Invariants for level-1 phylogenetic networks under the random walk 4-state Markov model

Abstract: Phylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees, such as hybridization, introgression, and lateral gene transfer. Studying phylogenetic networks under a statistical model of DNA sequence evolution can aid the inference of phylogenetic networks. Most notably Markov models like the Jukes-Cantor or Kimura-3 model can been employed to infer a phylogenetic network using phylogenetic invariants. In this article we determine all quadratic invariants for sunlet networks under the random walk 4-state Markov model, which includes the aforementioned models. Taking toric fiber products of trees and sunlet networks, we obtain a new class of invariants for level-1 phylogenetic networks under the same model. Furthermore, we apply our results to the identifiability problem of a network parameter. In particular, we prove that our new class of invariants of the studied model is not sufficient to derive identifiability of quarnets (4-leaf networks). Moreover, we provide an efficient method that is faster and more reliable than the state-of-the-art in finding a significant number of invariants for many level-1 phylogenetic networks.