Neighbor-net

NeighborNet[1] is an algorithm for constructing phylogenetic networks which is loosely based on the neighbor joining algorithm. Like neighbor joining, the method takes a distance matrix as input, and works by agglomerating clusters. However, the NeighborNet algorithm can lead to collections of clusters which overlap and do not form a hierarchy, and are represented using a type of phylogenetic network called a split network. If the distance matrix satisfies the Kalmanson combinatorial conditions then Neighbor-net will return the corresponding circular ordering.[2][3] The method is implemented in the SplitsTree package.

Examples of the application of Neighbor-net can be found in virology[4] , horticulture,[5] dinosaur genetics,[6] comparative linguistics, and archaeology.[7]

An example of a neighbor-net phylogenetic network generated by SplitsTree v4.6.

References

  1. Bryant and Moulton : Neighbor-net, an agglomerative method for the construction of phylogenetic networks - Molecular Biology and Evolution 21 (2003)
  2. Bryant, D. and Moulton, V. and Spillner, A. 2007. Consistency of the NeighborNet algorithm. Algorithms in Molecular Biology, 2,8
  3. D. Levy and L. Pachter, The neighbor-net algorithm, Advances in Applied Mathematics, doi:10.1016/j.aam.2010.09.002.
  4. J. Schmidt-Chanasit, A. Bialonski, P. Heinemann, R. Ulrich, S. Gunther, H. Rabenau, and H. Doerr. A10-year molecular survey of herpes simplex virus type 1 in germany demonstrates a stable and high prevalence of genotypes a and b. Journal of Clinical Virology, 44(3):235 -- 237, 2009.
  5. Killian, B. Özkan, H., Deusch, O., Effgen, S., Brandolini, A., Kohl, J., Martin, W., Salamini, F. (2007). Independent wheat B and G genome origins in outcrossing Aegilops progenitor haplotypes. Molecular Biology and Evolution 24(1):217-227.
  6. M. Buckley and 27 others. Comment on``protein sequences from Mastodon and Tyrannosaurus Rex revealed by mass spectrometry". Science, 319(5859):33, 2008.
  7. S. Shennan. Pattern and process in cultural evolution. University of California Press, 2009.
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