trans_beta class：利用trans_beta類可以變換和繪制beta分集的距離矩陣。該類中涉及到beta多樣性的分析主要包括排序、群距、聚類和方差分析。我們首先使用PCoA顯示排序。

> dataset$cal_betadiv()
The result is stored in object$beta_diversity ...
> t1 <- trans_beta$new(dataset = dataset, group = "Group", measure = "bray")
> t1$cal_ordination(ordination = "PCoA")
The ordination result is stored in object$res_ordination ...
> tmp <- t1$res_ordination$scores
> t2 <- trans_env$new(dataset = dataset, add_data = tmp[, 1:2])
Env data is stored in object$data_env ...
> t2$cal_diff(group = "Group", method = "anova")
The result is stored in object$res_diff ...
Warning message:
程輯包‘agricolae’是用R版本4.3.3 來建造的  #這里需要安裝agricolae包，直接install就行。
> t2
trans_env object:
Env table have 2 variables: PCo1,PCo2

> p1 <- t1$plot_ordination(plot_color = "Group", plot_shape = "Group", plot_type = c("point", "ellipse"))

#然后我們繪制并比較群距。
> t1$cal_group_distance()
> t1$plot_group_distance(distance_pair_stat = TRUE)

#這里應該會有差異比較的，但是卻沒有。示例如下，不知道有什么問題，等到有需求我會解決這個問題。

#計算和繪制組之間的樣本距離
> t1$cal_group_distance(within_group = FALSE)
> t1$plot_group_distance(distance_pair_stat = TRUE)

# 聚類圖也是一種常用的方法。
> t1$plot_clustering(group = "Group", replace_name = c("Saline", "Type"))

#perMANOVA常用于組間距離的差異檢驗。

> t1$cal_manova(cal_manova_all = TRUE)
The result is stored in object$res_manova ...
> t1$res_manova
Permutation test for adonis under reduced model
Terms added sequentially (first to last)
Permutation: free
Number of permutations: 999adonis2(formula = use_formula, data = metadata, cal_manova_all = TRUE)Df SumOfSqs      R2      F Pr(>F)    
Group     2   6.1207 0.19553 10.573  0.001 ***
Residual 87  25.1822 0.80447                  
Total    89  31.3029 1.00000                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

## manova表示每一對組

> t1$cal_manova(cal_manova_paired = TRUE)
The result is stored in object$res_manova ...
> t1$res_manova
Permutation test for adonis under reduced model
Terms added sequentially (first to last)
Permutation: free
Number of permutations: 999adonis2(formula = use_formula, data = metadata, cal_manova_paired = TRUE)Df SumOfSqs      R2      F Pr(>F)    
Group     2   6.1207 0.19553 10.573  0.001 ***
Residual 87  25.1822 0.80447                  
Total    89  31.3029 1.00000                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

# manova用于指定組集:這里是“group + Type”
> t1$cal_manova(cal_manova_set = "Group + Type")
The result is stored in object$res_manova ...
> t1$res_manova
Permutation test for adonis under reduced model
Terms added sequentially (first to last)
Permutation: free
Number of permutations: 999adonis2(formula = use_formula, data = metadata, cal_manova_set = "Group + Type")Df SumOfSqs      R2      F Pr(>F)    
Group     2   6.1207 0.19553 10.573  0.001 ***
Residual 87  25.1822 0.80447                  
Total    89  31.3029 1.00000                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

這個包的改動有些大，以前的代碼不能直接跑了。我發(fā)覺，學習這個包還是要基于需求啊，否則會很快忘掉。以前我使用vegan包分析+ggplot2包做PCOA分析，等把這個包分享完了，我會再分享其它的R語言。