Data and code from: TiDeTree: A Bayesian phylogenetic framework to estimate single-cell trees and population dynamic parameters from genetic lineage tracing data

The development of organisms and tissues is dictated by an elaborate
balance between cell division, apoptosis and differentiation: the cell
population dynamics. To quantify these dynamics, we propose a phylodynamic
inference approach based on data from single-cell lineage recorders. For
this purpose, we developed a Bayesian phylogenetic framework, TiDeTree,
that uses lineage recorder data as input to estimate time-scaled
single-cell trees. By implementing TiDeTree in the BEAST 2 platform, we
enable joint inference of the time-scaled trees and, for the first time,
the cell population dynamics. We validated TiDeTree using simulations and
showed that its performance can further be improved by including multiple
sources of additional independent information into the inference, such as
frequencies of editing outcomes or experimental replicates. We benchmarked
TiDeTree against state-of-the-art methods and show that it performs
comparably in terms of tree topology estimation and additionally enables
direct assessment of uncertainty, estimation of a time-scaled tree, and
co-estimation of additional parameters. To demonstrate TiDeTree’s use in
practice, we analysed a public data set containing lineage recorder data
from ~100 stem cell colonies. We estimated a time-scaled phylogeny for
each colony, as well as the cell division and apoptosis rates underlying
the growth dynamics of all colonies. We envision that TiDeTree will find
broad application in the analysis of single-cell lineage tracing data,
which will improve our understanding of cellular processes during
development.