本节来介绍如何使用ggplot2自定义绘制分面并添加统计信息,以及单分面数据注释
加载R包
library(tidyverse)
library(ggsignif)
library(ggsci)
绘制并排箱线图
通常geom_boxplot函数绘制的箱线图都是不带误差线的，在此我们通过stat_boxplot添加误差线
iris %>% pivot_longer(-Species) %>%
mutate(name=as.factor(name)) %>%
ggplot(aes(name,value,fill=Species))+
stat_boxplot(geom="errorbar",
position=position_dodge(width=0.8),width=0.2)+
geom_boxplot(position=position_dodge(width =0.8))
image.png
统计检验
p <- iris %>% pivot_longer(-Species) %>%
mutate(name=as.factor(name)) %>%
ggplot(aes(Species,value,fill=Species))+
stat_boxplot(geom="errorbar",
position=position_dodge(width=0.8),width=0.2)+
geom_boxplot(position=position_dodge(width =0.8))+
geom_signif(comparisons = list(c("setosa", "versicolor"),
c("virginica","versicolor"),
c("setosa","virginica")),
map_signif_level=T,vjust=0.5,color="black",
textsize=5,test=wilcox.test,step_increase=0.1)+
facet_wrap(.~name,nrow=1)+
scale_fill_jco()+
theme(legend.title=element_blank())+
labs(x=NULL,y=NULL)+
theme_classic()+
theme(strip.background = element_rect(fill="grey80",color="black"),
strip.text.x = element_text(size=10,color="black"),
axis.text.y=element_text(size=10,color="black"),
axis.ticks.x = element_blank(),
axis.text.x=element_blank(),
panel.spacing = unit(0,"lines"),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
legend.text = element_text(color="black",size=10),
legend.title=element_blank(),
legend.spacing.x=unit(0.1,'cm'),
legend.key=element_blank(),
legend.key.width=unit(0.6,'cm'),
legend.key.height=unit(0.6,'cm'),
plot.margin=unit(c(0.3,0.3,0.3,0.3),units=,"cm"))
单分面注释
有时可能只需要对单分面进行注释，此时可通过自定义数据集来给单个分面添加内容
data.segm<-data.frame(x=0.5,y=5,xend=4,yend=5,name="Sepal.Width")
ann_text <- data.frame(Species="versicolor",value=5.5,lab = "Text",
name= factor("Sepal.Width",
levels = c("Petal.Length","Petal.Width",
"Sepal.Length","Sepal.Width")))
p + geom_text(data = ann_text,label = "Sepal.Width")+
geom_segment(data=data.segm,color="red",
aes(x=x,y=y,yend=yend,xend=xend),inherit.aes=FALSE)
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R语言数据分析指南，持续分享数据可视化的经典案例及一些生信知识，希望对大家有所帮助
