SNaQ.jl: Improved scalability for phylogenetic network inference

Phylogenetic networks represent complex biological scenarios that are overlooked in trees, such as hybridization and horizontal gene transfer. Although numerous methods have been developed for phylogenetic network inference, their scalability is severely limited by the computational demands of likelihood optimization and the vastness of network space. Composite (or pseudo-) likelihood approaches like SNaQ have improved computational tractability for network inference, but they remain inadequate for datasets of sizes routinely handled by tree inference methods. Here, we introduce SNaQ.jl, a new standalone Julia package with the composite likelihood inference originally implemented within PhyloNetworks.jl as well as new scalability features that enhance computational efficiency through (1) parallelization of quartet likelihood calculations during composite likelihood computation, (2) weighted random selection of quartets, and (3) probabilistic decision-making during network search. Throug..., , # Data from: SNaQ.jl: Improved scalability for phylogenetic network inference

Simulation study and empirical analysis evaluating computational improvements made in [SNaQ.jl](https://github.com/JuliaPhylo/SNaQ.jl) version 1.1, a Julia package for phylogenetic network inference using composite likelihood. This version introduces significant scalability improvements, including parallelized quartet calculations, weighted quartet selection, and probabilistic network search, achieving up to 400% runtime improvements with maintained accuracy.

The data files related to this study are contained in the `dryad.zip` file here. Scripts used to analyze the data are contained in an accompanying Zenodo data repository.

## Replication instructions

Given the breadth of parameters tested in these simulations and the computational intensity of each simulation individually, it is necessary to perform this study on a high throughput computing cluster. For this purpose, we utilize HT Condor. You will find...,