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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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 |
work_keys_str_mv |
AT pachterlior ontheoptimalityoftheneighborjoiningalgorithm AT hugginspeter ontheoptimalityoftheneighborjoiningalgorithm AT eickmeyerkord ontheoptimalityoftheneighborjoiningalgorithm AT yoshidaruriko ontheoptimalityoftheneighborjoiningalgorithm |
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