R语言|ggpubr包绘图大法

一、准备

1.1 安装

#方法1
install.packages("ggpubr") 
#方法2
devtools::install_github("kassambara/ggpubr")

1.2 导入

library(ggpubr)

二、使用

2.1 带有均值线和地毯线的密度图

#构建数据集
set.seed(1234)
df <- data.frame( sex=factor(rep(c("f", "M"), each=200)),weight=c(rnorm(200, 55), rnorm(200, 58)))
# 预览数据格式
head(df)
# 绘制密度图
ggdensity(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",palette = c("#00AFBB", "#E7B800")) 
#rug参数添加地毯线，add参数可以添加均值mean和中位数median

##备注说明
 密度图展示不同性别分组下体重的分布，X轴为体重，Y轴为自动累计的密度，X轴上添加地毯线进一步呈现样本的分布；按性别分别组标记轮廓线颜色，再按性别填充色展示各组的分布，使用palette自定义颜色

2.2 带有均值线和边际地毯线的直方图

gghistogram(df, x="weight", add = "mean", rug = TRUE, color = "sex", fill = "sex",palette = c("#00AFBB", "#E7B800"))

2.3 箱线图+分组形状+统计

#加载数据集
data("ToothGrowth")
df1 <- ToothGrowth
p <- ggboxplot(df1, x="dose", y="len", color = "dose",
              palette = c("#00AFBB", "#E7B800", "#FC4E07"),
              add = "jitter", shape="dose")
#增加了jitter点，点shape由dose映射
p

2.4 箱线图+分组形状+统计

# 增加不同组间的p-value值，可以自定义需要标注的组间比较
my_comparisons <- list(c("0.5", "1"), c("1", "2"), c("0.5", "2"))
p+stat_compare_means(comparisons = my_comparisons)+    #不同组间的比较
stat_compare_means(label.y = 50)

2.5 内有箱线图的小提琴图+星标记

ggviolin(df1, 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")+   #label这里表示选择显著性标记（星号）
 stat_compare_means(label.y = 50)
#备注说明
#ggviolin绘制小提琴图， add = “boxplot”中间再添加箱线图，stat_compare_means中，设置lable=”p.signif”，即可添加星添加组间比较连线和统计P值按星分类。

2.6 条形/柱状图绘制(barplot)

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")])
ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
         palette = "npg", #杂志nature的配色
         sort.val = "desc", #下降排序
         sort.by.groups=FALSE, #不按组排序
         x.text.angle=60)
#柱状图展示不同车的速度，按cyl为分组信息进行填充颜色，颜色按nature配色方法(支持 ggsci包中的本色方案，如: “npg”, “aaas”, “lancet”, “jco”, “ucscgb”, “uchicago”, “simpsons” and “rickandmorty”)，按数值降序排列。

2.6 条形/柱状图绘制(barplot)+按组进行排序

ggbarplot(df2, x="name", y="mpg", fill = "cyl", color = "white",
         palette = "aaas", #杂志Science的配色
         sort.val = "asc", #上升排序,区别于desc，具体看图演示
         sort.by.groups=TRUE,x.text.angle=60) #按组排序 x.text.angle=90

2.7 偏差图绘制(Deviation graphs)+偏差图展示了与参考值之间的偏差

df2$mpg_z <- (df2$mpg-mean(df2$mpg))/sd(df2$mpg)    # 相当于Zscore标准化，减均值，除标准差
df2$mpg_grp <- factor(ifelse(df2$mpg_z<0, "low", "high"), levels = c("low", "high"))
head(df2[, c("name", "wt", "mpg", "mpg_grp", "cyl")])
ggbarplot(df2, x="name", y="mpg_z", fill = "mpg_grp", color = "white",
         palette = "jco", sort.val = "asc", sort.by.groups = FALSE,
         x.text.angle=60, ylab = "MPG z-score", xlab = FALSE, legend.title="MPG Group")

2.8 偏差图绘制(Deviation graphs)+坐标轴变换

ggbarplot(df2, x="name", y="mpg_z", fill = "mpg_grp", color = "white",
         palette = "jco", sort.val = "desc", sort.by.groups = FALSE,
         x.text.angle=90, ylab = "MPG z-score", xlab = FALSE,
         legend.title="MPG Group", rotate=TRUE, ggtheme = theme_minimal())     # rotate设置x/y轴对换

2.9 棒棒糖图绘制(Lollipop chart)+代替条形图展示数据

ggdotchart(df2, x="name", y="mpg", color = "cyl",
          palette = c("#00AFBB", "#E7B800", "#FC4E07"),
          sorting = "ascending",
          add = "segments", ggtheme = theme_pubr())

2.10 棒棒糖图绘制(Lollipop chart)+修改样式

ggdotchart(df2, x="name", y="mpg", color = "cyl",
    palette = c("#00AFBB", "#E7B800", "#FC4E07"),
    sorting = "descending", add = "segments", rotate = TRUE,
    group = "cyl", dot.size = 6,
    label = round(df2$mpg), font.label = list(color="white",
    size=9, vjust=0.5), ggtheme = theme_pubr())

2.11 棒棒糖偏差图

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，设置一位小数
    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")

2.12 Cleveland点图绘制

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
    rotate = TRUE, # Rotate vertically
    dot.size = 2, # Large dot size
    y.text.col = TRUE, # Color y text by groups
    ggtheme = theme_pubr() # ggplot2 theme
    )+ theme_cleveland() # Add dashed grids