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A Distance-Based Method for Inferring Phylogenetic Networks in the Presence of Incomplete Lineage Sorting

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Bioinformatics Research and Applications (ISBRA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9096))

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Abstract

Hybridization and incomplete lineage sorting (ILS) are two evolutionary processes that result in incongruence among gene trees and complicate the identification of the species evolutionary history. Although a wide array of methods have been developed for inference of species phylogeny in the presence of each of these two processes individually, methods that can account for both of them simultaneously have been introduced recently. However, these new methods are based on the optimization of certain criteria, such as parsimony and likelihood, and are thus computationally intensive. In this paper, we present a novel distance-based method for inferring phylogenetic networks in the presence of ILS that makes use of pairwise distances computed from multiple sampled loci across the genome. We show in simulation studies that the method infers accurate networks when the estimated pairwise distances have good accuracy. Furthermore, we devised a heuristic for post-processing the inferred network to remove potential false positive reticulation events. The method is computationally very efficient and is applicable to very large data sets.

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Authors and Affiliations

  1. Department of Computer Science, Rice University, 6100 Main Street, Houston, TX, 77005, USA

    Yun Yu & Luay Nakhleh

Authors
  1. Yun Yu
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  2. Luay Nakhleh
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Correspondence to Yun Yu .

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Editors and Affiliations

  1. Georgia State University, Atlanta, USA

    Robert Harrison

  2. Old Dominion University, Norfolk, USA

    Yaohang Li

  3. University of Connecticut, Storrs, Connecticut, USA

    Ion Măndoiu

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Yu, Y., Nakhleh, L. (2015). A Distance-Based Method for Inferring Phylogenetic Networks in the Presence of Incomplete Lineage Sorting. In: Harrison, R., Li, Y., Măndoiu, I. (eds) Bioinformatics Research and Applications. ISBRA 2015. Lecture Notes in Computer Science(), vol 9096. Springer, Cham. https://doi.org/10.1007/978-3-319-19048-8_32

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  • DOI: https://doi.org/10.1007/978-3-319-19048-8_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19047-1

  • Online ISBN: 978-3-319-19048-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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