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https://cran./web/packages/ggsignif/vignettes/intro.html 首先我們用示例數(shù)據(jù)跑一跑 > library(ggplot2)> library(ggsignif)> head(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species1 5.1 3.5 1.4 0.2 setosa2 4.9 3.0 1.4 0.2 setosa3 4.7 3.2 1.3 0.2 setosa4 4.6 3.1 1.5 0.2 setosa5 5.0 3.6 1.4 0.2 setosa6 5.4 3.9 1.7 0.4 setosa> ggplot(iris, aes(x = Species, y = Sepal.Length)) ++ geom_boxplot() ++ geom_signif(+ comparisons = list(c("versicolor", "virginica"))+ )
效果圖如下 
通過comparisons參數(shù)來手動指定需要比較的兩組，就會自動在上面添加p值和連線，默認都在頂部添加，當我么同時指定了多組數(shù)據(jù)的比較時，就會重疊，示例如下 > ggplot(iris, aes(x = Species, y = Sepal.Length)) ++ geom_boxplot() ++ geom_signif(+ comparisons = list(+ c("versicolor", "virginica"),+ c("setosa", "virginica"),+ c("setosa", "versicolor")+ )+ )
效果圖如下
為了避免這個問題，ggsignif還支持直接指定文字注釋的內(nèi)容和橫線的寬高度，代碼如下 > ggplot(iris, aes(x = Species, y = Sepal.Length)) ++ geom_boxplot() ++ geom_signif(+ annotations = c("First", "Second", "Third"),+ y_position = c(8, 8.2, 8.5),+ xmin = c(1, 2, 1),+ xmax = c(2, 3, 3)+ )
效果圖如下 
掌握了基本用法之后，就可以來復現(xiàn)文章中的圖表了，首先是兩組間的差異，代碼如下 > data <- iris[iris$Species %in% c("versicolor", "virginica"), ]> ggplot(data, aes(x = Species, y = Sepal.Length, fill = Species)) ++ geom_boxplot() ++ geom_signif(comparisons = list(c("versicolor", "virginica"))) ++ theme_classic() ++ theme(legend.position = "top")
效果圖如下 
再來復現(xiàn)一個三組比較的，文獻中插入如下所示 
> ggplot(data, aes(x = Species, y = Sepal.Length, fill = Species)) ++ geom_boxplot() ++ geom_signif(comparisons = list(c("versicolor", "virginica"))) ++ theme_classic() ++ theme(legend.position = "top")> ggplot(iris, aes(x = Species, y = Sepal.Length, fill = Species)) ++ geom_boxplot() ++ geom_signif(+ annotations = c("*", "**", "***"),+ y_position = c(8, 8.2, 8.5),+ xmin = c(1, 2, 1),+ xmax = c(2, 3, 3)+ ) ++ theme_classic() ++ theme(legend.position = "top")
效果圖如下 
通過y_position, xmin, xmax參數(shù)來指定p值的位置，通過annotations參數(shù)指定標記的具體信息，提升了靈活性。
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