ggpubr

ggpubr专门为学术期刊绘图而生，据说是能画出editor最喜欢看的图。

1.安装和加载

由于这个包放在cran上，所以安装也方便，直接install.packages().

install.packages("ggpubr")
library("ggpubr")

2.绘图示例

• Gene expression data
• Box plots
• Violin plots
• Stripcharts and dot plots
• Density plots
• Histogram plots
• Empirical cumulative density function
• Quantile - Quantile plot

library(ggpubr)
set.seed(1234)
wdata = data.frame(
   sex = factor(rep(c("F", "M"), each=200)),
   weight = c(rnorm(200, 55), rnorm(200, 58)))#200个随机数，平均数是55
head(wdata, 4)
 #  sex   weight
#1   F 53.79293
#2   F 55.27743
#3   F 56.08444
#4   F 52.65430

2.1 Density plots

# Density plot with mean lines and marginal rug
# :::::::::::::::::::::::::::::::::::::::::::::::::::
# Change outline and fill colors by groups ("sex")
# Use custom palette
ggdensity(wdata, x = "weight",
          add = "mean", rug = TRUE,
          color = "sex", fill = "sex",
          palette = c("#00AFBB", "#E7B800"))

其中，x为横轴需要绘制的变量；add = "mean"表示添加上均值；rug = TRUE表示添加数据小地毯，这样更能展示出数据的分布；color = "sex", fill = "sex"，表示密度图的颜色以sex为填充，如果只有color没有fill，则只会展示出密度曲线，不会有填充，反之则密度曲线都用黑线表示；palette作为调色板，指定绘图颜色。

image

2.2 Histogram plot

# Histogram plot with mean lines and marginal rug
# :::::::::::::::::::::::::::::::::::::::::::::::::::
# Change outline and fill colors by groups ("sex")
# Use custom color palette
gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))

参数与Density plots类似，便不再赘述。

image

2.3 Box plots and violin plots

# Load data
data("ToothGrowth")
df <- ToothGrowth
head(df, 4)
   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

# Box plots with jittered points
# :::::::::::::::::::::::::::::::::::::::::::::::::::
# Change outline colors by groups: dose
# Use custom color palette
# Add jitter points and change the shape by groups
p <- ggboxplot(df, x = "dose", y = "len",
               color = "dose", palette =c("#00AFBB", "#E7B800", "#FC4E07"),
               add = "jitter", shape = "dose")
p

image

做什么类型的图，都要把参数调成示例的模样，然后再进一步地修改，上述参数意义为以dose为横坐标，len为纵坐标，根据不同的dose填充不同的颜色;add = "jitter"表示在boxplot上添加跳动的点，表示数据的分布;shape = "dose"表示点的形状依据dose。

给横坐标分组添加P值

# Add p-values comparing groups
 # Specify the comparisons you want
my_comparisons <- list( c("0.5", "1"), c("1", "2"), c("0.5", "2") )
p + stat_compare_means(comparisons = my_comparisons)+ # Add pairwise comparisons p-value
  stat_compare_means(label.y = 50)                   # Add global p-value

my_comparisons表示添加比较的分组；label.y表示总的P值显示的位置。若去除最后一个stat_compare_means，则不显示整体的P值。

image

小提琴图

# Violin plots with box plots inside
# :::::::::::::::::::::::::::::::::::::::::::::::::::
# Change fill color by groups: dose
# add boxplot with white fill color
ggviolin(df, x = "dose", y = "len", fill = "dose",
         palette = c("#00AFBB", "#E7B800", "#FC4E07"),
         add = "boxplot", add.params = list(fill = "white"))+
  stat_compare_means(comparisons = my_comparisons, label = "p.signif")+ # Add significance levels
  stat_compare_means(label.y = 50)                                      # Add global the p-value 

image

label中P值有两种表示方式，Allowed values include "p.signif" (shows the significance levels), "p.format" (shows the formatted p value),默认是第二种方式。其中，add = "boxplot"表示在小提琴图上添加箱线图，add.params表示add添加图形的参数，此处为添加白色的箱线图。

2.4 Bar plots

2.4.1Ordered bar plots

data("mtcars")

df2 <- mtcars

df2$cyl <- factor(df2$cyl)

df2$name <- rownames(df2) #添加一行name

head(df2[, c("name", "wt", "mpg", "cyl")])
df2<-dfm

ggbarplot(dfm, 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 = "desc",          # Sort the value in dscending order
          sort.by.groups = FALSE,     # Don't sort inside each group
          x.text.angle = 90           # Rotate vertically x axis texts
)

image

fill = "cyl"，表示颜色填充按另一个分组来；color = "white"改变柱子的边界，即无色；sort.val = "desc"表示变量按降序排列，其他的选择为 Allowed values are "none" (no sorting), "asc" (for ascending) or "desc" (for descending)；sort.by.groups = FALSE表示分好的组并不聚集在一起，若为T，则聚集在一起； x.text.angle = 90X轴的名称逆时针旋转90度。

2.4.2 分组内部排序的barplot

通过设置sort.by.groups = TRUE。

ggbarplot(dfm, 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 dscending order
          sort.by.groups = TRUE,      # Sort inside each group
          x.text.angle = 90           # Rotate vertically x axis texts
          )

image

2.4.3 Deviation graphs

偏差图显示了定量值与参考值的偏差，下面的代码中，我们将从mtcars数据集绘制mpg z-score。
Calculate the z-score of the mpg data:
因子的设定值得学习，因子里面夹带了一个判断语句。

# Calculate the z-score of the mpg data
dfm$mpg_z <- (dfm$mpg -mean(dfm$mpg))/sd(dfm$mpg)
dfm$mpg_grp <- factor(ifelse(dfm$mpg_z < 0, "low", "high"), 
                     levels = c("low", "high"))
# Inspect the data
head(dfm[, c("name", "wt", "mpg", "mpg_z", "mpg_grp", "cyl")])

创造一个有序的barplot，并且根据mpg因子的水平上色。

ggbarplot(dfm, x = "name", y = "mpg_z",
          fill = "mpg_grp",           # change fill color by mpg_level
          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 = FALSE,     # Don't sort inside each group
          x.text.angle = 90,          # Rotate vertically x axis texts
          ylab = "MPG z-score",
          xlab = FALSE,
          legend.title = "MPG Group"
          )

image

legend.title对legend添加名称。

旋转图像。use rotate = TRUE and sort.val = “desc”

ggbarplot(dfm, x = "name", y = "mpg_z",
          fill = "mpg_grp",           # change fill color by mpg_level
          color = "white",            # Set bar border colors to white
          palette = "jco",            # jco journal color palett. see ?ggpar
          sort.val = "desc",          # Sort the value in descending order
          sort.by.groups = FALSE,     # Don't sort inside each group
          x.text.angle = 90,          # Rotate vertically x axis texts
          ylab = "MPG z-score",
          legend.title = "MPG Group",
          rotate = TRUE,
          ggtheme = theme_minimal()
          )

image

2.5 Dot charts

Lollipop chart(棒棒糖图)
当您有大量的值要可视化时，棒棒图是柱状图的另一种选择。

2.5.1 一般棒棒糖图

ggdotchart(dfm, x = "name", y = "mpg",
           color = "cyl",                                # Color by groups
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), # Custom color palette
           sorting = "ascending",                        # Sort value in descending order
           add = "segments",                             # Add segments from y = 0 to dots
           ggtheme = theme_pubr()                        # ggplot2 theme
           )

image

add = "segments"添加棒。

2.5.2 水平棒棒糖图

• Sort in descending order. sorting = “descending”.
• Rotate the plot vertically, using rotate = TRUE.
• Sort the mpg value inside each group by using group = “cyl”.
• Set dot.size to 6.
• Add mpg values as label. label = “mpg” or label = round(dfm$mpg).

ggdotchart(dfm, x = "name", y = "mpg",
           color = "cyl",                                # Color by groups
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), # Custom color palette
           sorting = "descending",                       # Sort value in descending order
           add = "segments",                             # Add segments from y = 0 to dots
           rotate = TRUE,                                # Rotate vertically
           group = "cyl",                                # Order by groups
           dot.size = 6,                                 # Large dot size
           label = round(dfm$mpg),                        # Add mpg values as dot labels
           font.label = list(color = "white", size = 9, 
                             vjust = 0.5),               # Adjust label parameters
           ggtheme = theme_pubr()                        # ggplot2 theme
           )

image

group=按组进行排序；dot.size设置点的大小；label将值写在点上，其中round()表示取整；font.label设置点的字体。

2.5.3 棒棒糖图类型的偏差图

• Use y = “mpg_z”
• Change segment color and size: add.params = list(color = “lightgray”, size = 2)

ggdotchart(dfm, x = "name", y = "mpg_z",
           color = "cyl",                                # Color by groups
           palette = c("#00AFBB", "#E7B800", "#FC4E07"), # Custom color palette
           sorting = "descending",                       # Sort value in descending order
           add = "segments",                             # Add segments from y = 0 to dots
           add.params = list(color = "lightgray", size = 2), # Change segment color and size
           group = "cyl",                                # Order by groups
           dot.size = 6,                                 # Large dot size
           label = round(dfm$mpg_z,1),                        # Add mpg values as dot labels
           font.label = list(color = "white", size = 9, 
                             vjust = 0.5),               # Adjust label parameters
           ggtheme = theme_pubr()                        # ggplot2 theme
           )+
  geom_hline(yintercept = 0, linetype = 2, color = "lightgray")

image

geom_hline绘制指定的水平线。

2.5.4 Cleveland’s dot plot

说白了就是将Y轴的颜色和图中分组的颜色对应起来。Use y.text.col = TRUE.

image

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3. 常用基本绘图函数及参数

基本绘图函数

gghistogram Histogram plot #绘制直方图

ggdensity Density plot #绘制密度图

ggdotplot Dot plot #绘制点图

ggdotchart Cleveland's Dot Plots #绘制Cleveland点图

ggline Line plot #绘制线图

ggbarplot Bar plot #绘制柱状图

ggstripchart Stripcharts #绘制带状图

ggboxplot Box plot #绘制箱线图

ggviolin Violin plot #绘制小提琴图

ggpie Pie chart #绘制饼图

ggqqplot QQ Plots #绘制QQ图

ggscatter Scatter plot #绘制散点图

ggmaplot MA-plot from means and log fold changes #绘制M-A图

ggpaired Plot Paired Data #绘制散点图矩阵

ggerrorplot Visualizing Error #绘制误差图

基本参数

ggtext Text #添加文本

border Set ggplot Panel Border Line #设置画布边框

grids Add Grids to a ggplot #添加网格线

font Change the Appearance of Titles and Axis Labels #设置字体类型

bgcolor Change ggplot Panel Background Color #更改画布背景颜色

background_image Add Background Image to ggplot2 #添加背景图片

facet Facet a ggplot into Multiple Panels #设置分面

ggpar Graphical parameters #添加画图参数

ggparagraph Draw a Paragraph of Text #添加文本段落

ggtexttable Draw a Textual Table #添加文本表格

ggadd Add Summary Statistics or a Geom onto a ggplot #添加基本统计结果或其他几何图形

ggarrange Arrange Multiple ggplots #排版多个图形

gradient_color Set Gradient Color #设置连续型颜色

xscale Change Axis Scale: log2, log10 and more #更改坐标轴的标度

add_summary Add Summary Statistics onto a ggplot #添加基本统计结果

set_palette Set Color Palette #设置画板颜色

rotate Rotate a ggplot Horizontally #设置图形旋转

rotate_axis_text Rotate Axes Text #旋转坐标轴文本

stat_stars Add Stars to a Scatter Plot #添加散点图星标

stat_cor Add Correlation Coefficients with P-values to a Scatter Plot #添加相关系数

stat_compare_means Add Mean Comparison P-values to a ggplot #添加平均值比较的P值

theme_transparent Create a ggplot with Transparent Background #设置透明背景

theme_pubr Publication ready theme #设置出版物主题

参考链接：
http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/
链接：https://www.jianshu.com/p/f53a05da7745
参考链接：https://www.jianshu.com/p/43967191bb06