Integrated likelihood for phylogenomics under a no-common-mechanism model.

Hunter Tidwell, Luay Nakhleh
Author Information
  1. Hunter Tidwell: Department of Computer Science, Rice University, Houston, TX, USA.
  2. Luay Nakhleh: Department of Computer Science, Rice University, Houston, TX, USA. nakhleh@rice.edu.

Abstract

BACKGROUND: Multi-locus species phylogeny inference is based on models of sequence evolution on gene trees as well as models of gene tree evolution within the branches of species phylogenies. Almost all statistical methods for this inference task assume a common mechanism across all loci as captured by a single value of each branch length of the species phylogeny.
RESULTS: In this paper, we pursue a "no common mechanism" (NCM) model, where every gene tree evolves according to its own parameters of the species phylogeny. Based on this model, we derive an analytically integrated likelihood of both species trees and networks given the gene trees of multiple loci under an NCM model. We demonstrate the performance of inference under this integrated likelihood on both simulated and biological data.
CONCLUSIONS: The model presented here will afford opportunities for exploring connections among various criteria for estimating species phylogenies from multiple, independent loci. Furthermore, further development of this model could potentially result in more efficient methods for searching the space of species phylogenies by focusing solely on the topology of the phylogeny.

Keywords

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MeSH Term

Animals
Computer Simulation
Culicidae
Evolution, Molecular
Genetic Speciation
Genomics
Likelihood Functions
Models, Genetic
Neural Networks, Computer
Phylogeny
Probability
Wills

Word Cloud

Created with Highcharts 10.0.0speciesmodelphylogenygenelikelihoodinferencetreesphylogeniescommonlocimodelsevolutiontreemethodsmechanismNCMintegratedmultipleIntegratedBACKGROUND:Multi-locusbasedsequencewellwithinbranchesAlmoststatisticaltaskassumeacrosscapturedsinglevaluebranchlengthRESULTS:paperpursue"nomechanism"everyevolvesaccordingparametersBasedderiveanalyticallynetworksgivendemonstrateperformancesimulatedbiologicaldataCONCLUSIONS:presentedwillaffordopportunitiesexploringconnectionsamongvariouscriteriaestimatingindependentFurthermoredevelopmentpotentiallyresultefficientsearchingspacefocusingsolelytopologyphylogenomicsno-common-mechanismMultispeciescoalescentPhylogenomics

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