Comprehensive benchmarking of somatic mutation detection by the SMaHT Network

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Abstract

Somatic mosaicism is increasingly recognized as a fundamental feature of human biology, yet the detection of somatic mutations remains challenging. The SMaHT Network conducted four large-scale benchmarking experiments to evaluate sequencing technologies, experimental approaches, and computational methods for detecting diverse somatic mutations. Cumulative sequencing coverage exceeded 1,000X with short reads and 100-400X with long reads for each of nine analyzed samples. We defined optimal strategies for integrating bulk short- and long-read sequencing for mutation detection and demonstrated that using donor-specific assemblies and human pangenome improved variant calling and extended mutation catalogs to challenging genomic regions. We benchmarked six duplex-seq technologies and showed that single-cell sequencing resolves cell type-specific mutational patterns and heterogeneity. Our results indicate that bulk, single-cell, and duplex analyses are complementary, and leveraging all three provides comprehensive characterization of mosaicism within a tissue. Together, these findings provide a roadmap for accurate, genome-wide somatic mutation discovery and analysis.

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