ArticleBioinformatics (Oxford, England)2022
Quintet Rooting: rooting species trees under the multi-species coalescent model.
Article in Bioinformatics (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Triplet-based species tree estimation: Sensitivity to gene tree rooting (or lack thereof).PLoS computational biology · 2026Article
- Road to Extinction? Past and Present Population Structure and Genomic Diversity in the Koala.Molecular biology and evolution · 2025Article
- Phylogenomic branch length estimation using quartets.Bioinformatics (Oxford, England) · 2023Article
- DISCO+QR: rooting species trees in the presence of GDL and ILS.Bioinformatics advances · 2023Article
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3 authors.
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Abstract
motivationRooted species trees are a basic model with multiple applications throughout biology, including understanding adaptation, biodiversity, phylogeography and co-evolution. Because most species tree estimation methods produce unrooted trees, methods for rooting these trees have been developed. However, most rooting methods either rely on prior biological knowledge or assume that evolution is close to clock-like, which is not usually the case. Furthermore, most prior rooting methods do not account for biological processes that create discordance between gene trees and species trees.
resultsWe present Quintet Rooting (QR), a method for rooting species trees based on a proof of identifiability of the rooted species tree under the multi-species coalescent model established by Allman, Degnan and Rhodes (J. Math. Biol., 2011). We show that QR is generally more accurate than other rooting methods, except under extreme levels of gene tree estimation error. AVAILABILITY AND IMPLEMENTATION: Quintet Rooting is available in open source form at https://github.com/ytabatabaee/Quintet-Rooting. The simulated datasets used in this study are from a prior study and are available at https://www.ideals.illinois.edu/handle/2142/55319. The biological dataset used in this study is also from a prior study and is available at http://gigadb.org/dataset/101041. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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