上次我们给大家介绍了用R的ggpubr包绘制各种散点图，今天我们继续学习ggpubr包绘制各种SCI发表级箱图。
library(ggpubr) library(patchwork)#如果没有安装要先安装 set.seed(123)#设种子数首先生成一个随机的数据集，该数据集有300个观测，3个变量(分别是A,sex,smokestatus）
dataset=data.frame(A=c(rnorm(150,12,2), rnorm(150, 6,1)),
sex=sample(c("0","1"),300,replace=TRUE),
smokestatus=sample(c("1","2","3"),300,replace=TRUE))绘制简单箱图：(下面的加号表示拼接图形,如果不需要拼接，可以直接把加号去掉)
ggboxplot(dataset, x = "smokestatus", y = "A",
bxp.errorbar=T,#显示误差条
width = 0.5,#箱体的宽度
color = "smokestatus", #分组
palette="aaas",#使用杂志aaas的配色
)+
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.5, color = "smokestatus",
palette="aaas",bxp.errorbar=T,
orientation = "horizontal"#调整图形方向为水平
)+
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.5,color = "smokestatus",
palette="aaas",bxp.errorbar=T,
notch = TRUE,#添加缺口
order = c("3","2","1")#调整顺序
)+
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.5, color = "smokestatus",
palette="aaas",bxp.errorbar=T,
select = c("3")#选择特定的水平来画图 )
绘制带散点的箱图
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.8,
add = "jitter",#添加图形元素
add.params=list(color = "smokestatus",size=0.8, shape = 23))#参数add的参数，可设置颜色
绘制簇状箱图(横坐标表示smokestatus分组，不同颜色代表不同性别sex）
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.6,
color = "black",#轮廓颜色
fill="sex",#填充
palette =c("#E7B800", "#00AFBB"),#分组着色
xlab = F, #不显示x轴的标签
bxp.errorbar=T,#显示误差条
bxp.errorbar.width=0.5, #误差条大小
size=1, #箱型图边线的粗细
outlier.shape=NA, #不显示outlier
legend = "right") #图例放右边
在箱图添加三组总体P值
ggboxplot(dataset, x = "smokestatus", y = "A", width = 0.8,
add = "jitter",add.params=list(color = "smokestatus",size=0.5))+
stat_compare_means(method = "anova")
两两比较
my_comparisons <- list( c("1", "2"), c("1", "3"), c("3", "2") )
ggboxplot(dataset, x = "smokestatus", y = "A",
color = "smokestatus", palette = "npg")+
#两两比较的p值
stat_compare_means(comparisons = my_comparisons, label.y = c(18, 22, 26))+
#整体的p值
stat_compare_means(label.y = 28)
固定某一组，其他与某组比较
ggboxplot(dataset, x = "smokestatus", y = "A",
color = "smokestatus", palette = "npg")+
# 整体的p值
stat_compare_means(method = "anova", label.y = 28)+
stat_compare_means(method = "t.test", #选择统计方法
ref.group = "1"#以smokestatus为1的作为对照组
)
分组/分面之后再做比较
ggboxplot(dataset, x = "sex", y = "A",
color = "sex", palette = "npg",
add = "jitter",
facet.by = "smokestatus"#按照smokestatus分不同的面板
)+
#label中去掉检验方法
stat_compare_means(aes(label = paste0("p = ", ..p.format..)))
今天箱图的学习到这。
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