The neighbor-net algorithm

Levy, Dan, Pachter, Lior (2011) The neighbor-net algorithm. Advances in Applied Mathematics, 47 (2). pp. 240-258. ISSN 0196-8858

URL: http://www.sciencedirect.com/science/article/pii/S...
DOI: 10.1016/j.aam.2010.09.002

Abstract

The neighbor-joining algorithm is a popular phylogenetics method for constructing trees from dissimilarity maps. The neighbor-net algorithm is an extension of the neighbor-joining algorithm and is used for constructing split networks. We begin by describing the output of neighbor-net in terms of the tessellation of M ¯ 0 n ( R ) by associahedra. This highlights the fact that neighbor-net outputs a tree in addition to a circular ordering and we explain when the neighbor-net tree is the neighbor-joining tree. A key observation is that the tree constructed in existing implementations of neighbor-net is not a neighbor-joining tree. Next, we show that neighbor-net is a greedy algorithm for finding circular split systems of minimal balanced length. This leads to an interpretation of neighbor-net as a greedy algorithm for the traveling salesman problem. The algorithm is optimal for Kalmanson matrices, from which it follows that neighbor-net is consistent and has optimal radius 1 2 . We also provide a statistical interpretation for the balanced length for a circular split system as the length based on weighted least squares estimates of the splits. We conclude with applications of these results and demonstrate the implications of our theorems for a recently published comparison of Papuan and Austronesian languages.

Item Type: Paper
Uncontrolled Keywords: Neighbor-net Neighbor-joining Circular decomposable metric Traveling salesman problem Kalmanson conditions Balanced length Minimum evolution Splits network
Subjects: bioinformatics
bioinformatics > computational biology
CSHL Authors:
Communities: CSHL labs > Levy lab
Depositing User: Matt Covey
Date: 2011
Date Deposited: 23 Jul 2015 15:38
Last Modified: 23 Jul 2015 15:38
URI: http://repository.cshl.edu/id/eprint/31646

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