PHALCON: phylogeny-aware variant calling from large-scale single-cell panel sequencing datasets

Single-cell sequencing (SCS) enables variant detection and tumor phylogeny reconstruction for resolving intra-tumor heterogeneity (ITH), which causes drug resistance and cancer relapse. Recently emerged panel sequencing methods sequence disease-specific genes across thousands of cells, but existing variant callers and SCS-specific phylogenetic methods struggle with large-scale datasets and amplification biases in panel-based sequencing protocols. We present a statistical variant caller, PHALCON for scalable mutation detection from large-scale single-cell panel sequencing data by modeling tumor evolution under a finite-sites model along a clonal phylogeny. Across a wide variety of simulation settings, PHALCON outperformed state-of-the-art methods in variant calling, tumor phylogeny inference, and runtime. From triple negative breast cancer (TNBC) and acute myeloid leukemia (AML) datasets, PHALCON detected novel somatic mutations with high functional impact, resolved clonal substructure and rare clones. In AML, PHALCON also uncovered poor-survival subgroups harboring DNA methylation and chromatin/cohesin mutations and revealed novel cellular co-occurrence and exclusivity patterns of driver mutations.