10Phylogenetic networks are rooted, directed, acyclic graphs that model reticulate sample the posterior of phylogenetic networks given bi-allelic marker data. Our method 27 has a very good performance in terms of accuracy and robustness as we demonstrate on 28 simulated data, as well as a data set of multiple New Zealand species of the plant genus 29 Ourisia (Plantaginaceae). We implemented the method in the publicly available, 30 open-source PhyloNet software package.
31Author summary
32The availability of genomic data has revolutionized the study of evolutionary histories 33 and phylogeny inference. Inferring evolutionary histories from genomic data requires, in 34 most cases, accounting for the fact that different genomic regions could have 35 evolutionary histories that differ from each other as well as from that of the species 36 from which the genomes were sampled. In this paper, we introduce a method for 37 inferring evolutionary histories while accounting for two processes that could give rise to 38 such differences across the genomes, namely incomplete lineage sorting and 39 hybridization. We introduce a novel algorithm for computing the likelihood of 40 phylogenetic networks from bi-allelic genetic markers and use it in a Bayesian inference 41 method. Analyses of synthetic and empirical data sets show a very good performance of 42 the method in terms of the estimates it obtains.