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Maximum Likelihood Estimation of Spe...

Kim, Anastasiia.

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Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees./
Author:	Kim, Anastasiia.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	172 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
Contained By:	Dissertations Abstracts International82-04B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28027790
ISBN:	9798672196800

Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees.
Kim, Anastasiia.

Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 172 p.

Source: Dissertations Abstracts International, Volume: 82-04, Section: B.

Thesis (Ph.D.)--The University of New Mexico, 2020.

This item must not be sold to any third party vendors.

A phylogenetic tree represents the evolutionary relationships among a set of organisms. Due to several biological processes, the evolutionary histories of the parts of the genome, called gene trees, might not agree with each other, or with the evolution of the species from which the genes were sampled. Such gene trees can be used to reconstruct phylogenetic trees. The multispecies coalescent is a stochastic process that often used to model sources of gene-species tree discordance.The methods in this dissertation focus on the gene tree topologies with emphasis on ranked gene tree topologies. A ranked tree depicts the order in which nodes appear in the tree together with topological relationships among gene lineages. One challenge that arises during phylogenetic inference is the existence of the anomaly zones, the regions of branch-length space in the species tree that can produce anomalous gene trees, gene trees that have topologies differing from the species tree topology but are more probable than the gene tree matching the species tree. The recognition of the possibility of anomalous gene trees motivated development of inference methods that are not affected by anomaly zones. In spite of the many analytic results known about the various types of anomalous gene trees, less is known about how often they arise in practice. In this work, we show how the parameters of a constant-rate birth-death process used to simulate species trees affect the probability that the species tree lies in the anomaly zone. We prove that the probability that a species tree is in an anomaly zone approaches 1 as the number of species and the birth rate go to infinity in a pure birth process. We propose a heuristic approach to infer whether species trees have different types of anomalous gene trees when it is intractable to compute the entire distribution of gene tree topologies. The method proposed cannot have false positives and serves as a quick test to check the presence of anomaly zones.In this dissertation, we develop the first maximum likelihood method that infers a species tree from the collection of ranked gene tree topologies. We introduce the software PRANC, which was initially designed to compute the probabilities of ranked gene tree topologies under the coalescent process and extended to infer a maximum likelihood species tree. PRANC has other useful options to work with phylogenetic trees. We propose methods to estimate a starting tree to be able to locate the maximum likelihood species tree quickly. We evaluate the computational and accuracy performance of PRANC under different settings. To illustrate the methods proposed, we analyze two experimental studies of skinks and gibbons.

ISBN: 9798672196800Subjects--Topical Terms:

517247
Statistics.
Subjects--Index Terms:

Algorithms

Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees.
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245 1 0 $a Maximum Likelihood Estimation of Species Trees and Anomaly Zone Detection Using Ranked Gene Trees.
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300 $a 172 p.
500 $a Source: Dissertations Abstracts International, Volume: 82-04, Section: B.
500 $a Advisor: Degnan, James H.
502 $a Thesis (Ph.D.)--The University of New Mexico, 2020.
506 $a This item must not be sold to any third party vendors.
520 $a A phylogenetic tree represents the evolutionary relationships among a set of organisms. Due to several biological processes, the evolutionary histories of the parts of the genome, called gene trees, might not agree with each other, or with the evolution of the species from which the genes were sampled. Such gene trees can be used to reconstruct phylogenetic trees. The multispecies coalescent is a stochastic process that often used to model sources of gene-species tree discordance.The methods in this dissertation focus on the gene tree topologies with emphasis on ranked gene tree topologies. A ranked tree depicts the order in which nodes appear in the tree together with topological relationships among gene lineages. One challenge that arises during phylogenetic inference is the existence of the anomaly zones, the regions of branch-length space in the species tree that can produce anomalous gene trees, gene trees that have topologies differing from the species tree topology but are more probable than the gene tree matching the species tree. The recognition of the possibility of anomalous gene trees motivated development of inference methods that are not affected by anomaly zones. In spite of the many analytic results known about the various types of anomalous gene trees, less is known about how often they arise in practice. In this work, we show how the parameters of a constant-rate birth-death process used to simulate species trees affect the probability that the species tree lies in the anomaly zone. We prove that the probability that a species tree is in an anomaly zone approaches 1 as the number of species and the birth rate go to infinity in a pure birth process. We propose a heuristic approach to infer whether species trees have different types of anomalous gene trees when it is intractable to compute the entire distribution of gene tree topologies. The method proposed cannot have false positives and serves as a quick test to check the presence of anomaly zones.In this dissertation, we develop the first maximum likelihood method that infers a species tree from the collection of ranked gene tree topologies. We introduce the software PRANC, which was initially designed to compute the probabilities of ranked gene tree topologies under the coalescent process and extended to infer a maximum likelihood species tree. PRANC has other useful options to work with phylogenetic trees. We propose methods to estimate a starting tree to be able to locate the maximum likelihood species tree quickly. We evaluate the computational and accuracy performance of PRANC under different settings. To illustrate the methods proposed, we analyze two experimental studies of skinks and gibbons.
590 $a School code: 0142.
650 4 $a Statistics. $3 517247
650 4 $a Biostatistics. $3 1002712
653 $a Algorithms
653 $a Anomaly zone
653 $a Coalescent
653 $a Gene tree
653 $a Maximum likelihood
653 $a Species tree
690 $a 0463
690 $a 0308
710 2 $a The University of New Mexico. $b Statistics. $3 1019592
773 0 $t Dissertations Abstracts International $g 82-04B.
790 $a 0142
791 $a Ph.D.
792 $a 2020
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28027790