A Comparative Method for Both Discrete and Continuous Characters Using the Threshold Model
A Comparative Method for Both Discrete and Continuous Characters Using the Threshold Model
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DOI：
10.1086/663681
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发表时间：
2012-02-01
影响因子：
2.9
通讯作者：
Felsenstein, Joseph
中科院分区：
文献类型：
--
作者：
Felsenstein, Joseph
Sewall Wright在1934年提出的阈值模型可以用来模拟两态离散性状沿着演化过程的演化。该模型假定存在一种称为负债的数量特征，这种特征是无法观察到的，并根据负债是否超过阈值来确定离散特征。一个马尔可夫链蒙特卡罗算法是用来推断的进化协方差的负债的离散字符，采样负债值一致的遗传和观察到的数据。同样的方法也可以用于连续字符，假设尖端物种具有已观察到的值。通过这种方式，可以进行结合离散和连续特征的比较方法分析。模拟表明，协方差的负债成功估计，虽然精度可以实现，只有通过使用大量的物种，我们必须始终担心是否协方差和模型适用于整个集团。阈值模型的一个优点是，该模型可以直接扩展到适应物种内的表型变异，并允许与定量遗传学模型的接口。
The threshold model developed by Sewall Wright in 1934 can be used to model the evolution of two-state discrete characters along a phylogeny. The model assumes that there is a quantitative character, called liability, that is unobserved and that determines the discrete character according to whether the liability exceeds a threshold value. A Markov chain Monte Carlo algorithm is used to infer the evolutionary covariances of the liabilities for discrete characters, sampling liability values consistent with the phylogeny and with the observed data. The same approach can also be used for continuous characters by assuming that the tip species have values that have been observed. In this way, one can make a comparative-methods analysis that combines both discrete and continuous characters. Simulations are presented showing that the covariances of the liabilities are successfully estimated, although precision can be achieved only by using a large number of species, and we must always worry whether the covariances and the model apply throughout the group. An advantage of the threshold model is that the model can be straightforwardly extended to accommodate within-species phenotypic variation and allows an interface with quantitative-genetics models.