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Updated: May 28, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Benchmarking major somatic structural variant callers on the HG008 genome
Xinran Cui1,2,3, Yadong Liu2,3, Long Qian4
1School of Medicine and Health, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin, Heilongjiang, China.
Abstract:
Somatic structural variants (SVs) are the predominant source of cancer driver mutations and play a critical role in oncogenesis. Comprehensive characterization of somatic SVs is critical for elucidating the mechanisms underlying tumorigenesis and for identifying biomarkers with diagnostic and therapeutic potential. However, their accurate detection remains challenging, primarily because most existing SV detection algorithms were originally developed for germline variants and are not well-suited to addressing the high heterogeneity of somatic mutations. In recent years, although several tools specifically designed for somatic SVs have emerged, their detection performance has not yet been rigorously validated. To bridge this gap, we conducted a comprehensive benchmarking of four leading somatic SV detection tools, namely, Sniffles2, Nanomonsv, Savana, and Severus, on the HG008 genome from Genome in a Bottle Consortium (GIAB). Their outputs were evaluated against the HG008 clonal somatic SV draft benchmark to assess overall performance. We further integrated the somatic SV callsets from multiple tools and compared them with the benchmark set, thereby establishing a multi-tool ensemble strategy for SV detection to achieve more accurate and comprehensive identification of somatic SVs.
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