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Rice University

Bayesian Inference of Phylogenetic Networks

Abstract

dc:description.abstract

The 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Engineering
Grantor
Rice University
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wen, Dingqiao Ellie
Advisor dc:contributor.advisor
  • Nakhleh, Luay

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • Copyright 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1911/96515
OAI identifier oai:identifier
oai:repository.rice.edu:1911/96515

Chain of custody

source
Harvested from
Rice University
Base URL
repository.rice.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Wen, Dingqiao Ellie. Bayesian Inference of Phylogenetic Networks. Masters thesis, Rice University, 2016. https://hdl.handle.net/1911/96515