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University of Illinois Urbana-Champaign

Novel computational methods for discordance-aware phylogenomic analysis

Abstract

dc:description

Inferring the evolutionary history of a set of species is a key step in many biological and medical research projects, as species trees provide a context in which problems in comparative genomics, biodiversity, phylogeography and epidemiology can be addressed. Recent advances in sequencing technologies have led to an increasing availability of genome-scale data, and today phylogenomics projects construct species trees using hundreds to thousands of loci, potentially whole genomes. However, species tree estimation from multi-locus datasets presents several statistical and computational challenges, as most problems in this area are NP-hard. Also, due to a phenomenon known as “gene tree heterogeneity”, different locations within the genome of a species can evolve differently due to biological processes such as incomplete lineage sorting, gene duplication and loss and horizontal gene transfer, that further complicate species tree estimation. Despite advances in developing methods that can estimate an unrooted and non-parameterized topology of a species tree in the presence of gene tree discordance, less attention has been paid to estimating the root location, quantifying branch lengths in units that are usable for downstream analysis, and estimating divergence times. All of these are necessary for many applications of phylogenomics, such as constructing the tree of life and analyzing the origins of diseases, such as HIV and COVID-19. In this dissertation, we introduce new computational methods developed for these tasks, collectively referred to as "post-species tree analysis", that address different sources of gene tree discordance. For these methods, we present rigorous theoretical results including proofs of statistical consistency, sample complexity, and running time analyses, as well as extensive empirical results on simulated and biological datasets ranging from the root of the tree of life to recent speciations. Overall, these methods provide high accuracy and scalability for estimating the root, branch lengths and divergence times in the presence of gene tree discordance, and some are accompanied with strong theoretical guarantees.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Illinois Urbana-Champaign
Year dc:date
2025

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Tabatabaee, Seyedeh Yasamin
Contributors dc:contributor
  • Warnow, Tandy
  • El-Kebir, Mohammed
  • Gropp, William
  • Liu, Ge
  • Mirarab, Siavash

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • Copyright 2025 Seyedeh Yasamin Tabatabaee
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier
https://hdl.handle.net/2142/132481
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/132481

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Tabatabaee, Seyedeh Yasamin. Novel computational methods for discordance-aware phylogenomic analysis. Dissertation thesis, University of Illinois Urbana-Champaign, 2025. https://hdl.handle.net/2142/132481