R语言之可视化（33）绘制差异基因分析统计图

读取各个数据集的差异分析结果。

GSE1 <- read.csv('diffSig.csv', header = T, row.names = 1)

GSE1 $Gene <- rownames(GSE1 )

GSE1 $GSE <- 'GSE1 '

colnames(GSE1 )

GSE1  <- subset(GSE1  select = c("Gene",    "GSE", "logFC") )

head(GSE1 )

将读取的差异分析结果合并，并将其分为上调和下调两个数据集

# --------------------------------------------------------

# --------------------------------------------------------


data <- rbind(dt1, dt2, dt3....)

table(data$GSE)


data1 <- subset(data, data$logFC > 0)

data2 <- subset(data, data$logFC < 0)


data1$logFC <-NULL
data2$logFC <-NULL

dt1 <- as.data.frame(table(data1$GSE))

dt1$sig <- 'Up-regulation'

dt2 <- as.data.frame(table(data2$GSE))

dt2$Freq <- -(dt2$Freq)

dt2$sig <- 'Down-regulation'

绘图

p <- ggplot() + 
  geom_bar(data = dt1, aes(x=Var1, y=Freq, fill=sig),stat = "identity",position = 'dodge') +
  geom_text(data = dt1, aes(x=Var1,  y=Freq, label=Freq, vjust=-0.25))+
 geom_bar(data = dt2, aes(x=Var1, y=Freq, fill=sig),stat = "identity",position = 'dodge') +
  geom_text(data = dt2, aes(x=Var1,  y=Freq, label=Freq, vjust=-0.25))+
  scale_fill_manual(values=c("#0072B5","#BC3C28"))+
  theme(axis.text.x = element_text(angle = 45, hjust = 0.5, vjust=0.5))+xlab('')+ylab('')

pdf(file = "deg_show.pdf",width=6,height=6)
p
dev.off()

基于此，就可以得到一张专门展示多个数据集差异分析结果统计的图，红色为每个数据集上调的基因数目。绿色为下调的基因数目。