Family-joining: A fast distance-based method for constructing generally labeled trees

TL;DR

The paper introduces a fast, distance-based method called family-joining (FJ) for constructing generally labeled trees that can include internal taxa and polytomies, improving evolutionary relationship modeling especially with densely sampled data.

Contribution

It presents a novel, efficient algorithm for building generally labeled trees with internal taxa and polytomies, outperforming existing methods in accuracy and support.

Findings

FJ-BIC effectively reconstructs correct trees across various simulations.

FJ-BIC trees align well with known transmission events in HIV data.

Internal branches in FJ-BIC trees have higher bootstrap support than traditional bifurcating trees.

Abstract

The widely used model for evolutionary relationships is a bifurcating tree with all taxa/observations placed at the leaves. This is not appropriate if the taxa have been densely sampled across evolutionary time and may be in a direct ancestral relationship, or if there is not enough information to fully resolve all the branching points in the evolutionary tree. In this paper, we present a fast distance-based agglomeration method called family-joining (FJ) for constructing so-called generally labeled trees in which taxa may be placed at internal vertices and the tree may contain polytomies. FJ constructs such trees on the basis of pairwise distances and a distance threshold. We tested three methods for threshold selection, FJ-AIC, FJ-BIC and FJ-CV, which minimize Akaike information criterion, Bayesian information criterion, and cross-validation error, respectively. When compared with related methods on simulated data, FJ-BIC was among the best at reconstructing the correct tree across a wide range of simulation scenarios. FJ-BIC was applied to HIV sequences sampled from individuals involved in a known transmission chain. The FJ-BIC tree was found to be compatible with almost all transmission events. On average, internal branches in the FJ-BIC tree have higher bootstrap support than branches in the leaf-labeled bifurcating tree constructed using RAxML. $36\%$ and $25\%$ of the internal branches in the FJ-BIC tree and RAxML tree, respectively, have bootstrap support greater than $70\%$. To the best of our knowledge the method presented here is the first attempt at modeling evolutionary relationships using generally labeled trees.