气泡图

作者

[编辑] 郑虎;

[审核] .

气泡图是在散点图的基础上，用气泡的大小来展示第三个变量,从而能够同时对三个变量进行对比分析的统计图表。

环境配置

  • 系统: Cross-platform (Linux/MacOS/Windows)

  • 编程语言: R

  • 依赖包: ggplot2; stringr

# 安装包
if (!requireNamespace("ggplot2", quietly = TRUE)) {
  install.packages("ggplot2")
}
if (!requireNamespace("stringr", quietly = TRUE)) {
  install.packages("stringr")
}

# 加载包
library(ggplot2)
library(stringr)

数据准备

载入数据为 GO Term, Gene Ridio,基因数和 P 值。

# 加载数据
data <- read.delim("files/Hiplot/016-bubble-data.txt", header = T)

# 整理数据格式
data[, 1] <- str_to_sentence(str_remove(data[, 1], pattern = "\\w+:\\d+\\W"))
topnum <- 7
data <- data[1:topnum, ]
data[, 1] <- factor(data[, 1], level = rev(unique(data[, 1])))

# 查看数据
head(data)
                               Term Count     Ratio   PValue
1                   Immune response    20 10.471204 9.61e-08
2     Defense response to bacterium    11  5.759162 3.02e-06
3                   Cell chemotaxis     8  4.188482 5.14e-06
4                     Cell adhesion    17  8.900524 2.73e-05
5             Complement activation     8  4.188482 3.56e-05
6 Extracellular matrix organization    11  5.759162 4.23e-05

可视化

# 气泡图
p <- ggplot(data, aes(Ratio, Term)) +
  geom_point(aes(size = Count, colour = -log10(PValue))) +
  scale_colour_gradient(low = "#00438E", high = "#E43535") +
  labs(colour = "-log10 (PValue)", size = "Count", x = "Ratio", y = "Term", 
       title = "Bubble Plot") +
  scale_x_continuous(limits = c(0, max(data$Ratio) * 1.2)) +
  guides(color = guide_colorbar(order = 1), size = guide_legend(order = 2)) +
  scale_y_discrete(labels = function(x) {str_wrap(x, width = 65)}) +
  theme_bw() +
  theme(text = element_text(family = "Arial"),
        plot.title = element_text(size = 12,hjust = 0.5),
        axis.title = element_text(size = 12),
        axis.text = element_text(size = 10),
        axis.text.x = element_text(angle = 0, hjust = 0.5,vjust = 1),
        legend.position = "right",
        legend.direction = "vertical",
        legend.title = element_text(size = 10),
        legend.text = element_text(size = 10))

p
图 1: 气泡图

x 轴表示 Gene Ridio，y 轴是 GO Term; 点的大小表示基因数，点的颜色代表 P 值的高低。