Detecting structural variations with precise breakpoints using low-depth WGS data from a single oxford nanopore MinION flowcell.

ABSTRACT: Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (specifically, 4×) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, particularly pathogenic SV for supporting clinical diagnosis. When using 4× ONT WGS data, existing SV calling software often fails to detect pathogenic SV, especially in the form of long deletion, terminal deletion, duplication, and unbalanced translocation. Our new SV calling software SENSV can achieve high sensitivity for all types of SV and a breakpoint precision typically ± 100 bp; both features are important for clinical concerns. The improvement achieved by SENSV stems from several new algorithms. We evaluated SENSV and other software using both r

SUBMITTER: Leung HCM 

PROVIDER: S-EPMC8927474 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature