Data from: Coestimating reticulate phylogenies and gene trees from multilocus sequence data

The multispecies network coalescent (MSNC) is a stochastic process that
captures how gene trees grow within the branches of a phylogenetic
network. Coupling the MSNC with a stochastic mutational process that
operates along the branches of the gene trees gives rise to a generative
model of how multiple loci from within and across species evolve in the
presence of both incomplete lineage sorting (ILS) and reticulation (e.g.,
hybridization). We report on a Bayesian method for sampling the parameters
of this generative model, including the species phylogeny, gene trees,
divergence times, and population sizes, from DNA sequences of multiple
independent loci. We demonstrate the utility of our method by analyzing
simulated data and reanalyzing an empirical data set. Our results
demonstrate the significance of not only co-estimating species phylogenies
and gene trees, but also accounting for reticulation and ILS
simultaneously. In particular, we show that when gene flow occurs, our
method accurately estimates the evolutionary histories, coalescence times,
and divergence times. Tree inference methods, on the other hand,
underestimate divergence times and overestimate coalescence times when the
evolutionary history is reticulate. While the MSNC corresponds to an
abstract model of ``intermixture," we study the performance of the
model and method on simulated data generated under a gene flow model. We
show that the method accurately infers the most recent time at which gene
flow occurs. Finally, we demonstrate the application of the new method to
a 106-locus yeast data set.