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标签:: PERMANOVA

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在R中正确运行PERMANOVA and pairwise comparison及注意事项

(本文于 2016-10-16 14:15 首发于 “科学网”) PERMANOVA and pairwise comparison——样品组间差异显著性分析及事后两两比较。 (R软件结果与PRIMER 7及 PAST v3软件结果一致!!!) PERMANOVA - permutational ANOVA/MANOVA Analyses univariate or multivariate data in response to factors, groups or treatments in an experimental design. PERMANOVA can be used as a better ANOVA/MANOVA. Whereas ANOVA/MANOVA assumes normal distributions and, implicitly, Euclidean distance, PERMANOVA works with any distance measure that is appropriate to the data, and uses permutations to make it distribution free. It carries this generalisation through to include most of the options you would expect from modern ANOVA/MANOVA implementation. For example, new theoretical work allows the handling of complex unbalanced designs, also including covariables. PERMANOVA与ANOSIM(Analysis of similarities)等方法目的类似,即比较样品组间的差异显著性。例:对多组数据进行聚类分析后得到3个大类,但是想知道这3个大类之间的差异是否显著,即可用上述方法。 ANOSIM比较的是组内或组间距离的平均值;对于样本量大小变化很敏感,适用于样本在欧式平面(Euclidean space)中单个数据变化有重要意义的情况;另,ANOSIM对异质性数据(方差不齐)很敏感,方差不等的情况不宜使用。 PERMANOVA比ANOSIM更强大,比较的是各组重心之间的差异;对样本数N以及方差的齐次性要求不高,推荐使用。 以上论述依据推荐参考:Anderson M,Walsh D.(2013) PERMANOVA, ANOSIM and the Mante test in the faceof heterogeneous dispersions: What null hypothesis are you testing?. Ecological Monographs,83(4):557-574. Step1:数据填写方式如下图,及导入到R 其中, dune.fish.csv为6种鱼的某一指标(如体长SL/cm)的数据; dune.fish.env32grp.csv为6种鱼对应的3个分组,分组可以依据实际需要进行分类或者按照聚类结果(如对dune.fish.csv基于UPGMA算法进行聚类)进行分类。 1234dune.fish<-read.csv("~/dune.fish.csv")View(dune.fish)dune.fish.env32grp<- read.csv("~/dune.fish.env32grp.csv")View(dune.fish.env32grp)