On the Mkv Model with Among-Character Rate Variation

变化(天文学) 变量(数学) 系统发育树 性格(数学) 现存分类群 生物 系统发育学 最大似然 系统发育比较方法 树(集合论) 统计 人工智能 进化生物学 计算机科学 数学 几何学 物理 数学分析 基因 生物化学 天体物理学
作者
Alessio Capobianco,Sebastian Höhna
出处
期刊:Systematic Biology [Oxford University Press]
被引量:4
标识
DOI:10.1093/sysbio/syaf038
摘要

Abstract Models used in likelihood-based morphological phylogenetics often adapt molecular phylogenetics models to the specificities of morphological data. Such is the case for the widely used Mkv model—which introduces an acquisition bias correction for sampling only characters that are observed to be variable—and for models of among-character rate variation (ACRV), routinely applied by researchers to relax the equal-rates assumption of Mkv. However, the interaction between variable character acquisition bias and ACRV has never been explored before. We demonstrate that there are two distinct approaches to condition the likelihood on variable characters when there is ACRV, and we call them joint and marginal acquisition bias. Far from being just a trivial mathematical detail, we show that the way in which the variable character conditional likelihood is calculated results in different assumptions about how rate variation is distributed in morphological data sets. Simulations demonstrate that tree length and amount of ACRV in the data are systematically biased when conditioning on variable characters differently from how the data were simulated. Moreover, an empirical case study with extant and extinct taxa reveals a potential impact not only on the estimation of branch lengths, but also of phylogenetic relationships. We recommend the use of the marginal acquisition bias approach for morphological data sets modeled with ACRV. Finally, we urge developers of phylogenetic software to clarify which acquisition bias correction is implemented for both estimation and simulation, and we discuss the implications of our findings on modeling variable characters for the future of morphological phylogenetics.
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