Phylodynamic inference on single-cell data

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Abstract

The way mutations accumulate over the course of evolution fundamentally differs between macroevolutionary settings and cellular reproduction. In macroevolution, mutations generally accumulate continuously over time. Under cellular reproduction, like somatic evolution within a tumor or evolution within a bacterial population, mutations occur largely in discrete steps at individual reproductive events. In this paper, we address the problem of phylodynamic inference under cellular reproduction. We find that when mutations occur at cell divisions, the number of mutations along a phylogenetic branch follows a compound Poisson statistics rather than a Poisson statistics, and this affects the inference from phylogenetic data. Based on the likelihood of a birth-death model, we set up an inference scheme for the relative death-to-birth rate and the number of mutations per generation and apply this method to haematopoietic stem cells. Our approach is computationally efficient thus allowing a broad range of applications, in particular on lineage trees from single-cell data.

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