SENSV: Detecting Structural Variations with Precise Breakpoints using Low-Depth WGS Data from a Single Oxford Nanopore MinION Flowcell
Henry C. M. Leung, Huijing Yu, Yifan Zhang, Wing Sze Leung, Ivan F. M. Lo, Ho‐Ming Luk, Wai-Chun Law, Ka Kui, Chak-Lim Wong, Yat Sing Wong, Ruibang Luo, Tak‐Wah Lam
SENSV detects structural variations with high sensitivity and precise breakpoints using low-depth Oxford Nanopore WGS data from a single MinION flowcell, outperforming existing tools in pathogenic SV detection.
Scientific Reports · Mar 16, 2022Peer-reviewedBioinformatics