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Power of eight tree shape statistics to detect nonrandom diversification: A comparison by simulation of two models of cladogenesis

机译:八棵树形状统计数据检测非随机多样性的能力:通过模拟两个成枝模型的比较

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We used simulations to compare the relative power of eight statistical tests to detect imbalance in phylogenies that is too great to be ascribed to an equal-rates Markov null model. Three of these tests have never had their power assessed before. Our simulations are the first to assess performance under scenarios in which the speciation rates of various lineages can evolve independently. In one of the scenarios explored, rates depend upon the value of an evolving trait, whereas in the other the probability that a species will speciate declines with the time since it last did so. The results indicate that the relative performance of the methods depends upon how the imbalance is generated. Different types of processes lead to different imbalance signatures, i.e., different patterns of imbalance at different depths in the phylogeny, and the measures of tree shape differ in the depth of phylogeny at which they are most sensitive. Relative performance is also affected by tree size but does not appear to depend greatly upon the degree of speciation rate variation among lineages. Two of the indices (Colless's index I-c and Shao and Sokal's (N) over bar) show reasonable performance throughout, but another (Shao and Sokal's B-2) is never indicated to be a preferred method. Two tests that do not require completely resolved phylogenies, mean I' and mean I-10', have reasonable power.
机译:我们使用模拟来比较八项统计测试的相对功效,以检测系统发育不平衡的严重性,而这种不平衡太大无法归因于等价的马尔可夫零模型。这些测试中的三个以前从未进行过功率评估。我们的仿真是第一个在各种谱系的物种形成率可以独立发展的情况下评估性能的仿真程序。在所研究的一种情况下,速率取决于进化特征的价值,而在另一种情况下,物种自上次出现以来随时间下降的概率下降。结果表明,这些方法的相对性能取决于不平衡的产生方式。不同类型的过程导致不同的失衡特征,即在系统发育的不同深度处的失衡模式不同,并且树形的度量在它们最敏感的系统发育深度上也不同。相对性能也受树大小的影响,但似乎并不太依赖于谱系间物种形成率变化的程度。两项指数(Colless的指数I-c和Shao和Sokal的(N)超过小节)在整个过程中都显示出合理的表现,但从未有人指出另一种指数(Shao和Sokal的B-2)是首选方法。不需要完全解析的系统发育的两个测试(均值I'和均值I-10')具有合理的功效。

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