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OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and

Qingxiang Guo1, Yangyang Li1, Ting-You Wang1

  • 1Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, United States.

Bioinformatics (Oxford, England)
|October 31, 2025
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Summary

OctopuSV and TentacleSV improve structural variant (SV) analysis by correcting ambiguous annotations and automating workflows. These tools enhance variant detection and comparative studies for researchers without programming expertise.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Structural variants (SVs) are crucial for gene regulation and disease but are challenging to integrate across platforms due to inconsistent annotations and fragmented workflows.
  • Ambiguous breakend (BND) annotations are often lost, hindering variant characterization, while existing tools lack essential merging capabilities for precise variant identification.
  • Current SV analysis pipelines demand manual intervention and complex tuning, impacting reproducibility and scalability, necessitating improved methods for clinical utility.

Purpose of the Study:

  • To develop novel computational tools, OctopuSV and TentacleSV, for enhanced structural variant (SV) analysis.
  • To address limitations in SV call integration, annotation ambiguity, and workflow fragmentation.
  • To enable sophisticated SV analyses for researchers without specialized programming skills.

Main Methods:

  • OctopuSV incorporates a BND correction module to standardize ambiguous annotations into canonical SV types.
  • OctopuSV provides advanced set operations for flexible variant filtering and identification of sample-specific SVs.
  • TentacleSV automates the SV analysis pipeline from raw sequencing data to high-confidence callsets, ensuring reproducibility.

Main Results:

  • OctopuSV recovers overlooked variants by correcting ambiguous BND annotations.
  • Advanced set operations in OctopuSV facilitate sophisticated variant filtering for identifying disease-specific or group-specific SVs.
  • Benchmarking demonstrated OctopuSV and TentacleSV achieve superior performance (F1 score, SV type consistency) across short-read and long-read platforms compared to existing tools.
  • The integrated framework enables complex comparative SV studies, such as cancer subtype analysis, without requiring programming expertise.

Conclusions:

  • OctopuSV and TentacleSV significantly improve the accuracy, interpretability, and clinical utility of structural variant analysis.
  • These tools democratize advanced SV analysis, empowering researchers to conduct complex studies with enhanced reproducibility and scalability.
  • The developed framework addresses critical gaps in SV integration and characterization, paving the way for more robust genomic research and diagnostics.