biostudies-literatureKosugi SJapan Society for the Promotion of Science246https://www.ebi.ac.uk/biostudies/studies/S-EPMC12366377biostudies-literatureUnknown26(1)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.Genome biologyTRsv: simultaneous detection of tandem repeat variations, structural variations, and short indels using long read sequencing data.PMC12366377JP21K06130JP17K07264Kosugi STerao CfalseTRsv: 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.2025-01-01T00:00:00Z2025 Aug2026-05-29T17:06:21.295Z2026-04-08T05:25:26.534ZS-EPMC123663774083052710.1186/s13059-025-03718-z