r - ggplot2:将 p 值添加到分组箱线图

Question

我正在尝试使用“stat_signif”函数将 p_values 添加到我的图表中。
问题是我的箱线图是分组箱线图，我想在其中比较同一类别的每 2 个箱线图，而 stat_signif 函数需要 x 轴值进行比较。
这是我的代码:

p <- ggplot(plot.data, aes(x = Element, y = Value, fill = Group)) + #Define the elements for plotting - group by "strandness".
geom_boxplot(outlier.shape = NA, colour = "black") +
scale_fill_manual(values = c("goldenrod","darkgreen")) +
coord_cartesian(ylim = c(0, 0.03)) +
stat_summary(fun.y=mean, colour="black", geom ="point", shape=18, size=4 ,show.legend = FALSE, position = position_dodge(0.75)) +
theme(legend.title=element_blank(),legend.text = element_text(size=16), axis.text.x = element_text(color = "black", size = 12), axis.text.y = element_text(color = "black", size = 12),
      panel.background = element_blank(),
      panel.grid.major = element_blank(), 
      panel.grid.minor = element_blank(),
      axis.line = element_line(colour = "black"),
      panel.border = element_rect(colour = "black", fill=NA, size=0.5),
      legend.key = element_rect(colour = "transparent", fill = "white")) +
theme(plot.title = element_text(lineheight=.8, hjust = 0.5, size = 20),axis.title.y = element_text(size = 20, angle = 90, margin = margin(t = 0, r = 20, b = 0, l = 0))) +
labs(x = "", y = paste0(dinuc, " frequency")) +
theme(plot.margin = unit(c(2,1,1,1), "cm")) +
#stat_compare_means(aes(group = group))
stat_signif(comparisons = list(c("Genes", "mRNA"))
            ,test = "wilcox.test", test.args = list(paired = FALSE, exact = FALSE, correct = FALSE,
                                                    map_signif_level = T), y_position = 0.02) 

plot.data 数据框的样子:

  Group, Value, Element
1 Transcribed, 0.004814926, Genes
2 Non-transcribed, 0.008926, Genes
3 Transcribed, 0.086000026, mRNA
4 Non-transcribed, 0.00548, mRNA
5 Transcribed, 0.258400078, Exons
6 Non-transcribed, 0.23008457, Exons
7 Transcribed, 0.00005687, Introns
8 Non-transcribed, 0.890000521, Introns

等(对于每个元素，大约有 10000 行)

这是代码得到的图: 当我真的想比较每个元素的转录和非转录箱形图时。

Answer 1

您没有发布足够的数据来获取 p 值，所以我发布了一个示例，您可以根据自己的数据集进行调整:

library(tidyverse)
library(ggpubr)

mtcars %>%
  mutate_at(vars(am, cyl), as.factor) %>%
  ggplot(aes(cyl, disp, fill=am))+
  geom_boxplot()+
  stat_compare_means(aes(group = am))

如果您只想在绘图中包含 p 值，则可以使用stat_compare_means(aes(group = am), label = "p.format")。