SVenX: A highly parallelized pipeline for structural variation detection using linked read whole genome sequencing data
Abstract: Genomic rearrangements larger than 50 bp are called structural variants. As a group, they affect the phenotypic diversity among humans and have been associated with many human disorders including neurodevelopmental disorder and cancer. Recent advances in whole genome sequencing (WGS) technologies have made it possible to identify many more disease-causing genetic variants relevant in clinical diagnostics and sometimes affecting treatment. Numerous approaches have been proposed to detect structural variants, but to acquire and filter out the most significant information from the multitude of called variants in the sequencing data has shown to be a challenge. Another obstacle is the high computational cost of data analyses and difficulties in configuring and operating the softwares and databases. Here, we present SVenX, a highly automated and parallelized pipeline that analyzes and call structural variants using linked read WGS data. It performs variant calling using three different approaches, as well as annotation of variants and variant filtering. We also introduce a new tool, SVGenT, that reanalyzes the called structural variants by performing de novo assembly using the aligned reads at the identified breakpoint junctions. By comparing assembled contigs and analyzing the read coverage between the breakpoint junctions, SVGenT improves both variant and genotype classification and the breakpoint localization.
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