Evidence map›Paper›PMID 42200198›Full record

ArticleFrontiers in genetics2026

Benchmarking major somatic structural variant callers on the HG008 genome.

Xinran Cui, Yadong Liu, Long Qian, Yadong Wang

Abstract read
In one paragraph

Article in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xinran CuiSchool of Medicine and Health, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin, Heilongjiang, China.
Yadong LiuCenter for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China.
Long QianCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Yadong WangSchool of Medicine and Health, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin, Heilongjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

benchmarkingcancer genomicsensemble strategylong-read sequencingsomatic structural variantsvariant calling tools

Identifiers

PMID42200198
PMCPMC13200840

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.