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.
| Original language | English |
|---|---|
| Title of host publication | Methods in Molecular Biology |
| Publisher | Humana Press Inc. |
| Pages | 137-151 |
| Number of pages | 15 |
| DOIs | |
| State | Published - 2022 |
Publication series
| Name | Methods in Molecular Biology |
|---|---|
| Volume | 2493 |
| ISSN (Print) | 1064-3745 |
| ISSN (Electronic) | 1940-6029 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Keywords
- Alignment-based calling
- Bioinformatics
- Germline mutation calling
- Long-read sequencing
- Population-based calling
- Scaling performance
- Structural variants detection
Fingerprint
Dive into the research topics of 'Structural Variant Detection from Long-Read Sequencing Data with cuteSV'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver