Pavoine Sandrine, Ollier Sébastien, Pontier Dominique, Chessel Daniel
Laboratoire de Biométrie et Biologie Evolutive, UMR CNRS 5558, Université de Lyon, Université Lyon 1, France.
Theor Popul Biol. 2008 Feb;73(1):79-91. doi: 10.1016/j.tpb.2007.10.001. Epub 2007 Oct 12.
Abouheif adapted a test for serial independence to detect a phylogenetic signal in phenotypic traits. We provide the exact analytic value of this test, revealing that it uses Moran's I statistic with a new matrix of phylogenetic proximities. We introduce then two new matrices of phylogenetic proximities highlighting their mathematical properties: matrix A which is used in Abouheif test and matrix M which is related to A and biodiversity studies. Matrix A unifies the tests developed by Abouheif, Moran and Geary. We discuss the advantages of matrices A and M over three widely used phylogenetic proximity matrices through simulations evaluating power and type-I error of tests for phylogenetic autocorrelation. We conclude that A enhances the power of Moran's test and is useful for unresolved trees. Data sets and routines are freely available in an online package and explained in an online supplementary file.
阿布海夫采用了一种用于序列独立性的检验方法来检测表型性状性状中的系统发育信号。我们给出了该检验的确切分析值，揭示出它使用了带有新的系统发育邻近矩阵的莫兰指数统计量。然后我们引入了两个新的系统发育邻近矩阵，并突出它们的数学性质：用于阿布海夫检验的矩阵A以及与A和生物多样性研究相关的矩阵M。矩阵A统一了由阿布海夫、莫兰和吉尔里开发的检验方法。我们通过评估系统发育自相关检验的功效和I型错误的模拟，讨论了矩阵A和M相较于三种广泛使用的系统发育邻近矩阵的优势。我们得出结论，A增强了莫兰检验的功效，并且对未解决的树状图很有用。数据集和程序在一个在线包中免费提供，并在一个在线补充文件中进行了解释。
