Skip to main content
Dryad

A Multi-Type Birth-Death model for Bayesian inference of lineage-specific birth and death rates

Cite this dataset

Barido-Sottani, Joëlle; Vaughan, Timothy; Stadler, Tanja (2020). A Multi-Type Birth-Death model for Bayesian inference of lineage-specific birth and death rates [Dataset]. Dryad. https://doi.org/10.5061/dryad.zpc866t5n

Abstract

Heterogeneous populations can lead to important differences in birth and death rates across a phylogeny. Taking this heterogeneity into account is necessary to obtain accurate estimates of the underlying population dynamics. We present a new multi-type birth-death model (MTBD) that can estimate lineage-specific birth and death rates. This corresponds to estimating lineage-dependent speciation and extinction rates for species phylogenies, and lineage-dependent transmission and recovery rates for pathogen transmission trees. In contrast with previous models, we do not presume to know the trait driving the rate differences, nor do we prohibit the same rates from appearing in different parts of the phylogeny. Using simulated datasets, we show that the MTBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtained by MTBD and by the existing software BAMM. We compare two implementations of the model, one exact and one approximate (assuming that no rate changes occur in the extinct parts of the tree), and show that the approximation only slightly affects results. The MTBD model is implemented as a package in the Bayesian inference software BEAST~2, and allows joint inference of the phylogeny and the model parameters.

Usage notes

Files contained in this dataset:

Supplement.pdf: Supplementary methods and results

code_files.zip: R scripts used to simulate, process and analyze the data and make the plots; XML configuration files used to run BEAST2

data_files.zip: Simulated datasets and summary of the results