Phylodynamics inference (PI) is a powerful approach for quantifying population dynamics and evolutionary trajectories of natural species based on phylogenetic trees. The emergence of single-cell lineage tracing technologies now enables the reconstruction of phylogenetic trees for thousands of individual cells within a multicellular organism, opening avenues for employing PI methodologies at the cellular level. However, the intricate process of cell differentiation poses challenges for directly applying current PI frameworks in somatic tissues. Here, we introduce a novel computational approach called single-cell phylodynamic explorer (scPhyloX), designed to model structured cell populations in various cell states, by leveraging single-cell phylogenetic trees to infer dynamics of tissue development and tumor evolution. Our comprehensive simulations demonstrate the high accuracy of scPhyloX across various biological scenarios. Application of scPhyloX to three real datasets of single-cell lineage tracing unveils novel insights into somatic dynamics, such as the overshoot of cycling stem cell populations in fly organ development, clonal expansion of multipotent progenitors of hematopoiesis during human aging, and pronounced subclonal selection in early colorectal tumorigenesis. Thus, scPhyloX is an innovative computational method for investigating the development and evolution of somatic tissues.
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