adonis文档：
https://www.rdocumentation.org/packages/vegan/versions/2.4-2/topics/adonis

vegdist文档：
https://www.rdocumentation.org/packages/vegan/versions/2.4-2/topics/vegdist

依赖包

library("vegan")

1 输入数据

多样本变量矩阵

data=data.frame(matrix(rnorm(100, 100, 10), 10, 10))
rownames(data)=paste("sample", 1:10, sep="_")
colnames(data)=paste("var", 1:10, sep="_")

表型数据

env = data.frame(sample = paste("sample", 1:10, sep="_"), 
                            group = c(rep("A", 5), rep("B", 5)))

2 permannova：表型与矩阵的关联

adonis(data ~ group,  # 矩阵 ~ 表型变量
       data = env,  # 表型表格
       distance = "bray",   # 距离算法
       permutations = 999)  # 排列次数

3 提取p值

# 循环所有算法
algo = c("manhattan", "euclidean", "canberra", "bray", "kulczynski", "jaccard", "gower", "altGower", "morisita", "horn", "mountford", "raup", "binomial", "chao", "cao", "mahalanobis")
p=c()
for(title in algo)
{
    res = adonis(data ~ group, data = env, 
                 distance = title, permutations = 999)
    # 提取P value并保存
    p = c(p, res$aov.tab$Pr[1])
    print(title)
}
perm = data.frame(algo, p)

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带统计学的PCoA完美解决打样本量多组数据不好区分