Phylogenetic Analysis of Characters with Dependencies under Maximum Likelihood

IF 5.7 1区 生物学 Q1 EVOLUTIONARY BIOLOGY
Pablo A Goloboff
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引用次数: 0

Abstract

The dependencies between characters used in phylogenetic analysis (e.g., inapplicabilities, functional dependencies) can be taken into account by using combinations of character states as possible ancestral morphotypes, and using appropriate rates of transformation between such morphotypes. As every morphotype represents a permissible combination of the original character states, this allows easily ruling out specific combinations of character states, and taking into account changes that are either less or more likely to co-occur, or to occur in certain contexts. For inapplicable characters, Goloboff et al. (2021) used morphotypes but proposed obtaining transition probabilities between morphotypes from products of transition probabilities of the original characters and factors to incorporate dependencies. The product of transition probabilities is shown here to be flawed (failing the time-continuity requirement of phylogenetic Markov models, essential for statistical consistency under the model). Tarasov (2023) used the same delimitation of morphotypes but proposed obtaining transition probabilities from rate matrices, synthesized in a stepwise fashion from the hierarchy of dependencies. This paper shows that the rate matrices can easily be created, instead of with a stepwise synthesis, from direct comparisons between legitimate morphotypes (as done by Goloboff and De Laet 2023 for parsimony). Based on a few simple rules, the resulting rate matrices are (for inapplicable characters) identical to those obtained by Tarasov (2023). Additionally, in the computer program TNT, biological dependencies beyond mere inapplicability can be specified by the user with a simple syntax for (combinations of) states in “parent” characters restricting the states that “child” characters can take, using AND and OR conjunctions for elaborate interactions. These researcher-defined rules are used to internally convert the original characters into morphotypes, discarding morphotypes made impossible by the rules. In the case of biological dependencies (where, depending on the parent characters, there can be restrictions in the states that dependent characters can take, instead of the character being inapplicable), the rates of transition between morphotypes cannot be calculated solely from comparisons of states differing in both morphotypes –consideration of the conditions of dependency is needed as well.
极大似然下具有依赖性性状的系统发育分析
系统发育分析中使用的性状之间的依赖性(例如,不适用性,功能依赖性)可以通过使用性状状态组合作为可能的祖先形态,并在这些形态之间使用适当的转换速率来考虑。由于每种形态都代表了原始角色状态的一种可允许的组合,这就可以很容易地排除角色状态的特定组合,并考虑到更少或更有可能同时发生的变化,或者在特定环境中发生的变化。对于不适用的字符,Goloboff等人(2021)使用形态型,但提出从原始字符的转移概率和因素的乘积中获得形态型之间的转移概率,以纳入依赖关系。转移概率的乘积在这里是有缺陷的(不符合系统发育马尔可夫模型的时间连续性要求,这对模型下的统计一致性至关重要)。Tarasov(2023)使用了相同的形态划分,但提出了从速率矩阵中获得转移概率的建议,并从依赖关系的层次结构中逐步合成。本文表明,速率矩阵可以很容易地创建,而不是通过逐步合成,从合法形态之间的直接比较(如Goloboff和De Laet 2023所做的那样)。基于一些简单的规则,得到的速率矩阵(对于不适用的字符)与Tarasov(2023)得到的相同。此外,在计算机程序TNT中,用户可以使用“父”字符状态的简单语法(组合)来指定生物依赖性,限制“子”字符可以采取的状态,使用AND和OR连词进行复杂的交互。这些研究人员定义的规则用于在内部将原始字符转换为形态,丢弃因规则而无法实现的形态。在生物依赖的情况下(根据亲本性状,依赖性状可以采取的状态可能有限制,而不是性状不适用),形态之间的转换速率不能仅仅通过比较两种形态不同的状态来计算——也需要考虑依赖条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Systematic Biology
Systematic Biology 生物-进化生物学
CiteScore
13.00
自引率
7.70%
发文量
70
审稿时长
6-12 weeks
期刊介绍: Systematic Biology is the bimonthly journal of the Society of Systematic Biologists. Papers for the journal are original contributions to the theory, principles, and methods of systematics as well as phylogeny, evolution, morphology, biogeography, paleontology, genetics, and the classification of all living things. A Points of View section offers a forum for discussion, while book reviews and announcements of general interest are also featured.
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