Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes
Elizabeth Gross (University of Hawaii at Manoa)
Leo van Iersel (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Remie Janssen (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Mark Jones (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Colby Long (The College of Wooster)
Yukihiro Murakami (TU Delft - Electrical Engineering, Mathematics and Computer Science)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
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.
help_outline