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Accumulated Coalescence Rank and Excess Gene Count for Species Tree Inference

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Book cover Algorithms for Computational Biology (AlCoB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9702))

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Abstract

We propose a novel summary based method to infer species trees from input multi-locus gene trees with incomplete lineage sorting (ILS). The method extends an existing technique called STAR [13], which defines average coalescence rank between taxa pairs (couplets), to derive species trees using Neighbor-Joining (NJ) [20, 23]. Such coalescence rank, however, is ambiguous at couplet level. We propose two new couplet based distance measures, termed as accumulated coalescence rank (AcR), and excess gene tree leaves (XL), and show that their combination discriminates individual couplets better. We propose a new method AcRNJXL, which uses the proposed measures, for NJ based species tree construction. Results show that for biological datasets, AcRNJXL produces much better performance than STAR and other reference approaches, with the same time and space complexities as STAR.

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Acknowledgments

The first author acknowledges Tata Consultancy Services (TCS) for providing the research scholarship.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, 721302, WB, India

    Sourya Bhattacharyya & Jayanta Mukhopadhyay

Authors
  1. Sourya Bhattacharyya
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  2. Jayanta Mukhopadhyay
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Corresponding author

Correspondence to Sourya Bhattacharyya .

Editor information

Editors and Affiliations

  1. CETA-Ciemat, Trujillo, Spain

    María Botón-Fernández

  2. Rovira i Virgili University, Tarragona, Spain

    Carlos Martín-Vide

  3. University of Extremadura, Cáceres, Spain

    Sergio Santander-Jiménez

  4. University of Extremadura, Cáceres, Spain

    Miguel A. Vega-Rodríguez

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© 2016 Springer International Publishing Switzerland

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Bhattacharyya, S., Mukhopadhyay, J. (2016). Accumulated Coalescence Rank and Excess Gene Count for Species Tree Inference. In: Botón-Fernández, M., Martín-Vide, C., Santander-Jiménez, S., Vega-Rodríguez, M.A. (eds) Algorithms for Computational Biology. AlCoB 2016. Lecture Notes in Computer Science(), vol 9702. Springer, Cham. https://doi.org/10.1007/978-3-319-38827-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-38827-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38826-7

  • Online ISBN: 978-3-319-38827-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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