Phylogenetic estimation with partial likelihood tensors

TL;DR

This paper introduces a novel method using partial likelihood tensors for molecular phylogenetics, offering significant computational savings over traditional likelihood calculation methods.

Contribution

The paper presents a new tensor-based approach for likelihood estimation in phylogenetics that improves computational efficiency compared to existing methods.

Findings

Significant computational savings demonstrated on simulated data.

The tensor approach generalizes partial likelihood vectors.

Enumeration of calculations shows efficiency gains.

Abstract

We present an alternative method for calculating likelihoods in molecular phylogenetics. Our method is based on partial likelihood tensors, which are generalizations of partial likelihood vectors, as used in Felsenstein's approach. Exploiting a lexicographic sorting and partial likelihood tensors, it is possible to obtain significant computational savings. We show this on a range of simulated data by enumerating all numerical calculations that are required by our method and the standard approach.