多分组差异分析结果的两种展示形式

#读取数据
dat00<-read.csv("DEseq2-FC.csv")
head(dat00)
dat00=dat00[,-1] #因为行名的命名规则是不可有重复项，所以这里我们把第一列Name信息去了，使用序列号命名行名，不影响后期作图
#构造数据集用来添加中间部分的色块
dat<-data.frame(x=c("0d vs. 3d","0d vs. 6d","0d vs. 9d","3d vs. 6d","3d vs. 9d","6d vs. 9d"),
y=0,
label=c("0d vs. 3d","0d vs. 6d","0d vs. 9d","3d vs. 6d","3d vs. 9d","6d vs. 9d"))
#构造数据集用来添加背景的灰色柱子
datbar<-data.frame(x=c("0d vs. 3d","0d vs. 6d","0d vs. 9d","3d vs. 6d","3d vs. 9d","6d vs. 9d"),
y=c(20,22,24,10,10,10))
library(ggplot2)
library(ggnewscale)
library(tidyverse)
head(dat00)
p=ggplot()+
geom_col(data=datbar,aes(x=x,y=y),fill="grey",alpha=0.5)+
geom_col(data=datbar,aes(x=x,y=-y),fill="grey",alpha=0.5)+
geom_jitter(data=dat00 %>% filter(newcol1 == 'pvalue > 0.05'),
aes(x=newcol2,y=log2FoldChange,
color=newcol1))+
geom_jitter(data=dat00 %>% filter(newcol1 == 'pvalue < 0.05'),
aes(x=newcol2,y=log2FoldChange,
color=newcol1))+
scale_color_manual(name=NULL,
values = c("red","darkgrey"))+
ggnewscale::new_scale_fill()+
theme_minimal()+
theme(axis.line.y = element_line(),
axis.ticks.y = element_line(),
panel.grid = element_blank(),
legend.position = "top",
legend.justification = c(1,0),
legend.direction = "vertical",
axis.text.x = element_blank())+
labs(x=" ",y="average log2(FlodChang)")+
geom_tile(data=dat,
aes(x=x,y=y,fill=x),
height=3,color="black",
alpha=0.9,
show.legend = F)+
scale_fill_manual(values = c("#ECC947","#44a9a9","#4177aa","#12783c","#a94698","#E15659"))+
geom_text(data=dat,aes(x=x,y=y,label=label))
#输出图片
pdf(file="DEseq2-FC1.pdf", height=7, width=7)
print(p)
dev.off()