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Inferring Phylogenetic Networks Using PhyloNet

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AbstractPhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or bi-allelic markers) is implemented. Maximum parsimony is based on an extension of the “minimizing deep coalescences” criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudo-likelihood measure. PhyloNet summarizes the results of the various analyses, and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software, [phylogenetic networks; reticulation; incomplete lineage sorting; multispecies network coalescent; Bayesian inference; maximum likelihood; maximum parsimony.]
Title: Inferring Phylogenetic Networks Using PhyloNet
Description:
AbstractPhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks.
At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree.
Since then, PhyloNet has grown significantly.
The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.
g.
, hybridization) and incomplete lineage sorting.
In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates.
Furthermore, Bayesian inference directly from sequence data (sequence alignments or bi-allelic markers) is implemented.
Maximum parsimony is based on an extension of the “minimizing deep coalescences” criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent.
All methods allow for multiple individuals per species.
As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudo-likelihood measure.
PhyloNet summarizes the results of the various analyses, and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software, [phylogenetic networks; reticulation; incomplete lineage sorting; multispecies network coalescent; Bayesian inference; maximum likelihood; maximum parsimony.
].

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