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

被引:0
作者
Elizabeth Gross
Leo van Iersel
Remie Janssen
Mark Jones
Colby Long
Yukihiro Murakami
机构
[1] University of Hawai‘i at Mānoa,Department of Mathematics
[2] Delft University of Technology,Delft Institute of Applied Mathematics
[3] The College of Wooster,undefined
来源
Journal of Mathematical Biology | 2021年 / 83卷
关键词
Phylogenetic networks; Identifiability; Reticulation; Markov processes; 05C05; 92B10; 92D15;
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摘要
Phylogenetic 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.
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