本文首发于“生信补给站”公众号 ggplot2|ggpubr进行“paper”组图合并
多个图形进行组图展示，既可以展示一个“事情”的多个角度，也可以进行异同的比较，同时也是发表paper所必须的。
可以利用PS或者AI进行处理，但是图形的大小，位置，布局，字体等的调整也不是一个小工程。本文利用R包-ggpubr函数从0开始介绍组图的合并方式，也许。。。比AI或者PS更简单易学呢。
基础函数进行组图合并可参考R|绘图边距及布局
载入数据，R包
加载函数包及数据集
#install.packages("ggpubr") library(ggpubr) # ToothGrowth数据集 data("ToothGrowth") head(ToothGrowth)
len supp dose
1 4.2 VC 0.5
2 11.5 VC 0.5
3 7.3 VC 0.5
4 5.8 VC 0.5
5 6.4 VC 0.5
6 10.0 VC 0.5
# mtcars 数据集 data("mtcars") mtcars$name <- rownames(mtcars) mtcars$cyl <- as.factor(mtcars$cyl) head(mtcars[, c("name", "wt", "mpg", "cyl")])
name wt mpg cyl
Mazda RX4 Mazda RX4 2.620 21.0 6
Mazda RX4 Wag Mazda RX4 Wag 2.875 21.0 6
Datsun 710 Datsun 710 2.320 22.8 4
Hornet 4 Drive Hornet 4 Drive 3.215 21.4 6
Hornet Sportabout Hornet Sportabout 3.440 18.7 8
Valiant Valiant 3.460 18.1 6
创建单图
创建用于图形组合的图：
#箱线图
Box_plot <- ggboxplot(ToothGrowth, x = "dose", y = "len",color = "dose", palette = "jco") Box_plot
#点图
Dot_plot <- ggdotplot(ToothGrowth, x = "dose", y = "len", color = "dose", palette = "jco", binwidth = 1) Dot_plot
#有序条形图
Bar_plot <- ggbarplot(mtcars, x = "name", y = "mpg", fill = "cyl", # change fill color by cyl color = "white", # Set bar border colors to white palette = "jco", # jco journal color palett. see ?ggpar sort.val = "asc", # Sort the value in ascending order sort.by.groups = TRUE, # Sort inside each group x.text.angle = 90 # Rotate vertically x axis texts ) + font("x.text", size = 8) Bar_plot
# 散点图
Scatter_plots <- ggscatter(mtcars, x = "wt", y = "mpg", add = "reg.line", # Add regression line conf.int = TRUE, # Add confidence interval color = "cyl", palette = "jco", # Color by groups "cyl" shape = "cyl" # Change point shape by groups "cyl" )+ stat_cor(aes(color = cyl), label.x = 3) # Add correlation coefficient Scatter_plots
图形组合
使用ggpubr包的函数ggarrange（）中在一页上进行组合展示
1）ToothGrowth数据集的箱线图，点图 组合展示
ggarrange(Box_plot, Dot_plot,labels = c("A", "B"),ncol = 2, nrow = 1)
#图的边缘放置共同的唯一图例：common.legend = TRUE参数
ggarrange(bxp, dp, labels = c("A", "B"), common.legend = TRUE, legend = "bottom")
2）mtcars 数据集的条形图，散点图组合展示
figure <- ggarrange(Scatter_plots, Bar_plot + font("x.text", size = 10),ncol = 1, nrow = 2)
#添加图形的注释信息（标题，副标题，坐标轴，字体，颜色等）
annotate_figure(figure, top = text_grob("Visualizing mpg", color = "red", face = "bold", size = 14), bottom = text_grob("Data source: mtcars data set", color = "blue", hjust = 1, x = 1, face = "italic", size = 10), left = text_grob("Figure arranged using ggpubr", color = "green", rot = 90), right = "Here )!", fig.lab = "Figure 1", fig.lab.face = "bold" )
3）ggarrange（）函数更改绘图的列/行跨度
#散点图在第一行跨两列，箱形图和点图并于第二行
ggarrange(Scatter_plots, # First row with scatter plot ggarrange(Box_plot, Dot_plot, ncol = 2, labels = c("B", "C")), # Second row with box and dot plots nrow = 2, labels = "A" # Labels of the scatter plot )
4）利用NULL构建空白图
示例：绘制具有边际密度图的散点图
#绘制主要散点图
Scatter_plots <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width", color = "Species", palette = "jco", size = 3, alpha = 0.6)+ border()
#上侧，右侧添加密度图
xplot <- ggdensity(iris, "Sepal.Length", fill = "Species", palette = "jco") yplot <- ggdensity(iris, "Sepal.Width", fill = "Species", palette = "jco")+ rotate() # 设置主题 yplot <- yplot + clean_theme() xplot <- xplot + clean_theme()
# 通过width和height参数调整图的大小
# 利用NULL设置空白图
ggarrange(xplot, NULL, Scatter_plots, yplot, ncol = 2, nrow = 2, align = "hv", widths = c(2, 1), heights = c(1, 2), common.legend = TRUE)
5）添加统计图表及文本信息
绘制变量“Sepal.Length” 的密度图以及描述性统计（mean，sd，...）的汇总表。
# Sepal.Length密度图
density.p <- ggdensity(iris, x = "Sepal.Length", fill = "Species", palette = "jco")
# Sepal.Length描述性统计
stable <- desc_statby(iris, measure.var = "Sepal.Length", grps = "Species") stable <- stable[, c("Species", "length", "mean", "sd")]
# 设置table的主题
stable.p <- ggtexttable(stable, rows = NULL, theme = ttheme("mOrange"))
# text 信息
text <- paste("iris data set gives the measurements in cm", "of the variables sepal length and width", "and petal length and width, reScatter_plotsectively,", "for 50 flowers from each of 3 Scatter_plotsecies of iris.", "The Scatter_plotsecies are Iris setosa, versicolor, and virginica.", sep = " ") text.p <- ggparagraph(text = text, face = "italic", size = 11, color = "black")
# 组图展示，调整高度和宽度
ggarrange(density.p, stable.p, text.p, ncol = 1, nrow = 3, heights = c(1, 0.5, 0.3))
#子母图展示
density.p + annotation_custom(ggplotGrob(stable.p), xmin = 5.5, ymin = 0.7, xmax = 8)
6）嵌套布局展示
p1 <- ggarrange(Scatter_plots, Bar_plot + font("x.text", size = 9), ncol = 1, nrow = 2) p2 <- ggarrange(density.p, stable.p, text.p, ncol = 1, nrow = 3, heights = c(1, 0.5, 0.3)) #先组合P1，P2，然后自定义行 列 ，嵌套组合展示 ggarrange(p1, p2, ncol = 2, nrow = 1)
