Data from: Dating phylogenies with sequentially sampled tips

Tanja Stadler & Ziheng Yang
We develop a Bayesian Markov chain Monte Carlo (MCMC) algorithm for estimating divergence times using sequentially sampled molecular sequences. This type of data is commonly collected during viral epidemics and is sometimes available from different species in ancient DNA studies. We derive the distribution of ages of nodes in the tree under a birth–death-sequential-sampling (BDSS) model and use it as the prior for divergence times in the dating analysis. We implement the prior in the...
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