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NeighborNet: An Agglomerative Method for the Construction of Planar Phylogenetic Networks

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Algorithms in Bioinformatics (WABI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2452))

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Abstract

We introduce NeighborNet, a network construction and data representation method that combines aspects of the neighbor joining (NJ) and SplitsTree. Like NJ, NeighborNet uses agglomeration: taxa are combined into progressively larger and larger overlapping clusters. Like SplitsTree, NeighborNet constructs networks rather than trees, and so can be used to represent multiple phylogenetic hypotheses simultaneously, or to detect complex evolutionary processes like recombination, lateral transfer and hybridization. NeighborNet tends to produce networks that are substantially more resolved than those made with SplitsTree. The method is efficient (O(n 3) time) and is well suited for the preliminary analyses of complex phylogenetic data. We report results of three case studies: one based on mitochondrial gene order data from early branching eukaryotes, another based on nuclear sequence data from New Zealand alpine buttercups (Ranunculi), and a third on poorly corrected synthetic data.

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Author information

Authors and Affiliations

  1. McGill Centre for Bioinformatics, 3775 University St, Montréal, H3A 2B4, Québec

    David Bryant

  2. Linnaeus Center for Bioinformatics, Uppsala University, Box 598, 751 24, Uppsala, Sweden

    Vincent Moulton

Authors
  1. David Bryant
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  2. Vincent Moulton
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Editor information

Editors and Affiliations

  1. IMIM-UPF-CRG, Dr. Aiguader 80, 08003, Barcelona, Spain

    Roderic Guigó

  2. Department of Computer Science, University of California, 95616, Davis, CA, USA

    Dan Gusfield

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© 2002 Springer-Verlag Berlin Heidelberg

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Bryant, D., Moulton, V. (2002). NeighborNet: An Agglomerative Method for the Construction of Planar Phylogenetic Networks. In: Guigó, R., Gusfield, D. (eds) Algorithms in Bioinformatics. WABI 2002. Lecture Notes in Computer Science, vol 2452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45784-4_28

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  • DOI: https://doi.org/10.1007/3-540-45784-4_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44211-0

  • Online ISBN: 978-3-540-45784-8

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