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On the Statistical Interpretation of Site-Specific Variables in Phylogeny-Based Substitution Models

机译:基于系统发育的替代模型中特定于站点的变量的统计解释

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摘要

Phylogeny-based modeling of heterogeneity across the positions of multiple-sequence alignments has generally been approached from two main perspectives. The first treats site specificities as random variables drawn from a statistical law, and the likelihood function takes the form of an integral over this law. The second assigns distinct variables to each position, and, in a maximum-likelihood context, adjusts these variables, along with global parameters, to optimize a joint likelihood function. Here, it is emphasized that while the first approach directly enjoys the statistical guaranties of traditional likelihood theory, the latter does not, and should be approached with particular caution when the site-specific variables are high dimensional. Using a phylogeny-based mutation-selection framework, it is shown that the difference in interpretation of site-specific variables explains the incongruities in recent studies regarding distributions of selection coefficients.
机译:通常已经从两个主要角度研究了基于系统发育的跨多序列比对位置的异质性建模。前者将位点特异性视为从统计定律得出的随机变量,似然函数采用对该定律的积分形式。第二种方法为每个位置分配不同的变量,并在最大似然上下文中调整这些变量以及全局参数,以优化联合似然函数。这里要强调的是,尽管第一种方法直接享有传统似然理论的统计保证,但后者却没有,当特定于站点的变量是高维时,应格外谨慎。使用基于系统发生学的突变选择框架,表明位点特异性变量解释的差异解释了最近关于选择系数分布的研究的不一致性。

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