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

Bioinformatics. 2015 Jun 15;31(12):i44-52. 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 [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 and datasets used are available at


Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Data Interpretation, Statistical
  • Genes, Plant*
  • Genetic Speciation*
  • Genomics
  • Phylogeny*
  • Plants / classification*
  • Plants / genetics*