Optimizing Phylogenetic Supertrees Using Answer Set Programming

TL;DR

This paper explores using answer set programming with two different encodings to construct phylogenetic supertrees, demonstrating its application on felid species and comparing it to traditional MRP methods.

Contribution

It introduces a novel ASP encoding for supertree construction based on direct projections, alongside an existing quartet-based encoding, advancing computational methods in phylogenetics.

Findings

ASP approach successfully constructs supertrees for Felidae.

Comparison shows ASP results are competitive with MRP methods.

New encoding improves flexibility in representing phylogenetic relationships.

Abstract

The supertree construction problem is about combining several phylogenetic trees with possibly conflicting information into a single tree that has all the leaves of the source trees as its leaves and the relationships between the leaves are as consistent with the source trees as possible. This leads to an optimization problem that is computationally challenging and typically heuristic methods, such as matrix representation with parsimony (MRP), are used. In this paper we consider the use of answer set programming to solve the supertree construction problem in terms of two alternative encodings. The first is based on an existing encoding of trees using substructures known as quartets, while the other novel encoding captures the relationships present in trees through direct projections. We use these encodings to compute a genus-level supertree for the family of cats (Felidae). Furthermore, we compare our results to recent supertrees obtained by the MRP method.