Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune system. Densely sampled phylogenetic trees can contain special features, including "sampled ancestors" in which we sequence a genotype along with its direct descendants, and "polytomies" in which multiple descendants arise simultaneously. These features are apparent after identifying zero-length branches in the tree. However, current maximum-likelihood based approaches are not capable of revealing such zero-length branches. In this paper, we find these zero-length branches by introducing adaptive-LASSO-type regularization estimators to phylogenetics, deriving their properties, and showing regularization to be a practically useful approach for phylogenetics.
@article{arxiv.1805.11073,
title = {Non-bifurcating phylogenetic tree inference via the adaptive LASSO},
author = {Cheng Zhang and Vu Dinh and Frederick A. Matsen},
journal= {arXiv preprint arXiv:1805.11073},
year = {2020}
}