PhyloNet

PhyloNet: a software package for analyzing and reconstructing reticulate evolutionary relationships. BACKGROUND: Phylogenies, i.e., the evolutionary histories of groups of taxa, play a major role in representing the interrelationships among biological entities. Many software tools for reconstructing and evaluating such phylogenies have been proposed, almost all of which assume the underlying evolutionary history to be a tree. While trees give a satisfactory first-order approximation for many families of organisms, other families exhibit evolutionary mechanisms that cannot be represented by trees. Processes such as horizontal gene transfer (HGT), hybrid speciation, and interspecific recombination, collectively referred to as reticulate evolutionary events, result in networks, rather than trees, of relationships. Various software tools have been recently developed to analyze reticulate evolutionary relationships, which include SplitsTree4, LatTrans, EEEP, HorizStory, and T-REX. RESULTS: In this paper, we report on the PhyloNet software package, which is a suite of tools for analyzing reticulate evolutionary relationships, or evolutionary networks, which are rooted, directed, acyclic graphs, leaf-labeled by a set of taxa. These tools can be classified into four categories: (1) evolutionary network representation: reading/writing evolutionary networks in a newly devised compact form; (2) evolutionary network characterization: analyzing evolutionary networks in terms of three basic building blocks - trees, clusters, and tripartitions; (3) evolutionary network comparison: comparing two evolutionary networks in terms of topological dissimilarities, as well as fitness to sequence evolution under a maximum parsimony criterion; and (4) evolutionary network reconstruction: reconstructing an evolutionary network from a species tree and a set of gene trees. CONCLUSION: The software package, PhyloNet, offers an array of utilities to allow for efficient and accurate analysis of evolutionary networks. The software package will help significantly in analyzing large data sets, as well as in studying the performance of evolutionary network reconstruction methods. Further, the software package supports the proposed eNewick format for compact representation of evolutionary networks, a feature that allows for efficient interoperability of evolutionary network software tools. Currently, all utilities in PhyloNet are invoked on the command line.


References in zbMATH (referenced in 11 articles )

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  1. Kong, Sungsik; Pons, Joan Carles; Kubatko, Laura; Wicke, Kristina: Classes of explicit phylogenetic networks and their biological and mathematical significance (2022)
  2. Gross, Elizabeth; van Iersel, Leo; Janssen, Remie; Jones, Mark; Long, Colby; Murakami, Yukihiro: Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes (2021)
  3. Grindstaff, Gillian; Owen, Megan: Representations of partial leaf sets in phylogenetic tree space (2019)
  4. Warnow, Tandy (ed.): Bioinformatics and phylogenetics. Seminal contributions of Bernard Moret (2019)
  5. Janssen, Remie; Jones, Mark; Erdos, P├ęter L.; van Iersel, Leo; Scornavacca, Celine: Exploring the tiers of rooted phylogenetic network space using tail moves (2018)
  6. Bayzid, Md. Shamsuzzoha; Warnow, Tandy: Gene tree parsimony for incomplete gene trees (2017)
  7. Chen, Zhi-Zhong; Fan, Ying; Wang, Lusheng: Faster exact computation of rSPR distance (2015)
  8. Makarenkov, Vladimir; Boc, Alix; Legendre, Pierre: A new algorithm for inferring hybridization events based on the detection of horizontal gene transfers (2014)
  9. Arenas, Miguel; Patricio, Mateus; Posada, David; Valiente, Gabriel: Characterization of phylogenetic networks with nettest (2010) ioport
  10. Rosenberg, Noah A.; Degnan, James H.: Coalescent histories for discordant gene trees and species trees (2010)
  11. Zierke, Stephanie; Bakos, Jason D.: FPGA acceleration of the phylogenetic likelihood function for Bayesian MCMC inference methods (2010) ioport