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Accepted
zhang
Asked: 2023-12-23 16:20:40 +0800 CST

如何根据R中ggplot2中的离散y轴标签更改面板的背景颜色？

  • 772

我有一个用plot_dfR 命名的数据框，其结构如下：

# Import the library
library(ggplot2)

# Create a sample data
set.seed(123)
plot_df <- data.frame(gene = rep(paste0("ENSG", 1:10, ".17"), each = 2),
                      mean = rnorm(20, 0.5, 0.1),
                      sd = rnorm(20, 0.02, 0.01),
                      group = rep(c("group_a", "group_b"), 10))

我正在尝试创建一个带有点和误差线的 ggplot，其中 y 轴代表基因名称（作为离散标签），x 轴代表平均值，颜色代表组（“group_a”或“组_b”）。这是我正在使用的代码：

ggplot(plot_df, aes(y=gene)) + 
    geom_point(aes(x=mean, color = group), position = position_dodge(width=0.9)) + 
    geom_errorbar(aes(xmin=mean-sd, xmax=mean+sd, color = group), width=.2,
                 position=position_dodge(.9)) + 
    geom_vline(aes(xintercept=0.5), linetype=2, color = 'gray') + 
    theme_bw() + 
    theme(panel.background = element_blank(),
          panel.grid.major = element_blank(), 
          panel.grid.minor = element_blank())

在此输入图像描述

但是，我想根据 y 轴上的基因名称更改面板的背景颜色（每个基因具有不同的颜色或相邻基因没有相同的颜色）。由于我的 y 轴标签是离散的，我不确定如何实现这一点。任何帮助，将不胜感激。谢谢！

我努力了：

在R中的ggplot2中更改白天和晚上的背景颜色

2 个回答

  1. Best Answer

    这是一个使用的解决方案geom_tile()，

    1. 我们为背景颜色创建一个数据框
    2. 当我们使用时，geom_tile()我们将设置x美观性以覆盖绘图的整个宽度并相应地调整每个图块的宽度。
    3. geom_tile()用于x = sum(x_limits) / 2将图块定位在地块的中心并width = diff(x_limits)确保每个图块跨越地块的整个宽度
    
library(ggplot2)
library(dplyr)

set.seed(123)
plot_df <- data.frame(
  gene = rep(paste0("ENSG", 1:10, ".17"), each = 2),
  mean = rnorm(20, 0.5, 0.1),
  sd = rnorm(20, 0.02, 0.01),
  group = rep(c("group_a", "group_b"), 10)
)

# df for background colors
bg_df <- plot_df %>%
  distinct(gene) %>%
  arrange(gene) %>% 
  mutate(color = ifelse(row_number() %% 2 == 1, "gold", "lightgrey"))

# x axis limts based on data 
x_limits <- range(plot_df$mean - plot_df$sd, plot_df$mean + plot_df$sd, na.rm = TRUE)

# the plot
ggplot(plot_df, aes(y = gene, x = mean)) +
  geom_tile(data = bg_df, aes(y = gene, x = sum(x_limits) / 2, width = diff(x_limits), fill = color), 
            alpha = 0.3, inherit.aes = FALSE) +
  geom_point(aes(color = group), position = position_dodge(width = 0.9)) +
  geom_errorbar(aes(xmin = mean - sd, xmax = mean + sd, color = group), 
                width = 0.2, position = position_dodge(.9)) +
  scale_color_manual(values = c("steelblue3", "red3"))+
  geom_vline(xintercept = 0.5, linetype = 2, color = 'gray80') +
  theme_bw() +
  theme(panel.background = element_blank(),
        panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        legend.position = "right") +
  scale_fill_identity()

    在此输入图像描述

    • 4

  2. 另一种选择是geom_rect通过将离散genes 转换为数字并添加-/+.5for来使用 a ymin/ymax。另外，通过设置xmin/max允许-/+Inf填充整个面板，我还将 y 比例的扩展减少到.5。另请注意，我添加了作为scale_y_discrete第一层以强制离散比例。

    library(ggplot2)
library(dplyr)

set.seed(123)
plot_df <- data.frame(
  gene = rep(paste0("ENSG", 1:10, ".17"), each = 2),
  mean = rnorm(20, 0.5, 0.1),
  sd = rnorm(20, 0.02, 0.01),
  group = rep(c("group_a", "group_b"), 10)
)

plot_df <- plot_df |>
  mutate(
    ymin = as.numeric(factor(gene)) - .5,
    ymax = as.numeric(factor(gene)) + .5,
    fill = factor(as.numeric(factor(gene)) %% 2)
  )

# the plot
ggplot(plot_df, aes(y = gene)) +
  scale_y_discrete(expand = c(0, .5)) +
  geom_rect(
    aes(ymin = ymin, ymax = ymax, fill = fill, xmin = -Inf, xmax = Inf),
    alpha = .3
  ) +
  geom_point(aes(x = mean, color = group),
    position = position_dodge(width = 0.9)
  ) +
  geom_errorbar(aes(xmin = mean - sd, xmax = mean + sd, color = group),
    width = .2,
    position = position_dodge(.9)
  ) +
  geom_vline(aes(xintercept = 0.5), linetype = 2, color = "gray") +
  scale_fill_manual(values = c("grey90", "grey60"), guide = "none") +
  theme_bw() +
  theme(
    panel.background = element_blank(),
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank()
  )

    • 2

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