Inferring DAGs and Phylogenetic Networks from Least Common Ancestors
Anna Lindeberg, Anton Alfonsson, Vincent Moulton, Guillaume E. Scholz, Marc Hellmuth

TL;DR
This paper extends the concept of least common ancestors from trees to DAGs and phylogenetic networks, providing polynomial-time algorithms and a Python package for realizing LCA constraints.
Contribution
It introduces a theoretical framework and algorithms for DAG and phylogenetic network realization of LCA constraints, generalizing Aho et al.'s tree-based approach.
Findings
The $+$-closure captures all implied LCA relations in a constraint set.
A canonical DAG $G_R$ realizes the constraint set if and only if it is DAG-realizable.
The algorithms are implemented in the Python package RealLCA.
Abstract
A least common ancestor (LCA) of two leaves in a directed acyclic graph (DAG) is a vertex that is an ancestor of both leaves and has no proper descendant that is also their common ancestor. LCAs capture hierarchical relationships in rooted trees and, more generally, in DAGs. In 1981, Aho et al. introduced the problem of determining whether a set of pairwise LCA constraints on a set , of the form with , can be realized by a rooted tree whose leaf set is , such that whenever , the LCA of is a descendant of that of . They also presented a polynomial-time algorithm, BUILD, to solve this problem. However, many such constraint systems cannot be realized by any tree, prompting the question of whether they can be realized by a more general DAG. We extend Aho et al.'s framework from trees to DAGs, providing both theoretical and…
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