R-使用'stat_compare_means'在ggplot中重新格式化P值 [英] R - reformat P value in ggplot using 'stat_compare_means'

问题描述

我想在多面ggplot中将p值绘制到每个面板.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).

I want to plot the p values to each panel in a faceted ggplot. If the p value is larger than 0.05, I want to display the p value as it is. If the p value is smaller than 0.05, I want to display the value in scientific notation (i.e, 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)

此代码运行无错误，但是数字的格式未更改.我究竟做错了什么?我附加了数据以重现该图:数据在这里

This code runs without error, however, the format of numbers isn't changed. What am I doing wrong? I attached the data to reproduce the plot: 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")

推荐答案

我认为您的问题来自 stat_compare_means 和 comparisons 的使用.我不太确定，但是我会猜测 stat_compare_means 的p值输出与 compare_means 不同，因此，您不能将其用于 aes (标签).

I think your issue came from the stat_compare_means and the use of comparisons. I'm not totally sure, but I will guess that the output of p value for stat_compare_means is different from compare_means and so, you can't use it for the aes of label.

让我用您的示例解释一下，您可以像这样修改p.value的显示:

Let me explain, with your example, you can modify the display of the p.value like this:

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..)))

您可以正确显示p.value，但丢失了条形图.因此，如果您使用 comparisons 参数，则会得到:

You get the correct display of p.value but you lost your bars. So, if you use comparisons argument, you get:

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..)))

因此，现在您得到的是条形，但显示不正确.

So, now, you get bars but not the correct display.

要规避此问题，您可以使用 compare_means 函数在ggplot2之外执行统计，并使用软件包 ggsignif 来显示正确的显示.

To circumwent this issue, you can perform the statistics outside of ggplot2 using compare_means functions and use the package ggsignif to display the correct display.

在这里，我正在使用 dplyr 和函数 mutate 创建新列，但是您可以在 base R中轻松地做到这一点.

Here, I'm using dplyr and the function mutate to create new columns, but you can do it easily in base R.

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，您可以绘制它:

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)

它看起来像您要绘制的内容吗?

Does it look what you are trying to plot ?

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