ArticleBioinformatics (Oxford, England)2015
ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 346 papers, 1 of them a synthesis that pooled it.
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346 citing papers in PubMed, 1 synthesis or guideline pooled it.
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286 more citing papers are in PubMed but not listed here.
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2 authors.
Funding
Abstract
motivationThe estimation of species phylogenies requires multiple loci, since different loci can have different trees due to incomplete lineage sorting, modeled by the multi-species coalescent model. We recently developed a coalescent-based method, ASTRAL, which is statistically consistent under the multi-species coalescent model and which is more accurate than other coalescent-based methods on the datasets we examined. ASTRAL runs in polynomial time, by constraining the search space using a set of allowed 'bipartitions'. Despite the limitation to allowed bipartitions, ASTRAL is statistically consistent.
resultsWe present a new version of ASTRAL, which we call ASTRAL-II. We show that ASTRAL-II has substantial advantages over ASTRAL: it is faster, can analyze much larger datasets (up to 1000 species and 1000 genes) and has substantially better accuracy under some conditions. ASTRAL's running time is [Formula: see text], and ASTRAL-II's running time is [Formula: see text], where n is the number of species, k is the number of loci and X is the set of allowed bipartitions for the search space. AVAILABILITY AND IMPLEMENTATION: ASTRAL-II is available in open source at https://github.com/smirarab/ASTRAL and datasets used are available at http://www.cs.utexas.edu/~phylo/datasets/astral2/. CONTACT: smirarab@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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