Supplementary tables for scMutrace

We present scMutrace, a computational framework for high-confidence somatic mutation detection from single-cell sequencing data. By combining background-noise modeling with cross-sample cluster comparisons, scMutrace suppresses technical artifacts and accurately identifies variants across diverse platforms and species. Benchmarking against matched genome sequencing data demonstrates superior performance over existing methods. In addition, scMutrace reconstructs cellular lineages from aggregated single-cell groups, providing temporal and clonal context for mutational landscapes. scMutrace enables scalable extraction of genetic variation from single-cell data to study cellular heterogeneity, lineage dynamics, and disease progression. These files are supplementary tables for scMutrace to be published.