Regularizing and Normalizing DAGs and Phylogenetic Networks

TL;DR

This paper introduces a unified framework for simplifying DAGs and phylogenetic networks by analyzing clusters, least common ancestors, and visibility, leading to new regularization and normalization methods.

Contribution

It develops an LCA-based regularization procedure and compares it with normalization, providing a comprehensive approach to DAG simplification.

Findings

The $ eg_i(G)$ procedure preserves key LCAs and is cluster-isomorphic.

Regularization and normalization coincide under certain conditions.

The framework unifies cluster, LCA, and visibility-based DAG simplifications.

Abstract

Phylogenetic networks and, more generally, directed acyclic graphs (DAGs) represent hierarchical structure beyond trees, for instance in the presence of reticulate evolutionary events such as hybridization or horizontal gene transfer. A central question is which parts of such graphs are essential with respect to leaf-observable information, and which parts can be removed without changing this information. Resolving this question can lead to principled simplification methods for phylogenetic networks, such as the recent normalization approach of Francis et al. In this paper, we study this question from three related perspectives: clusters displayed by a DAG $G$, least common ancestors (LCAs) of subsets of its leaf set, and visibility, a path-based property of vertices. We first introduce an LCA-based simplification procedure called $i$-regularization. For a DAG $G$ and $i\geq 1$, the DAG $\reg_i(G)$ retains precisely those vertices that occur as unique LCAs of leaf subsets of size at most $i$, removes the remaining non-leaf vertices by a graph-editing operation $\ominus$, and then deletes shortcuts. We show that $\reg_i(G)$ preserves all such LCAs, is $i$-lca-relevant, and admits a cluster-level description: it is regular, i.e., isomorphic to the Hasse diagram of the corresponding lca-clusters. We then compare LCA-based regularization with normalization. Using the same $\ominus$-operator, we describe the cover construction underlying normalization, identify visible vertices that are nevertheless removed, and characterize when regularization and normalization coincide. Together, these results provide a unified framework for cluster-based, LCA-based, and visibility-based simplifications of DAGs and phylogenetic networks.