Development and validation of a computational method for assessment of missense variants in hypertrophic cardiomyopathy.

ABSTRACT: Assessing the significance of novel genetic variants revealed by DNA sequencing is a major challenge to the integration of genomic techniques with medical practice. Many variants remain difficult to classify by traditional genetic methods. Computational methods have been developed that could contribute to classifying these variants, but they have not been properly validated and are generally not considered mature enough to be used effectively in a clinical setting. We developed a computational method for predicting the effects of missense variants detected in patients with hypertrophic cardiomyopathy (HCM). We used a curated clinical data set of 74 missense variants in six genes associated with HCM to train and validate an automated predictor. The predictor is based on support vector regre

SUBMITTER: Jordan DM 

PROVIDER: S-EPMC3035712 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature