ASTRAL: genome-scale coalescent-based species tree estimation

By Siavash Mirarab, Rezwana Reaz, Md. Shamsuzzoha Bayzid, Théo Zimmermann, M. Shel Swenson, Tandy J. Warnow. Bioinform., 2014

1,200 citations recorded by the source corpus.

Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: warnow@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ce18cc110884842047946a455d2962641780ba3f

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Citations in the corpus

Ultraconserved elements show utility in phylogenetic inference of Adephaga (Coleoptera) and suggest paraphyly of ‘Hydradephaga’ (2017, methodology): “A bootstrap ≥70% was considered as strong support (Hillis & Bull, 1993) Species tree inference was conducted using astral ii (Mirarab et al., 2014b; Mirarab & Warnow, 2015) and astrid (Vachaspati & Warnow, 2015), following the UCE processing steps of Alexander (2016), as astral and astrid have been…”
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era (2019, methodology): “S option), which can be used for subsequent coalescent (e.g., Mirarab et al. 2014) or concordance analyses (e.g., Minh et al. 2018).”
Enriching the ant tree of life: enhanced UCE bait set for genome‐scale phylogenetics of ants and other Hymenoptera (2017, neutral): “10.8 (Mirarab et al. 2014; Mirarab &Warnow 2015).”
ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes (2015, methodology): “ASTRAL (Mirarab et al., 2014a) was developed to enable coalescent-based analyses of these larger datasets. ASTRAL solves a likely NP-hard problem by constraining the allowed search space to those species trees that derive their bipartitions from an input set X, provided by the user. In the default s”
Tales from the crypt: genome mining from fungarium specimens improves resolution of the mushroom tree of life (2016, methodology): “The phylogenies produced by the 208-gene concatenated dataset, the MRE tree, and the ASTRAL tree analysis derived from the 208 single gene bootstrap trees are largely congruent, as are the topologies obtained from alternative datasets based on genes ranked by different criteria.”
PhyloNetworks: A Package for Phylogenetic Networks (2017, methodology): “The search is started from the topology obtained with ASTRAL (Mirarab et al. 2014) on the same input gene trees.”
A phylum-level phylogenetic classification of zygomycete fungi based on genome-scale data (2016, methodology): “1) and the ASTRAL (FIG.”
TreeShrink: fast and accurate detection of outlier long branches in collections of phylogenetic trees (2018, methodology): “Several reanalyses of this dataset using various methodologies have largely been consistent, except, for the position of the tree shrews that often changes [6, 30].”
HybPiper: Extracting coding sequence and introns for phylogenetics from high-throughput sequencing reads using target enrichment (2016, methodology): “This is especially true for “species tree” methods that require gene tree reconstructions as input (Mirarab et al., 2014).”
ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees (2018, methodology): “Examples include MP-EST [17], NJst [18], ASTRID [19], DISTIQUE [20], ASTRAL [21, 22] and STAR [23], which only use gene tree topologies, and GLASS [24] and STEAC [23], which also use branch lengths.”