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Accepted (AM)Open Access (License Unspecified), Open
Journal article
A survey of algorithms for the detection of genomic structural variants from long-read sequencing data
Nature methods, v 20(8), pp 1143-1158
01 Aug 2023
PMID: 37386186
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
As long-read sequencing technologies are becoming increasingly popular, a number of methods have been developed for the discovery and analysis of structural variants (SVs) from long reads. Long reads enable detection of SVs that could not be previously detected from short-read sequencing, but computational methods must adapt to the unique challenges and opportunities presented by long-read sequencing. Here, we summarize over 50 long-read-based methods for SV detection, genotyping and visualization, and discuss how new telomere-to-telomere genome assemblies and pangenome efforts can improve the accuracy and drive the development of SV callers in the future.
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Details
- Title
- A survey of algorithms for the detection of genomic structural variants from long-read sequencing data
- Creators
- Mian Umair Ahsan - Children's Hospital of PhiladelphiaQian Liu - Children's Hospital of PhiladelphiaJonathan Elliot Perdomo - Drexel University, Graduate School of Biomedical Sciences and Professional StudiesLi Fang - Sun Yat-sen UniversityKai Wang - University of Pennsylvania
- Publication Details
- Nature methods, v 20(8), pp 1143-1158
- Publisher
- Springer Nature
- Number of pages
- 16
- Grant note
- GM132713 / NIGMS NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Graduate School of Biomedical Sciences and Professional Studies
- Web of Science ID
- WOS:001022127400002
- Scopus ID
- 2-s2.0-85163760750
- Other Identifier
- 991021893414204721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Biochemical Research Methods