补充材料Fig9 小提琴图
image.png数据格式如下
image.png需要示例数据可以直接在文末留言
首先是读入数据df<-read.csv("Single_Cell/violineplot-1.csv",header=T)
colnames(df)
head(df)
最基本的小提琴图library(ggplot2)
#help(package="ggplot2")
ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin()
image.png 更改主题设置，包括ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line())
image.png 将x轴文字标签更改为垂直ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(),
axis.text.x = element_text(angle=90,hjust = 1,vjust=0.5))
image.png 更改坐标轴的标题，并给整幅图添加一个标题ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(),
axis.text.x = element_text(angle=90,hjust = 1,vjust=0.5),
plot.title = element_text(hjust=0.5))+
labs(x=NULL,
y=NULL,
title = "Complexity")
image.png 填充颜色ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin(aes(fill=cell.type),show.legend = F)+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(),
axis.text.x = element_text(angle=90,hjust = 1,vjust=0.5),
plot.title = element_text(hjust=0.5))+
labs(x=NULL,
y=NULL,
title = "Complexity")
image.png 叠加散点图ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin(aes(fill=cell.type),show.legend = F)+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(),
axis.text.x = element_text(angle=90,hjust = 1,vjust=0.5),
plot.title = element_text(hjust=0.5))+
labs(x=NULL,
y=NULL,
title = "Complexity")+
geom_jitter(size=0.5)
image.png这样的话论文中的图就复现出来了。上图叠加的散点图是矩形的，最近看到一个函数geom_sina()可以让散点图也以小提琴的形状显示，我们试一下用这个函数的效果，这个函数来自ggforce这个包，使用前需要先加载
library(ggforce)
ggplot(df,aes(x=cell.type,y=Complexity))+
geom_violin(aes(fill=cell.type),show.legend = F)+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(),
axis.text.x = element_text(angle=90,hjust = 1,vjust=0.5),
plot.title = element_text(hjust=0.5))+
labs(x=NULL,
y=NULL,
title = "Complexity")+
geom_sina(size=0.1,alpha=0.2)
image.png这样看起来比论文中的图好像好看一点
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