Comprehensive benchmarking of somatic mutation detection by the SMaHT Network.
Abstract
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 technologies, experimental approaches, and computational methods for detecting different types of somatic mutations, generating community resources with >1,000× short-read and 100-400× long-read data for nine analyzed samples. We determined effective strategies for utilizing short- and long-read sequencing for mutation detection and demonstrated that using donor-specific and pangenome-inferred diploid assemblies 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 that leveraging all three provides comprehensive characterization of mosaicism within tissues. Together, these findings provide the scientific and clinical communities with a roadmap for accurate genome-wide somatic mutation analysis.