An alternating least squares approach to inferring phylogenies from pairwise distances
An alternating least squares approach to inferring phylogenies from pairwise distances
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DOI：
10.2307/2413638
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发表时间：
1997-03-01
影响因子：
6.5
通讯作者：
Felsenstein, J
中科院分区：
文献类型：
--
作者：
Felsenstein, J
提出了一种计算方法，用于最小化物种之间观察到的和预期的成对距离之间的差异的加权平方和，其中期望是由加性树模型生成的。 Pitch 和 Margoliash (1967, Science 155:279-284) 以及 Cavalli-Sforza 和 Edwards (1967, Evolution 21:550-570) 的标准都是加权最小二乘法，具有不同的权重。该方法提出了一次迭代树中相邻分支的长度三个。迭代过程中加权平方和永远不会增加，并且迭代逼近平方和曲面上的驻点。这种迭代方法使得维持分支长度永远不会变为负值的约束变得特别容易，尽管也可以允许负分支长度。该方法在计算机程序 FITCH 中实现，该程序自 1982 年起作为用于推断系统发育的程序 PHYLIP 包的一部分进行分发，并且也在 PAUP* 中实现。使用一些模拟数据集，将本方法与 De Soete 方法的实现进行比较（1983，Psychometrika 48：621-626）；它比 De Soete 的方法慢，但在寻找最小二乘树方面更有效。还讨论了该方法与邻居连接方法的关系。
A computational method is presented for minimizing the weighted sum of squares of the differences between observed and expected pairwise distances between species, where the expectations are generated by an additive tree model. The criteria of Pitch and Margoliash (1967, Science 155:279-284) and Cavalli-Sforza and Edwards (1967, Evolution 21:550-570) are both weighted least squares, with different weights. The method presented iterates lengths of adjacent branches in the tree three at a time. The weighted sum of squares never increases during the process of iteration, and the iterates approach a stationary point on the surface of the sum of squares. This iterative approach makes it particularly easy to maintain the constraint that branch lengths never become negative, although negative branch lengths can also be allowed. The method is implemented in a computer program, FITCH, which has been distributed since 1982 as part of the PHYLIP package of programs for inferring phylogenies, and is also implemented in PAUP*. The present method is compared, using some simulated data sets, with an implementation of the method of De Soete (1983, Psychometrika 48:621-626); it is slower than De Soete's method but more effective at finding the least squares tree. The relationship of this method to the neighbor-joining method is also discussed.