A statistical method for massively scalable inference of phylogenetic networks

Music City Center 

We will introduce a new divide-and-conquer algorithm to merge large explicit networks up to 1000 taxa. We conduct a robust simulation study that shows that our algorithm matches the accuracy of SNaQ on small datasets while drastically improving runtimes, and that drastically outperforms heuristic methods on large datasets while maintaining computational feasibility. Last, we illustrate its performance on an empirical dataset of over 1000 plants.

networks