NanoVar: accurate characterization of patients’ genomic structural variants using low-depth nanopore sequencing
Cheng Yong Tham, Roberto Tirado-Magallanes, Yufen Goh, Melissa J. Fullwood, Bryan T. H. Koh, Wilson Wang, Chin Hin Ng, Wee Joo Chng, Alexandre H. Thiéry, Daniel G. Tenen, Touati Benoukraf
Abstract
The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we present NanoVar, an optimized structural variant caller utilizing low-depth (8X) whole-genome sequencing data generated by Oxford Nanopore Technologies. NanoVar exhibits higher structural variant calling accuracy when benchmarked against current tools using low-depth simulated datasets. In patient samples, we successfully validate structural variants characterized by NanoVar and uncover normal alternative sequences or alleles which are present in healthy individuals.