| Literature DB >> 35751813 |
Tao Jiang1, Shiqi Liu1, Shuqi Cao1, Yadong Wang2.
Abstract
Structural Variation (SV) represents genomic rearrangements and is strongly associated with human health and disease. Recently, long-read sequencing technologies provide the opportunity to more comprehensive identification of SVs at an ever-high resolution. However, under the circumstance of high sequencing errors and the complexity of SVs, there remains lots of technical issues to be settled. Hence, we propose cuteSV, a sensitive, fast, and scalable alignment-based SV detection approach to complete comprehensive discovery of diverse SVs. The benchmarking results indicate cuteSV is suitable for large-scale genome project since its excellent SV yields and ultra-fast speed. Here, we explain the overall framework for providing a detailed outline for users to apply cuteSV correctly and comprehensively. More details are available at https://github.com/tjiangHIT/cuteSV .Entities:
Keywords: Alignment-based calling; Bioinformatics; Germline mutation calling; Long-read sequencing; Population-based calling; Scaling performance; Structural variants detection
Mesh:
Year: 2022 PMID: 35751813 DOI: 10.1007/978-1-0716-2293-3_9
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745