Bayesian Inference of Phylogenetic Networks

dc.contributor.advisorNakhleh, Luayen_US
dc.creatorWen, Dingqiao Ellieen_US
dc.date.accessioned2017-08-03T14:02:37Zen_US
dc.date.available2017-08-03T14:02:37Zen_US
dc.date.created2016-05en_US
dc.date.issued2016-04-08en_US
dc.date.submittedMay 2016en_US
dc.date.updated2017-08-03T14:02:38Zen_US
dc.description.abstractThe multispecies coalescent (MSC) is a statistical framework that models how gene genealogies grow within the branches of a species tree. The field of computational phylogenetics has witnessed an explosion in the development of methods for species tree inference under the MSC, owing mainly to the accumulating evidence of incomplete lineage sorting in phylogenomic analyses. However, the evolutionary history of a set of genomes, or species, could be reticulate due to the occurrence of evolutionary processes such as hybridization or horizontal gene transfer. We devised a novel method for Bayesian inference of genome and species phylogenies under the multispecies network coalescent (MSNC). This framework models gene evolution within the branches of a phylogenetic network, thus incorporating reticulate evolutionary processes, such as hybridization, in addition to incomplete lineage sorting. As phylogenetic networks with different numbers of reticulation events correspond to points of different dimensions in the space of models, we devised a reversible-jump Markov chain Monte Carlo (RJMCMC) technique for sampling the posterior distribution of phylogenetic networks under the MSNC. Given the reticulate evolutionary histories for the whole genome, we devised a method to quantify introgression which would elucidate how each gene evolves. We implemented the methods in the publicly available, open-source software package PhyloNet and studied their performance on simulated and biological data. The work extends the reach of Bayesian inference to phylogenetic networks and enables new evolutionary analyses that account for reticulation.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationWen, Dingqiao Ellie. "Bayesian Inference of Phylogenetic Networks." (2016) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/96515">https://hdl.handle.net/1911/96515</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/96515en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectBayesian Inferenceen_US
dc.subjectPhylogenetic Networksen_US
dc.subjectMultispecies Network Coalescenten_US
dc.subjectReversible-Jump MCMCen_US
dc.titleBayesian Inference of Phylogenetic Networksen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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