在 facet_wrap (gepolt) 之后使用“整体”组

Question

我想在我的 ggplot 中添加一个栏（有意义）。 我知道添加条的代码（stat_pvalue_manual（）），但我的问题更普遍。 是否可以在 facet_wrap 之后使用“整体”组？

我的代码如下：

library(data.table)
library(ggplot2)
library(dplyr)
data(mtcars)
data <-mtcars[,c(1,2)]
data <- data[c(1:30),]
setDT(data, keep.rownames = TRUE)[]
data <- as.data.frame(data[,c(1,2)])
data$group <- c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3,3)
data$group2 <- c(1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2)
data$mpg2 <- data$mpg * 0.6345
data$mp3 <- data$mpg * 0.7564
data$group <- as.factor(data$group)
data$group2 <- as.factor(data$group2)


long_data <- melt(setDT(data), id.vars = c("rn", "group", "group2"), variable.name = "Timepoint")

p <- ggplot(long_data, aes(x = Timepoint, y = value, fill = group2)) +
  geom_bar(stat = "summary", fun = "mean", position = "dodge", na.rm = T, alpha=0.35) +
  geom_point(data = long_data %>% filter(group=="1") , aes(x = Timepoint, y = value, colour =  group),  size = 0.9, shape = 16)+
  geom_point(data = long_data %>% filter(group=="2") ,aes(x = Timepoint, y = value, colour =  group),  size = 0.9, shape = 16)+
  geom_point(data = long_data %>% filter(group=="3") ,aes(x = Timepoint, y = value, colour =  group),  size = 0.9, shape = 17)+
  geom_line(data = long_data, aes(x= Timepoint, y = value, group = rn),  alpha = .3, size = 0.4) +
  facet_wrap(~group2)



p

我想“使用”这两个组并在第 1 组和第 2 组之间添加一个栏（由 facet_wrap 分隔）。 我附上了一张 plot 给我的图片，并手动绘制了我想要的红色。

Answer 1

解决这个问题的一种方法是使用patchwork将两个图重叠在一起。 一个 plot 必须只有一个geom_signif层，另一个是您现有的 plot：

library(ggpubr)
library(patchwork)

p1 <- ggplot(long_data, aes(x = Timepoint, y = value, colour = group)) +
  geom_bar(aes(fill = group2), color = NA, stat = "summary", fun = "mean", 
           position = "dodge", na.rm = TRUE, alpha = 0.35) +
  geom_point(data = filter(long_data, group == "1"), size = 0.9, shape = 16) +
  geom_point(data = filter(long_data, group == "2"), size = 0.9, shape = 16) +
  geom_point(data = filter(long_data, group == "3"), size = 0.9, shape = 17) +
  geom_line(data = long_data, aes(group = rn), color = 'black',
            alpha = 0.3, size = 0.4) +
  facet_wrap(~group2) +
  ylim(c(0, 40))

p2 <- ggplot(long_data, aes(group2, value)) +
  geom_bar(stat = 'summary', fun = 'mean', fill = NA) +
  geom_signif(comparisons = list(c('1', '2')), test = 't.test',
              map_signif_level = function(p) sprintf("p = %.2g", p),
              extend_line = 0.025, y_position = 37, vjust = -0.2) +
  ylim(c(0, 40)) +
  theme_void()

现在我们绘制p1并将p2直接放在它上面：

layout <- c(
  area(t = 1, l = 1, b = 2, r = 2),
  area(t = 1, l = 1, b = 2, r = 2)
)

p1 + p2 + plot_layout(design = layout) 

Answer 2

作为重要性条的替代方案，也许在两个方面为整体组均值添加条会更容易且同样清晰，例如geom_crossbar(aes(group = group2), color = "black") 。 然后误差条的重叠可以表明面板之间差异的大小。