ASTRAL-II: coalescent-based species tree estimation with many hundreds of taxa and thousands of genes

• Published in: Bioinformatics (Oxford, England) Vol. 31; no. 12; pp. i44 - i52
• Main Authors: Mirarab, Siavash, Warnow, Tandy
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.06.2015
• Subjects: Algorithms; Computer Simulation; Data Interpretation, Statistical; Genes, Plant; Genetic Speciation; Genomics; Phylogeny; Plants - classification; Plants - genetics
• ISSN: 1367-4803; 1367-4811; 1367-4811
• DOI: 10.1093/bioinformatics/btv234

Motivation: The 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. Results: We 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 O(n2k|X|2), and ASTRAL-II’s running time is O(nk|X|2), 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.