此脚本无需修改，认清输入数据即可
rm(list = ls())
load(file = "step4output.Rdata")
1.火山图,输入数据是deg
{
library(dplyr)
dat <- mutate(deg,v=-log10(P.Value))
head(dat)
library(ggpubr)
ggscatter(dat, x = "logFC", y = "v",
color = "change",size = 0.5,
label = "symbol", repel = T,
#label.select = dat$symbol[1:30] ,
label.select = c('CD36','DUSP6'), #挑选一些基因在图中显示出来
palette = c("#00AFBB", "#999999", "#FC4E07"),#RGB颜色编号
ylab = "-log10p.value")
ggsave("volcano.png")
}
dev.off()
#palette里面是RGB颜色编号，想换其他颜色可以尝试https://www.114la.com/other/rgb.htm
取差异基因做热图
#输入数据是exp表达矩阵的子集
{
load(file = 'step2output.Rdata')
x=deg$logFC
names(x)=deg$probe_id
#上调下调基因各100个（可以自定义）
cg=c(names(head(sort(x),100)),#前一百
names(tail(sort(x),100)))
n=exp[cg,]
}
作热图
{
library(pheatmap)
annotation_col=data.frame(group=group_list)
rownames(annotation_col)=colnames(n)
#保存
pdf(file = "heatmap.pdf")
pheatmap(n,show_colnames =F,
show_rownames = F,
scale = "row",
#cluster_cols = F,
annotation_col=annotation_col)
dev.off()
}
heatmap.png
