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Cluster Matching Distance for Rooted Phylogenetic Trees

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Bioinformatics Research and Applications (ISBRA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10847))

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Abstract

Phylogenetic trees are fundamental to biology and are benefitting several other research areas. Various methods have been developed for inferring such trees, and comparing them is an important problem in computational phylogenetics. Addressing this problem requires tree measures, but all of them suffer from problems that can severely limit their applicability in practice. This also holds true for one of the oldest and most widely used tree measures, the Robinson-Foulds distance. While this measure is satisfying the properties of a metric and is efficiently computable, it has a negatively skewed distribution, a poor range of discrimination and diameter, and may not be robust when comparing erroneous trees. The cluster distance is a measure for comparing rooted trees that can be interpreted as a weighted version of the Robinson-Foulds distance. We show that when compared with the Robinson-Foulds distance, the cluster distance is much more robust towards small errors in the compared trees, and has a significantly improved distribution and range.

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Acknowledgments

This material is based upon work supported by the National Science Foundation under Grant No. 1617626.

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Authors and Affiliations

  1. Department of Computer Science and Computer Engineering, California State University Long Beach, Long Beach, CA, 90840, USA

    Jucheol Moon

  2. Department of Computer Science, Iowa State University, Ames, IA, 50011, USA

    Oliver Eulenstein

Authors
  1. Jucheol Moon
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  2. Oliver Eulenstein
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Correspondence to Jucheol Moon .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Fa Zhang

  2. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  3. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  4. Chinese Academy of Sciences, Beijing, China

    Shihua Zhang

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Moon, J., Eulenstein, O. (2018). Cluster Matching Distance for Rooted Phylogenetic Trees. In: Zhang, F., Cai, Z., Skums, P., Zhang, S. (eds) Bioinformatics Research and Applications. ISBRA 2018. Lecture Notes in Computer Science(), vol 10847. Springer, Cham. https://doi.org/10.1007/978-3-319-94968-0_31

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  • DOI: https://doi.org/10.1007/978-3-319-94968-0_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94967-3

  • Online ISBN: 978-3-319-94968-0

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