R - 使用 'stat_compare_means' 在 ggplot 中重新格式化 P 值

Question

我想将 p 值绘制到多面 ggplot 中的每个面板。如果 p 值大于 0.05，我想按原样显示 p 值。如果 p 值小于 0.05，我想以科学计数法显示该值（即 0.0032 -> 3.20e-3；0.0000425 -> 4.25e-5）。

我为此编写的代码是：

   p1 <- ggplot(data = CD3, aes(location, value, color = factor(location),
                             fill = factor(location))) + 
  theme_bw(base_rect_size = 1) +
  geom_boxplot(alpha = 0.3, size = 1.5, show.legend = FALSE) +
  geom_jitter(width = 0.2, size = 2, show.legend = FALSE) +
  scale_color_manual(values=c("#4cdee6", "#e47267", "#13ec87")) +
  scale_fill_manual(values=c("#4cdee6", "#e47267", "#13ec87")) +
  ylab(expression(paste("Density of clusters, ", mm^{-2}))) +
  xlab(NULL) +
  stat_compare_means(comparisons = list(c("CT", 'N'), c("IF","N")), 
                     aes(label = ifelse(..p.format.. < 0.05, formatC(..p.format.., format = "e", digits = 2),
                                        ..p.format..)), 
                     method = 'wilcox.test', show.legend = FALSE, size = 10) +
  #ylab(expression(paste('Density, /', mm^2, )))+
  theme(axis.text = element_text(size = 10), 
        axis.title = element_text(size = 20), 
        legend.text = element_text(size = 38), 
        legend.title = element_text(size = 40), 
        strip.background = element_rect(colour="black", fill="white", size = 2),
        strip.text = element_text(margin = margin(10, 10, 10, 10), size = 40),
        panel.grid = element_line(size = 1.5))
plot(p1)

这段代码运行没有错误，但是，数字的格式没有改变。我究竟做错了什么？我附上了重现情节的数据：donwload data here

编辑

structure(list(value = c(0.931966449207829, 3.24210526315789, 
3.88811650210901, 0.626860993574675, 4.62085308056872, 0.477508650519031, 
0.111900110501359, 3.2495164410058, 4.06626506024096, 0.21684918139434, 
1.10365086026018, 4.66666666666667, 0.174109967855698, 0.597625869832174, 
2.3758865248227, 0.360751947840548, 1.00441501103753, 3.65168539325843
), Criteria = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Density", "Density of cluster", 
"nodular count", "Elongated count"), class = "factor"), Case = structure(c(1L, 
1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 
6L), .Label = c("Case 1A", "Case 1B", "Case 2", "Case 3", "Case 4", 
"Case 5"), class = "factor"), Mark = structure(c(1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("CD3", 
"CD4", "CD8", "CD20", "FoxP3"), class = "factor"), location = structure(c(3L, 
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 
2L), .Label = c("CT", "IF", "N"), class = "factor")), row.names = c(91L, 
92L, 93L, 106L, 107L, 108L, 121L, 122L, 123L, 136L, 137L, 138L, 
151L, 152L, 153L, 166L, 167L, 168L), class = "data.frame")

Answer 1

我认为您的问题来自 stat_compare_means 和 comparisons 的使用。我不太确定，但我猜想 stat_compare_means 的 p 值输出与 compare_means 不同，因此，您不能将它用于 aes 的 [=] 19=].

让我解释一下，用你的例子，你可以像这样修改p.value的显示：

library(ggplot2)
library(ggpubr)
ggplot(df, aes(x = location, y = value, color = location))+
  geom_boxplot()+
  stat_compare_means(ref.group = "N", aes(label = ifelse(p < 0.05,sprintf("p = %2.1e", as.numeric(..p.format..)), ..p.format..)))

您得到 p.value 的正确显示，但您失去了酒吧。所以，如果你使用 comparisons 参数，你会得到：

library(ggplot2)
library(ggpubr)
ggplot(df, aes(x = location, y = value, color = location))+
    geom_boxplot()+
    stat_compare_means(comparisons = list(c("CT","N"), c("IF","N")), aes(label = ifelse(p < 0.05,sprintf("p = %2.1e", as.numeric(..p.format..)), ..p.format..)))

所以，现在，您得到了条形图，但显示不正确。

为了避免这个问题，您可以使用 compare_means 函数在 ggplot2 之外执行统计，并使用包 ggsignif 来显示正确的显示。

在这里，我使用 dplyr 和函数 mutate 来创建新列，但您可以在 base R 中轻松完成。

library(dplyr)
library(magrittr)
c <- compare_means(value~location, data = df, ref.group = "N")
c %<>% mutate(y_pos = c(5,5.5), labels = ifelse(p < 0.05, sprintf("%2.1e",p),p))

# A tibble: 2 x 10
  .y.   group1 group2       p p.adj p.format p.signif method   y_pos labels 
  <chr> <chr>  <chr>    <dbl> <dbl> <chr>    <chr>    <chr>    <dbl> <chr>  
1 value N      CT     0.00866 0.017 0.0087   **       Wilcoxon   5   8.7e-03
2 value N      IF     0.00866 0.017 0.0087   **       Wilcoxon   5.5 8.7e-03

然后，你可以绘制它：

library(ggplot2)
library(ggpubr)
library(ggsignif)
ggplot(df, aes(x = location, y = value))+
  geom_boxplot(aes(colour = location))+
  ylim(0,6)+
  geom_signif(data = as.data.frame(c), aes(xmin=group1, xmax=group2, annotations=labels, y_position=y_pos),
                manual = TRUE)

它看起来像你想要绘制的东西吗？

R - 使用 'stat_compare_means' 在 ggplot 中重新格式化 P 值

R - reformat P value in ggplot using 'stat_compare_means'

r

ggplot2

ggpubr