Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2.

ABSTRACT: Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the perfo

SUBMITTER: D'Aurizio R 

PROVIDER: S-EPMC5175347 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature