ASTRAL-III: Increased Scalability and Impacts of Contracting Low Support Branches

Abstract

Discordances between species trees and gene trees can complicate phylogenetics reconstruction. ASTRAL is a leading method for inferring species trees given gene trees while accounting for incomplete lineage sorting. It finds the tree that shares the maximum number of quartets with input trees, drawing bipartitions from a predefined set of bipartitions X. In this paper, we introduce ASTRAL-III, which substantially improves on ASTRAL-II in terms of running time by handling polytomies more efficiently, exploiting similarities between gene trees, and trimming unnecessary parts of the search space. The asymptotic running time in the presence of polytomies is reduced from \(O(n^3k|X|^{{1.726}})\) for n species and k genes to \(O(D|X|^{1.726})\) where \(D=O(nk)\) is the sum of degrees of all unique nodes in input trees. ASTRAL-III enables us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations and on real data, we show that removing branches with very low support improves accuracy while overly aggressive filtering is harmful.