Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes

Author:

Gross Elizabeth,van Iersel Leo,Janssen Remie,Jones Mark,Long Colby,Murakami YukihiroORCID

Abstract

AbstractPhylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees. These networks are able to incorporate reticulate evolutionary events such as hybridization, introgression, and lateral gene transfer. Recently, network-based Markov models of DNA sequence evolution have been introduced along with model-based methods for reconstructing phylogenetic networks. For these methods to be consistent, the network parameter needs to be identifiable from data generated under the model. Here, we show that the semi-directed network parameter of a triangle-free, level-1 network model with any fixed number of reticulation vertices is generically identifiable under the Jukes–Cantor, Kimura 2-parameter, or Kimura 3-parameter constraints.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Nederlandse Organisatie voor Wetenschappelijk OnderzoekNederlandse Organisatie voor Wetenschappelijk Onderzoek

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Agricultural and Biological Sciences (miscellaneous),Modeling and Simulation

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Computational algebraic geometry for evolutionary biology;Proceedings of the 2024 International Symposium on Symbolic and Algebraic Computation;2024-07-16

2. Dimensions of Level-1 Group-Based Phylogenetic Networks;Bulletin of Mathematical Biology;2024-06-17

3. Ultrafast learning of four-node hybridization cycles in phylogenetic networks using algebraic invariants;Bioinformatics Advances;2024-01-01

4. Statistically Consistent Estimation of Rooted and Unrooted Level-1 Phylogenetic Networks from SNP Data;Lecture Notes in Computer Science;2024

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