Chapter title |
Structural Variant Detection from Long-Read Sequencing Data with cuteSV
|
---|---|
Chapter number | 9 |
Book title |
Variant Calling
|
Published in |
Methods in molecular biology, January 2022
|
DOI | 10.1007/978-1-0716-2293-3_9 |
Pubmed ID | |
Book ISBNs |
978-1-07-162292-6, 978-1-07-162293-3
|
Authors |
Jiang, Tao, Liu, Shiqi, Cao, Shuqi, Wang, Yadong |
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 . |
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