Phylogenetic ANOVA: Group-clade aggregation, biological challenges, and a refined permutation procedure
Phylogenetic ANOVA: Group-clade aggregation, biological challenges, and a refined permutation procedure
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DOI：
10.1111/evo.13492
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发表时间：
2018-06-01
期刊：
影响因子：
3.3
通讯作者：
Collyer, Michael L.
中科院分区：
文献类型：
--
作者：
Adams, Dean C.;Collyer, Michael L.
系统发育回归经常用于宏观进化研究，其统计特性已被彻底研究。相比之下，系统发育方差分析得到了相对较少的关注，并导致不正确的统计和生物学推断的条件下，比较多变量表型组之间仍然未充分探索。在这里，我们提出了一种改进的方法，随机化残差的排列程序（RRPP），用于评估组间的表型差异，同时调节数据的同源性。我们表明，RRPP显示适当的统计属性系统发育方差分析和回归模型，以及单变量和多变量数据集。对于方差分析，我们发现RRPP表现出更高的统计功率比利用系统发育模拟的方法。此外，我们研究了群体分散在遗传学中如何影响推断，并揭示了高度聚集的群体与遗传学产生强烈而显著的相关性，这降低了统计能力，并随后影响生物学解释。我们讨论了更广泛的影响，这种系统发育组聚合，其关系到遇到的挑战与其他比较方法，在离散性状的一个或几个过渡上观察到的同源性。最后，我们建议连续性状数据的系统发育比较研究使用RRPP来评估性状变异来源的指示变量的重要性。
Phylogenetic regression is frequently used in macroevolutionary studies, and its statistical properties have been thoroughly investigated. By contrast, phylogenetic ANOVA has received relatively less attention, and the conditions leading to incorrect statistical and biological inferences when comparing multivariate phenotypes among groups remain underexplored. Here, we propose a refined method of randomizing residuals in a permutation procedure (RRPP) for evaluating phenotypic differences among groups while conditioning the data on the phylogeny. We show that RRPP displays appropriate statistical properties for both phylogenetic ANOVA and regression models, and for univariate and multivariate datasets. For ANOVA, we find that RRPP exhibits higher statistical power than methods utilizing phylogenetic simulation. Additionally, we investigate how group dispersion across the phylogeny affects inferences, and reveal that highly aggregated groups generate strong and significant correlations with the phylogeny, which reduce statistical power and subsequently affect biological interpretations. We discuss the broader implications of this phylogenetic group aggregation, and its relation to challenges encountered with other comparative methods where one or a few transitions in discrete traits are observed on the phylogeny. Finally, we recommend that phylogenetic comparative studies of continuous trait data use RRPP for assessing the significance of indicator variables as sources of trait variation.