Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

ABSTRACT: As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozy

SUBMITTER: Hwang KB 

PROVIDER: S-EPMC4112476 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature