TriLoNet

Phylogenetic networks are a generalization of evolutionary trees that can be used
to represent reticulate processes such as hybridization and recombination. Here,
we introduce a new approach called TriLoNet (Trinet Level- one Network algorithm)
to construct such networks directly from sequence alignments which works by
piecing together smaller phylogenetic networks. More specifically, using a bottom
up approach similar to Neighbor-Joining, TriLoNet constructs level-1 networks
(networks that are somewhat more general than trees) from smaller level-1
networks on three taxa. In simulations, we show that TriLoNet compares well with
Lev1athan, a method for reconstructing level-1 networks from three-leaved trees.
In particular, in simulations we find that Lev1athan tends to generate networks
that overestimate the number of reticulate events as compared with those
generated by TriLoNet. We also illustrate TriLoNet's applicability using
simulated and real sequence data involving recombination, demonstrating that it
has the potential to reconstruct informative reticulate evolutionary histories.
TriLoNet has been implemented in JAVA and is freely available at
https://www.uea.ac.uk/computing/TriLoNet.

TriLoNet: Piecing Together Small Networks to Reconstruct Reticulate Evolutionary Histories.

TriLoNet (Trinet Level-one Network) is a software tool that constructs rooted level-1 phylogenetic networks from DNA sequence alignments to Reconstruct Reticulate Evolutionary Histories. The TriLoNet algorithm assembles small phylogenetic networks using a bottom-up approach similar to Neighbor-Joining.

TriLoNet

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