Practical Aspects of Phylogenetic Network Analysis Using PhyloNet

Phylogenetic networks extend trees to enable simultaneous modeling of both vertical and horizontal evolutionary processes. PhyloNet is a software package that has been under constant development for over 10 years and includes a wide array of functionalities for inferring and analyzing phylogenetic networks. These functionalities differ in terms of the input data they require, the criteria and models they employ, and the types of information they allow to infer about the networks beyond their topologies. Furthermore, PhyloNet includes functionalities for simulating synthetic data on phylogenetic networks, quantifying the topological differences between phylogenetic networks, and evaluating evolutionary hypotheses given in the form of phylogenetic networks. In this paper, we use a simulated data set to illustrate the use of several of PhyloNet9s functionalities and make recommendations on how to analyze data sets and interpret the results when using these functionalities. All inference methods that we illustrate are incomplete lineage sorting (ILS) aware; that is, they account for the potential of ILS in the data while inferring the phylogenetic network. While the models do not include gene duplication and loss, we discuss how the methods can be used to analyze data in the presence of polyploidy. The concept of species is irrelevant for the computational analyses enabled by PhyloNet in that species-individuals mappings are user-defined. Consequently, none of the functionalities in PhyloNet deals with the task of species delimitation. In this sense, the data being analyzed could come from different individuals within a single species, in which case population structure along with potential gene flow is inferred (assuming the data has sufficient signal), or from different individuals sampled from different species, in which case the species phylogeny is being inferred.