ArticlePLoS computational biology2026
Triplet-based species tree estimation: Sensitivity to gene tree rooting (or lack thereof).
Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Species tree estimation often involves phylogenomic methodologies that incorporate multiple genes sampled across the genome. However, gene tree heterogeneity (discordance), often attributed to Incomplete Lineage Sorting (ILS), presents a significant challenge to accurate species tree inference. Triplet and quartet-based species tree estimation methods have attracted considerable attention owing to their provable statistical consistency in the presence of ILS. Yet, the adoption of rooted triplet-based approaches in the systematics community has been restricted, largely due to their limitations in handling unrooted gene trees-an issue not faced by quartet-based methods. Since the root placement directly influences the distribution of induced triplets in a gene tree, the accuracy of triplet-based methods is dependent on gene tree rooting accuracy. While there is extensive research on approaches for rooting unrooted gene trees, the choice of rooting techniques and their implications for triplet-based species tree estimation on realistic model conditions are greatly understudied. In this study, we carry out an extensive empirical analysis of different gene tree rooting strategies to assess the effects of rooting on triplet-based species tree inference. Across simulated and empirical datasets, triplet-based estimation using STELAR is generally robust to gene tree rooting, with several algorithmic rooting strategies yielding performance comparable to, and in some model conditions exceeding, that of STELAR on outgroup-rooted gene trees and the widely used quartet-based method ASTRAL. Our results highlight different model conditions in which rooting choices positively influence triplet-based species tree inference, thereby providing new insights into their potential utility in phylogenomic analyses.
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