ggpubr进行“paper”组图合并，也许比PS，AI更简单

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多个图形进行组图展示，可以既展示一个“事情”的多个角度，也可以进行异同的比较，同时也是发表论文所必须的。

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

一 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

创建用于图形组合的图：
#箱线图

Box_plot <- ggboxplot(ToothGrowth, x = "dose", y = "len",color = "dose", palette = "jco")

#点图

Dot_plot <- ggdotplot(ToothGrowth, x = "dose", y = "len",                 color = "dose", palette = "jco", binwidth = 1)

#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 whit
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)

# 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 coefficien

二 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)

参考链接：

http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/81-ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/

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