Javascript must be enabled to continue!
Inferring Phylogenetic Networks Using PhyloNet
View through CrossRef
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.
].
Related Results
CAMUS: Scalable Phylogenetic Network Estimation
CAMUS: Scalable Phylogenetic Network Estimation
Abstract
Motivation
Phylogenetic networks are models of evolution that go beyond trees, and so represent reticulate events such...
PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks
PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks
Abstract
Phylogenetic diversity plays an important role in biodiversity, conservation, and evolutionary studies by measuring the diversity of a s...
Phylogenetic overdispersion of plant species in southern Brazilian savannas
Phylogenetic overdispersion of plant species in southern Brazilian savannas
Ecological communities are the result of not only present ecological processes, such as competition among species and environmental filtering, but also past and continuing evolutio...
Inference of Species Phylogenies from Bi-allelic Markers Using Pseudo-likelihood
Inference of Species Phylogenies from Bi-allelic Markers Using Pseudo-likelihood
AbstractMotivationPhylogenetic networks represent reticulate evolutionary histories. Statistical methods for their inference under the multispecies coalescent have recently been de...
Empirical Performance of Tree-based Inference of Phylogenetic Networks
Empirical Performance of Tree-based Inference of Phylogenetic Networks
AbstractPhylogenetic networks extend the phylogenetic tree structure and allow for modeling vertical and horizontal evolution in a single framework. Statistical inference of phylog...
On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo
On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo
Abstract
For various species, high quality sequences and complete genomes are nowadays available for many individuals. This makes data analysis c...
Phylogenetic diversity and regionalization of root nodule symbiosis
Phylogenetic diversity and regionalization of root nodule symbiosis
ABSTRACTAimHere we determine centers of species richness (SR), relative phylogenetic diversity (RPD) and centers of paleo- and neo-endemism, and regionalizations of phylogenetic di...
phyr: An R package for phylogenetic species-distribution modelling in ecological communities
phyr: An R package for phylogenetic species-distribution modelling in ecological communities
SummaryModel-based approaches are increasingly popular in ecological studies. A good example of this trend is the use of joint species distribution models to ask questions about ec...

