Species network inference under the multispecies coalescent model

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Author
Baños Cervantes, Hector Daniel
Chair
Allman, Elizabeth S.
Rhodes, John A.
Committee
Barry, Ronald
Faudree, Jill
Keyword
biology
mathematical models
molecular biology
phylogeny
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URI
http://hdl.handle.net/11122/10482
Abstract
Species network inference is a challenging problem in phylogenetics. In this work, we present two results on this. The first shows that many topological features of a level-1 network are identifable under the network multispecies coalescent model (NMSC). Specifcally, we show that one can identify from gene tree frequencies the unrooted semidirected species network, after suppressing all cycles of size less than 4. The second presents the theory behind a new, statistically consistent, practical method for the inference of level-1 networks under the NMSC. The input for this algorithm is a collection of unrooted topological gene trees, and the output is an unrooted semidirected species network.
Description
Dissertation (Ph.D.) University of Alaska Fairbanks, 2019
Table of Contents
Chapter 1: Introduction -- Chapter 2: The network multispecies coalescent model -- 1. The coalescent model -- 2. The network multispecies coalescent model (NMSC) -- Chapter 3: Identifying species network features from gene tree quartets under the coalescent model -- 1. Introduction -- 2. Phylogenetic networks -- 3. Structure of level-1 networks -- 4. The network multispecies coalescent model and quartet concordance factors -- 5. Computing quartet concordance factors -- 6. The cycle property -- 7. The big cycle property -- 8. Identifying cycles in networks -- 9. Further results in 32-cycles -- 10. Discussion -- 11. Appendix -- Chapter 4: NANUQ: A method for inferring species networks from gene trees under the coalescent model -- 1. Introduction -- 2. Phylogenetic networks -- 3. The network multispecies coalescent model and quartet concordance factors -- 4. Network split systems and distances -- 5. Quartet distance for level-1 networks -- 6. Split networks from the network quartet distance -- 7. The NANUQ algorithm for inference of phylogenetic networks -- 8. Examples -- Chapter 5: Conclusions and future work - References.
Date
2019-05
Type
Dissertation
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