VarSight: prioritizing clinically reported variants with binary classification algorithms.

ABSTRACT:

Background

When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance.

Methods

We tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will

SUBMITTER: Holt JM 

PROVIDER: S-EPMC6792253 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature