Comprehensive evaluation of structural variation detection for germline and somatic analysis with long-read sequencing data.

Long-read sequencing-based detection of germline and somatic structural variations achieves high accuracy with specific tools, with some methods reaching stable performance across diverse datasets.

• Why it matters: Accurate detection of structural variations is crucial for understanding genetic diversity and disease, but current methods face challenges due to genomic complexity and lack of comprehensive benchmarks, especially for somatic variants.
• What they did: A unified benchmarking framework evaluated 14 long-read SV callers across 20 datasets from PacBio and Oxford Nanopore platforms, analyzing performance with 12 metrics including artefact rates and inheritance errors.
• The result: Tools like DeBreak, cuteSV2, and SVDF reliably detect germline SVs, while Severus, SAVANA, and nanomonsv excel in somatic SV detection, guiding tool selection and future algorithm development.