4.7 Article

Species Tree Inference from Gene Splits by Unrooted STAR Methods

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2016.2604812

关键词

Coalescent model; STAR algorithm; NJ(st); species tree

资金

  1. National Science Foundation
  2. U.S. Department of Homeland Security
  3. U.S. Department of Agriculture through NSF [EF-0832858]
  4. University of Tennessee, Knoxville
  5. National Institutes of Health under Joint DMS/NIGMS Initiative to Support Research at the Interface of the Biological and Mathematical Sciences [R01 GM117590]
  6. Direct For Biological Sciences
  7. Div Of Biological Infrastructure [1300426] Funding Source: National Science Foundation

向作者/读者索取更多资源

The NJ(st) method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a four-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here, we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects NJ(st) to a generalization of the STAR method of Liu, Pearl, and Edwards, and a previous theoretical analysis of it. We further show NJ(st) utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency.

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