title: Quartet-net: a quartet-based method to reconstruct phylogenetic networks.
abstract: Phylogenetic networks can model reticulate evolutionary events such as hybridization, recombination, and horizontal gene transfer. However, reconstructing such networks is not trivial. Popular character-based methods are computationally inefficient, whereas distance-based methods cannot guarantee reconstruction accuracy because pairwise genetic distances only reflect partial information about a reticulate phylogeny. To balance accuracy and computational efficiency, here we introduce a quartet-based method to construct a phylogenetic network from a multiple sequence alignment. Unlike distances that only reflect the relationship between a pair of taxa, quartets contain information on the relationships among four taxa; these quartets provide adequate capacity to infer a more accurate phylogenetic network. In applications to simulated and biological data sets, we demonstrate that this novel method is robust and effective in reconstructing reticulate evolutionary events and it has the potential to infer more accurate phylogenetic distances than other conventional phylogenetic network construction methods such as Neighbor-Joining, Neighbor-Net, and Split Decomposition. This method can be used in constructing phylogenetic networks from simple evolutionary events involving a few reticulate events to complex evolutionary histories involving a large number of reticulate events. A software called "Quartet-Net" is implemented and available at http://sysbio.cvm.msstate.edu/QuartetNet/.
authors.affiliation: Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, USA.
authors.forename: Jialiang
authors.initials: J
authors.lastname: Yang
authors.forename: Stefan
authors.initials: S
authors.lastname: Grünewald
authors.forename: Xiu-Feng
authors.initials: XF
authors.lastname: Wan
mesh_terms: D019143:Evolution, Molecular; D008957:Models, Genetic; D008962:Models, Theoretical; D010802:Phylogeny; D012984:Software