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.

• Publication year

  2025

• Venue

  Genome Biology

• Publication date

  2025-08-20

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1186/s13059-025-03718-zPMID 40830527PMCID 12366377
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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