Comprehensive benchmarking of somatic mutation detection by the SMaHT Network

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 involving cell-lines and donor tissues, to evaluate sequencing technologies, experimental approaches, and computational methods for detecting different types of somatic mutations, generating community resource with >1,000x short-read and 100-400x long-read data for each of the nine analyzed samples. We determined effective strategies for utilizing short- and long-reads sequencing for mutation detection and demonstrated that using donor-specific assemblies and human pangenome improved calling, extending mutation catalogs to challenging genomic regions. We benchmarked six duplex 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 tissues. Together, these findings provide a roadmap for accurate, genome-wide somatic mutation discovery and analysis.