Fast Coalescent-Based Computation of Local Branch Support from Quartet Frequencies

By Erfan Sayyari, Siavash Mirarab. Molecular biology and evolution, 2016

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Species tree reconstruction is complicated by effects of incomplete lineage sorting, commonly modeled by the multi-species coalescent model (MSC). While there has been substantial progress in developing methods that estimate a species tree given a collection of gene trees, less attention has been paid to fast and accurate methods of quantifying support. In this article, we propose a fast algorithm to compute quartet-based support for each branch of a given species tree with regard to a given set of gene trees. We then show how the quartet support can be used in the context of the MSC to compute (1) the local posterior probability (PP) that the branch is in the species tree and (2) the length of the branch in coalescent units. We evaluate the precision and recall of the local PP on a wide set of simulated and biological datasets, and show that it has very high precision and improved recall compared with multi-locus bootstrapping. The estimated branch lengths are highly accurate when gene tree estimation error is low, but are underestimated when gene tree estimation error increases. Computation of both the branch length and local PP is implemented as new features in ASTRAL.

Subfields: Genetics, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/96bf808e5dcb7aa1784c1c90d1c2a2539d82a9b0

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Citations in the corpus

ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees (2018, background): “Previous studies indicate that simply using the set of all bootstrap gene tree replicates as input to ASTRAL increases error [21], perhaps due to the increased noise [31, 35].”
Ultraconserved elements show utility in phylogenetic inference of Adephaga (Coleoptera) and suggest paraphyly of ‘Hydradephaga’ (2017, methodology): “Support was assessed by annotating the astral and astrid phylogenies with local posterior probabilities (PPs; Sayyari & Mirarab, 2016).”
Evaluating Fast Maximum Likelihood-Based Phylogenetic Programs Using Empirical Phylogenomic Data Sets (2017, methodology): “9 [Sayyari and Mirarab 2016]), the species tree inferred by these strategies became even more similar to the best-observed species trees, although FastTree-generated species trees still showed the greatest topological distances (supplementary table S7).”