Phylogenetic tree inference from single-cell RNA sequencing data with SCITE-RNA

We present SCITE-RNA, a novel phylogenetic tree inference method designed for single-cell RNA sequencing data which takes reference and alternative read counts of single-nucleotide variants as input. Our approach uses a maximum-likelihood random-scan greedy search that alternates between cell lineage tree and mutation tree representations to escape local optima until convergence is achieved in both. We demonstrate superior performance on simulated data compared to existing methods. Furthermore, we show its applicability to cancer single-cell RNA sequencing data, where it allows us to link evolutionary trajectories of cells to their gene expression profiles.