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1. QuCo: quartet-based co-estimation of species trees and gene trees

   https://doi.org/10.1093/bioinformatics/btac265  

   Rabiee, Maryam; Mirarab, Siavash (June 2022, Bioinformatics)

   Abstract MotivationPhylogenomics faces a dilemma: on the one hand, most accurate species and gene tree estimation methods are those that co-estimate them; on the other hand, these co-estimation methods do not scale to moderately large numbers of species. The summary-based methods, which first infer gene trees independently and then combine them, are much more scalable but are prone to gene tree estimation error, which is inevitable when inferring trees from limited-length data. Gene tree estimation error is not just random noise and can create biases such as long-branch attraction. ResultsWe introduce a scalable likelihood-based approach to co-estimation under the multi-species coalescent model. The method, called quartet co-estimation (QuCo), takes as input independently inferred distributions over gene trees and computes the most likely species tree topology and internal branch length for each quartet, marginalizing over gene tree topologies and ignoring branch lengths by making several simplifying assumptions. It then updates the gene tree posterior probabilities based on the species tree. The focus on gene tree topologies and the heuristic division to quartets enables fast likelihood calculations. We benchmark our method with extensive simulations for quartet trees in zones known to produce biased species trees and further with larger trees. We also run QuCo on a biological dataset of bees. Our results show better accuracy than the summary-based approach ASTRAL run on estimated gene trees. Availability and implementationQuCo is available on https://github.com/maryamrabiee/quco. Supplementary informationSupplementary data are available at Bioinformatics online. 

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2. SODA: multi-locus species delimitation using quartet frequencies

   https://doi.org/10.1093/bioinformatics/btaa1010  

   Rabiee, Maryam; Mirarab, Siavash (December 2020, Bioinformatics)

   Ponty, Yann (Ed.)

   Abstract Motivation Species delimitation, the process of deciding how to group a set of organisms into units called species, is one of the most challenging problems in computational evolutionary biology. While many methods exist for species delimitation, most based on the coalescent theory, few are scalable to very large datasets, and methods that scale tend to be not accurate. Species delimitation is closely related to species tree inference from discordant gene trees, a problem that has enjoyed rapid advances in recent years. Results In this article, we build on the accuracy and scalability of recent quartet-based methods for species tree estimation and propose a new method called SODA for species delimitation. SODA relies heavily on a recently developed method for testing zero branch length in species trees. In extensive simulations, we show that SODA can easily scale to very large datasets while maintaining high accuracy. Availability and implementation The code and data presented here are available on https://github.com/maryamrabiee/SODA. Supplementary information Supplementary data are available at Bioinformatics online. 

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3. Gene tree quality affects empirical coalescent branch length estimation

   https://doi.org/10.1111/zsc.12512  

   Forthman, Michael; Braun, Edward L.; Kimball, Rebecca T. (September 2021, Zoologica Scripta)

   Abstract Assessing effects of gene tree error in coalescent analyses have widely ignored coalescent branch lengths (CBLs) despite their potential utility in estimating ancestral population demographics and detecting species tree anomaly zones. However, the ability of coalescent methods to obtain accurate estimates remains largely unexplored. Errors in gene trees should lead to underestimates of the true CBL, and for a given set of comparisons, longer CBLs should be more accurate. Here, we furthered our empirical understanding of how error in gene tree quality (i.e., locus informativeness and gene tree resolution) affect CBLs using four datasets comprised of ultraconserved elements (UCE) or exons for clades that exhibit wide ranges of branch lengths. For each dataset, we compared the impact of locus informativeness (assessed using number of parsimony‐informative sites) and gene tree resolution on CBL estimates. Our results, in general, showed that CBLs were drastically shorter when estimates included low informative loci. Gene tree resolution also had an impact on UCE datasets, with polytomous gene trees producing longer branches than randomly resolved gene trees. However, resolution did not appear to affect CBL estimates from the more informative exon datasets. Thus, as expected, gene tree quality affects CBL estimates, though this can generally be minimized by using moderate filtering to select more informative loci and/or by allowing polytomies in gene trees. These approaches, as well as additional contributions to improve CBL estimation, should lead to CBLs that are useful for addressing evolutionary and biological questions. 

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4. Statistically Consistent Rooting of Species Trees Under the Multispecies Coalescent Model

   https://doi.org/10.1007/978-3-031-29119-7_3  

   Tabatabaee, Y.; Roch, S.; Warnow, T. (April 2023, Research in Computational Molecular Biology. RECOMB 2023. Lecture Notes in Computer Science. Springer.)

   Tang, H. (Ed.)

   Rooted species trees are used in several downstream applications of phylogenetics. Most species tree estimation methods produce unrooted trees and additional methods are then used to root these unrooted trees. Recently, Quintet Rooting (QR) (Tabatabaee et al., ISMB and Bioinformatics 2022), a polynomial-time method for rooting an unrooted species tree given unrooted gene trees under the multispecies coalescent, was introduced. QR, which is based on a proof of identifiability of rooted 5-taxon trees in the presence of incomplete lineage sorting, was shown to have good accuracy, improving over other methods for rooting species trees when incomplete lineage sorting was the only cause of gene tree discordance, except when gene tree estimation error was very high. However, the statistical consistency of QR was left as an open question. Here, we present QR-STAR, a polynomial-time variant of QR that has an additional step for determining the rooted shape of each quintet tree. We prove that QR-STAR is statistically consistent under the multispecies coalescent model, and our simulation study shows that QR-STAR matches or improves on the accuracy of QR. QR-STAR is available in open source form at https://github.com/ytabatabaee/Quintet-Rooting. 

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5. “Correcting” Gene Trees to be More Like Species Trees Frequently Increases Topological Error

   https://doi.org/10.1093/gbe/evad094  

   Yan, Zhi; Ogilvie, Huw A; Nakhleh, Luay (June 2023, Genome Biology and Evolution)

   Holland, Barbara (Ed.)

   Abstract The evolutionary histories of individual loci in a genome can be estimated independently, but this approach is error-prone due to the limited amount of sequence data available for each gene, which has led to the development of a diverse array of gene tree error correction methods which reduce the distance to the species tree. We investigate the performance of two representatives of these methods: TRACTION and TreeFix. We found that gene tree error correction frequently increases the level of error in gene tree topologies by “correcting” them to be closer to the species tree, even when the true gene and species trees are discordant. We confirm that full Bayesian inference of the gene trees under the multispecies coalescent model is more accurate than independent inference. Future gene tree correction approaches and methods should incorporate an adequately realistic model of evolution instead of relying on oversimplified heuristics. 

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