小提琴图保留了箱式图的优势，有效显示中位数，范围和变异性，简单美观可看性强，今天给大家分享下绘制小提琴图、箱线图、及散点图的基本做法。

读入数据

library(ggplot2)
library(patchwork)
data <- read.csv("DEGs_FC.csv",header=T)
head(data)
data$sampleA <- as.factor(data$sampleA) #指定因子

绘制

#箱线图
ggplot(data=data,aes(x=sampleA,
                         y=log2FoldChange,color=sampleA
                         ))+
  geom_boxplot() -> p1 

#散点图
ggplot(data=data,aes(x=sampleA,
                         y=log2FoldChange,
                         color=sampleA))+
  geom_jitter() -> p2

#小提琴图
ggplot(data=data,aes(x=sampleA,
                     y=log2FoldChange,
                     color=sampleA))+
  geom_violin() ->p3
p1+p2+p3+plot_layout(nrow=1)#拼图

三图合一

cbPalette <- c("#6495ED", "#DA70D6", "#FF3030")
ggplot(data=data,aes(x=sampleA,
                         y=log2FoldChange,
                         color=sampleA))+
  geom_jitter(alpha=0.2,
              position=position_jitterdodge(jitter.width = 0.35, 
                                            jitter.height = 0, 
                                            dodge.width = 0.8))+
  geom_boxplot(alpha=0.2,width=0.45,
               position=position_dodge(width=0.8),
               size=0.75,outlier.colour = NA)+
  geom_violin(alpha=0.2,width=0.9,
              position=position_dodge(width=0.8),
              size=0.75)+
  scale_color_manual(values = cbPalette)+
  theme_classic() +
  theme(legend.position="none") + 
  theme(text = element_text(size=16)) + 
  #ylim(0.0,1.3)+
  ylab("log2Fold Change")+xlab("Treatment")+
  theme(axis.text.x=element_text(vjust=1,size=20,face = "bold"))+
  theme(axis.text.y=element_text(vjust=1,size=20,face = "bold"))