Consensus Genotyper for Exome Sequencing (CGES): improving the quality of exome variant genotypes.

ABSTRACT:

Motivation

The development of cost-effective next-generation sequencing methods has spurred the development of high-throughput bioinformatics tools for detection of sequence variation. With many disparate variant-calling algorithms available, investigators must ask, 'Which method is best for my data?' Machine learning research has shown that so-called ensemble methods that combine the output of multiple models can dramatically improve classifier performance. Here we describe a novel variant-calling approach based on an ensemble of variant-calling algorithms, which we term the Consensus Genotyper for Exome Sequencing (CGES). CGES uses a two-stage voting scheme among four algorithm implementations. While our ensemble method can accept variants generated by any variant-calling algorit

SUBMITTER: Trubetskoy V 

PROVIDER: S-EPMC4287941 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature