5. 差异分析 - 作图 - 火山图、热图

rm(list = ls()) 
load(file = "step1output.Rdata")
load(file = "step4output.Rdata")
#1.火山图----
library(dplyr)
library(ggplot2)
dat  = deg

p <- ggplot(data = dat, 
            aes(x = logFC, 
                y = -log10(P.Value))) +
  geom_point(alpha=0.4, size=3.5, 
             aes(color=change)) +
  ylab("-log10(Pvalue)")+
  scale_color_manual(values=c("blue", "grey","red"))+
  geom_vline(xintercept=c(-logFC_t,logFC_t),lty=4,col="black",lwd=0.8) +
  geom_hline(yintercept = -log10(P.Value_t),lty=4,col="black",lwd=0.8) +
  theme_bw()
p


if(T){
  #自选基因
  for_label <- dat%>% 
    filter(symbol %in% c("TRPM3","SFRP1")) 
}
if(F){
  #p值最小的10个
  for_label <- dat %>% head(10)
}
if(F) {
  #p值最小的前3下调和前3上调
  x1 = dat %>% 
    filter(change == "up") %>% 
    head(3)
  x2 = dat %>% 
    filter(change == "down") %>% 
    head(3)
  for_label = rbind(x1,x2)
}

volcano_plot <- p +
  geom_point(size = 3, shape = 1, data = for_label) +
  ggrepel::geom_label_repel(
    aes(label = symbol),
    data = for_label,
    color="black"
  )
volcano_plot
ggsave(plot = volcano_plot,filename = paste0(gse,"volcano.png"))

#2.差异基因热图----

load(file = 'step2output.Rdata')
if(F){
  #全部差异基因
  cg = deg$probe_id[deg$change !="stable"]
  length(cg)
}else{
  #取前30上调和前30下调
  x=deg$logFC[deg$change !="stable"] 
  names(x)=deg$probe_id[deg$change !="stable"] 
  cg=c(names(head(sort(x),30)),names(tail(sort(x),30)))
  length(cg)
}
n=exp[cg,]
dim(n)

#作热图
library(pheatmap)
annotation_col=data.frame(group=group_list)
rownames(annotation_col)=colnames(n) 
library(ggplotify)
heatmap_plot <- as.ggplot(pheatmap(n,show_colnames =F,
                          show_rownames = F,
                          scale = "row",
                          #cluster_cols = F, 
                          annotation_col=annotation_col)) 
heatmap_plot
ggsave(heatmap_plot,filename = paste0(gse,"heatmap.png"))
load("pca_plot.Rdata")
library(patchwork)
(pca_plot + volcano_plot +heatmap_plot)+ plot_annotation(tag_levels = "A")

标签：load,filter,head,作图,library,dat,file,热图,GEO
来源： https://www.cnblogs.com/xiaogaobugao/p/16675834.html