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QR-STAR: A Polynomial-Time Statistically Consistent Method for Rooting Species Trees Under the Coalescent.

Yasamin Tabatabaee1, Sebastien Roch2, Tandy Warnow1

  • 1Department of Computer Science, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 30, 2023
PubMed
Summary
This summary is machine-generated.

We developed QR-STAR, a statistically consistent algorithm for rooting species trees from gene trees using the multispecies coalescent model. This new method improves accuracy and has polynomial sample complexity for accurate phylogenetic inference.

Keywords:
multispecies coalescentrootingspecies tree estimationstatistical consistency

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Area of Science:

  • Computational Biology
  • Phylogenetics
  • Evolutionary Biology

Background:

  • Rooting unrooted species trees from gene trees is crucial for understanding evolutionary relationships.
  • The multispecies coalescent (MSC) model is a standard framework for gene tree evolution.
  • Previous algorithms like Quintet Rooting (QR) showed promise but lacked proven statistical consistency.

Purpose of the Study:

  • To develop a statistically consistent algorithm for rooting species trees under the MSC model.
  • To improve upon the accuracy and theoretical guarantees of existing methods.
  • To provide a robust computational tool for phylogenetic inference.

Main Methods:

  • Introduced QR-STAR, a novel variant of the Quintet Rooting (QR) algorithm.
  • Incorporated an additional step and a modified cost function into QR.
  • Proved statistical consistency of QR-STAR under the MSC model.
  • Derived sample complexity bounds for QR-STAR, including a variant with polynomial sample complexity using 'short quintets'.

Main Results:

  • QR-STAR is statistically consistent for rooting species trees under the MSC.
  • The algorithm achieves polynomial sample complexity, particularly the 'short quintets' variant.
  • Simulations demonstrate that QR-STAR matches or surpasses the accuracy of the original QR algorithm across various conditions.

Conclusions:

  • QR-STAR offers a statistically sound and accurate method for inferring rooted species trees from gene trees.
  • The algorithm advances the field of phylogenetics by providing theoretical guarantees and improved performance.
  • QR-STAR is available as an open-source tool to facilitate research in evolutionary biology.