TRsv: simultaneous detection of tandem repeat variations, structural variations, and short indels using long read sequencing data
Tandem repeat copy number variations (TR-CNVs), structural variations (SVs), and short indels have been responsible for many diseases and traits, but no tools exist to distinguish and detect these variants. In this study, we developed a computational tool, TRsv, to distinguish and detect TR-CNVs, SVs, and short indels using long reads. In evaluation with simulated and real datasets, TRsv outperformed existing tools for detection of TR-CNVs and indels and performed equally well for detection of SVs. We demonstrated genome-wide detection of TR-CNVs, including variants associated with gene expression, disease, and quantitative traits, using 160 long-read whole genome sequencing data and TRsv.
Authors
- Chikashi C. Terao (ORCID: https://orcid.org/0000-0002-6452-4095)
- Shunichi Kosugi (ORCID: https://orcid.org/0000-0002-5882-9255)
Institutions
- National Institute of Genetics (JP)
- University of Shizuoka (JP)
- Shizuoka General Hospital (JP)
- RIKEN Center for Integrative Medical Sciences (JP)
- Research Organization of Information and Systems (JP)
Publication Details
- Journal
- Genome biology
- Published
- 2025-08-19
- DOI
- https://doi.org/10.1186/s13059-025-03718-z
- Citations
- 1
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Japan Society for the Promotion of Science