBMITTER: Peterson TA 

PROVIDER: S-EPMC6192032 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature