ASSESSING PHENOTYPIC CORRELATION THROUGH THE MULTIVARIATE PHYLOGENETIC LATENT LIABILITY MODEL
ASSESSING PHENOTYPIC CORRELATION THROUGH THE MULTIVARIATE PHYLOGENETIC LATENT LIABILITY MODEL
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DOI：
10.1214/15-aoas821
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发表时间：
2015-06-01
影响因子：
1.8
通讯作者：
Suchard, Marc A.
中科院分区：
文献类型：
--
作者：
Cybis, Gabriela B.;Sinsheimer, Janet S.;Suchard, Marc A.
了解哪些表型性状在整个进化过程中是一致相关的，这是现代进化生物学中一个高度相关的问题。在这里，我们提出了一个多变量的系统发育潜在责任模型，用于评估多种类型数据之间的相关性，同时控制它们通过分子序列了解的未知的共同进化历史。潜在公式使我们能够在一个模型中考虑连续性状、离散二元性状和具有多个有序和无序状态的离散性状的组合。以前的方法通常只考虑固定历史的单一数据类型，排除了对性状之间相关性的估计，并忽略了历史中的不确定性。我们在贝叶斯系统发育框架中实现了我们的模型，并讨论了用于假设检验的推理技术。最后，我们通过在柱花草的形态、沙门氏菌的抗生素耐药性和流感的表位进化方面的应用展示了该方法。
Understanding which phenotypic traits are consistently correlated throughout evolution is a highly pertinent problem in modern evolutionary biology. Here, we propose a multivariate phylogenetic latent liability model for assessing the correlation between multiple types of data, while simultaneously controlling for their unknown shared evolutionary history informed through molecular sequences. The latent formulation enables us to consider in a single model combinations of continuous traits, discrete binary traits and discrete traits with multiple ordered and unordered states. Previous approaches have entertained a single data type generally along a fixed history, precluding estimation of correlation between traits and ignoring uncertainty in the history. We implement our model in a Bayesian phylogenetic framework, and discuss inference techniques for hypothesis testing. Finally, we showcase the method through applications to columbine flower morphology, antibiotic resistance in Salmonella and epitope evolution in influenza.