Oct 2026· Cell Genomics· pp.
101390
· 2 citations· 43 references
Medicine
TL;DR
This work establishes a framework and best practices for reliably detecting low-VAF mutations in non-cancer tissues and provides a valuable resource for the community.
Abstract
Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark variant-calling strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep short- and long-read whole-genome sequencing data across five centers (170×-470× per center). We assembled a reference set of mosaic SNVs and indels, cross-validated with long-read data to expose short-read limitations. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied twelve pipelines, callsets were largely discordant across tools and replicates, partly reflecting stochastic sampling of low-VAF mutations in biological replicates. For SNVs with VAFs above 2%, sensitivity and precision approached 80% at ≥300×, with little gain from additional sequencing. This work establishes a framework and best practices for reliably detecting low-VAF mutations in non-cancer tissues and provides a valuable resource for the community.
Somatic mosaicism is widespread in human biology and disease, yet robust benchmarks are scarce. The Somatic Mosaicism across Human Tissues (SMaHT) Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25%-16.5% variant allele fractions. We developed a technology-agnostic method that bu...
Nahyun Kong, Zi-Tian Tang, Andrew Ruttenberg et al.· Cell Genomics· 1 citation
Somatic mosaicism is increasingly recognized as a fundamental feature of human biology, yet the detection of somatic mutations remains challenging. The Somatic Mosaicism across Human Tissues (SMaHT) Network conducted large-scale benchmarking experiments involving cell lines and donor tissues to evaluate sequencing tech...
A. Abyzov, Abhiram Natu, Adam Voshall et al.· Cell· 1 citation
Continuous advances in read accuracy have positioned bulk whole-genome sequencing as a promising approach for somatic mutation discovery in research and clinical settings, but its utility for detecting low-frequency mutations in high-coverage data has not been thoroughly assessed. We utilized an experimental design fea...
Yeongjun Jang, Stephanie Gardiner, Yifan Wang et al.· American Journal of Human Ge...· 2 citations
Structural variants (SVs) are a major source of genomic diversity, yet their discovery remains challenging due to repetitive genomic contexts, alignment ambiguity and the trade-off between sequencing cost and read length. Here we introduce HitSV, which implements repetitiveness- and signature-density-aware breakpoint r...
Background Next-generation sequencing (NGS) is vital for tracking viral evolution during outbreaks. Oxford Nanopore Technologies (ONT) offers long-read, cost-effective sequencing, but accurate sub-consensus variant detection remains challenging. LoFreq, a widely used caller for sub-consensus variant calling in haploid...
Xavier Zair, Andreas Wilm, Miles C. Benton et al.· PLoS ONE· 0 citations
ContextSV, a framework that integrates alignment evidence with copy number predictions derived from sequencing coverage and single-nucleotide variant allele frequencies to improve SV detection, serves as a valuable complement to existing long-read SV detection approaches by improving sensitivity for large and clinicall...
J. E. Perdomo, Mian Umair Ahsan, Jasmine Akoto et al.· NAR Genomics and Bioinformat...· 0 citations
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