On the optimality of the neighbor-joining algorithm

<p>Abstract</p> <p>The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree...

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Main Authors: Pachter Lior, Huggins Peter, Eickmeyer Kord, Yoshida Ruriko
Format: Article
Language:English
Published: BMC 2008-04-01
Series:Algorithms for Molecular Biology
Online Access:http://www.almob.org/content/3/1/5
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spelling doaj-499a2494a67c44e08a5ea9ae75c3bda82020-11-24T23:28:07ZengBMCAlgorithms for Molecular Biology1748-71882008-04-0131510.1186/1748-7188-3-5On the optimality of the neighbor-joining algorithmPachter LiorHuggins PeterEickmeyer KordYoshida Ruriko<p>Abstract</p> <p>The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion. We use the fact that the NJ tree topology and the BME tree topology are determined by polyhedral subdivisions of the spaces of dissimilarity maps <inline-formula><m:math name="1748-7188-3-5-i1" xmlns:m="http://www.w3.org/1998/Math/MathML"><m:semantics><m:mrow><m:msubsup><m:mi mathvariant="script">R</m:mi><m:mo>+</m:mo><m:mrow><m:mrow><m:mo>(</m:mo><m:mrow><m:mtable><m:mtr><m:mtd><m:mi>n</m:mi></m:mtd></m:mtr><m:mtr><m:mtd><m:mn>2</m:mn></m:mtd></m:mtr></m:mtable></m:mrow><m:mo>)</m:mo></m:mrow></m:mrow></m:msubsup></m:mrow><m:annotation encoding="MathType-MTEF"> MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaWenfgDOvwBHrxAJfwnHbqeg0uy0HwzTfgDPnwy1aaceaGae83gHi1aa0baaSqaaiabgUcaRaqaamaabmaabaqbaeqabiqaaaqaaiabd6gaUbqaaiabikdaYaaaaiaawIcacaGLPaaaaaaaaa@3BA1@</m:annotation></m:semantics></m:math></inline-formula> to study the optimality of the neighbor-joining algorithm. In particular, we investigate and compare the polyhedral subdivisions for <it>n </it>≤ 8. This requires the measurement of volumes of spherical polytopes in high dimension, which we obtain using a combination of Monte Carlo methods and polyhedral algorithms. Our results include a demonstration that highly unrelated trees can be co-optimal in BME reconstruction, and that NJ regions are not convex. We obtain the <it>l</it><sub>2 </sub>radius for neighbor-joining for <it>n </it>= 5 and we conjecture that the ability of the neighbor-joining algorithm to recover the BME tree depends on the diameter of the BME tree.</p> http://www.almob.org/content/3/1/5
collection DOAJ
language English
format Article
sources DOAJ
author Pachter Lior
Huggins Peter
Eickmeyer Kord
Yoshida Ruriko
spellingShingle Pachter Lior
Huggins Peter
Eickmeyer Kord
Yoshida Ruriko
On the optimality of the neighbor-joining algorithm
Algorithms for Molecular Biology
author_facet Pachter Lior
Huggins Peter
Eickmeyer Kord
Yoshida Ruriko
author_sort Pachter Lior
title On the optimality of the neighbor-joining algorithm
title_short On the optimality of the neighbor-joining algorithm
title_full On the optimality of the neighbor-joining algorithm
title_fullStr On the optimality of the neighbor-joining algorithm
title_full_unstemmed On the optimality of the neighbor-joining algorithm
title_sort on the optimality of the neighbor-joining algorithm
publisher BMC
series Algorithms for Molecular Biology
issn 1748-7188
publishDate 2008-04-01
description <p>Abstract</p> <p>The popular neighbor-joining (NJ) algorithm used in phylogenetics is a greedy algorithm for finding the balanced minimum evolution (BME) tree associated to a dissimilarity map. From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion. We use the fact that the NJ tree topology and the BME tree topology are determined by polyhedral subdivisions of the spaces of dissimilarity maps <inline-formula><m:math name="1748-7188-3-5-i1" xmlns:m="http://www.w3.org/1998/Math/MathML"><m:semantics><m:mrow><m:msubsup><m:mi mathvariant="script">R</m:mi><m:mo>+</m:mo><m:mrow><m:mrow><m:mo>(</m:mo><m:mrow><m:mtable><m:mtr><m:mtd><m:mi>n</m:mi></m:mtd></m:mtr><m:mtr><m:mtd><m:mn>2</m:mn></m:mtd></m:mtr></m:mtable></m:mrow><m:mo>)</m:mo></m:mrow></m:mrow></m:msubsup></m:mrow><m:annotation encoding="MathType-MTEF"> MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaWenfgDOvwBHrxAJfwnHbqeg0uy0HwzTfgDPnwy1aaceaGae83gHi1aa0baaSqaaiabgUcaRaqaamaabmaabaqbaeqabiqaaaqaaiabd6gaUbqaaiabikdaYaaaaiaawIcacaGLPaaaaaaaaa@3BA1@</m:annotation></m:semantics></m:math></inline-formula> to study the optimality of the neighbor-joining algorithm. In particular, we investigate and compare the polyhedral subdivisions for <it>n </it>≤ 8. This requires the measurement of volumes of spherical polytopes in high dimension, which we obtain using a combination of Monte Carlo methods and polyhedral algorithms. Our results include a demonstration that highly unrelated trees can be co-optimal in BME reconstruction, and that NJ regions are not convex. We obtain the <it>l</it><sub>2 </sub>radius for neighbor-joining for <it>n </it>= 5 and we conjecture that the ability of the neighbor-joining algorithm to recover the BME tree depends on the diameter of the BME tree.</p>
url http://www.almob.org/content/3/1/5
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AT hugginspeter ontheoptimalityoftheneighborjoiningalgorithm
AT eickmeyerkord ontheoptimalityoftheneighborjoiningalgorithm
AT yoshidaruriko ontheoptimalityoftheneighborjoiningalgorithm
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