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Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss

Brandon Legried, View ORCID ProfileErin K. Molloy, View ORCID ProfileTandy Warnow, View ORCID ProfileSébastien Roch
doi: https://doi.org/10.1101/821439
Brandon Legried
1University of Wisconsin-Madison, Madison, WI, USA
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Erin K. Molloy
2University of Illinois at Urbana-Champaign, Urbana, IL, USA
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Tandy Warnow
2University of Illinois at Urbana-Champaign, Urbana, IL, USA
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Sébastien Roch
1University of Wisconsin-Madison, Madison, WI, USA
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  • ORCID record for Sébastien Roch
  • For correspondence: roch@math.wisc.edu
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Abstract

Phylogenomics—the estimation of species trees from multi-locus datasets—is a common step in many biological studies. However, this estimation is challenged by the fact that genes can evolve under processes, including incomplete lineage sorting (ILS) and gene duplication and loss (GDL), that make their trees different from the species tree. In this paper, we address the challenge of estimating the species tree under GDL. We show that species trees are identifiable under a standard stochastic model for GDL, and that the polynomial-time algorithm ASTRAL-multi, a recent development in the ASTRAL suite of methods, is statistically consistent under this GDL model. We also provide a simulation study evaluating ASTRAL-multi for species tree estimation under GDL.

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Posted October 29, 2019.
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Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss
Brandon Legried, Erin K. Molloy, Tandy Warnow, Sébastien Roch
bioRxiv 821439; doi: https://doi.org/10.1101/821439
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Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss
Brandon Legried, Erin K. Molloy, Tandy Warnow, Sébastien Roch
bioRxiv 821439; doi: https://doi.org/10.1101/821439

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