RNA-seq下游分析之 PCA图_欧阳火火的博客-CSDN博客
rm(list=ls())
mydata <- read.table("C:/Users/gao/Desktop/all.id.txt",header =TRUE,quote='\t',skip = 1)
smpleNames <- c('mesc_1','mesc_1','mesc_2','mesc_2','mesc_3','mesc_3','mesc_4','mesc_4','mesc_5','mesc_5','mesc_6','mesc_6','mesc_7','mesc_7','mesc_8','mesc_8')
names(mydata)[7:22] <- smpleNames
head(mydata)
countmatrix <- as.matrix(mydata[7:22])
rownames(countmatrix) <- mydata$Geneid
head(countmatrix)
save(countmatrix,file="expr.Rdata")
table2 <- data.frame(name = c('mesc_1','mesc_1','mesc_2','mesc_2','mesc_3','mesc_3','mesc_4','mesc_4','mesc_5','mesc_5','mesc_6','mesc_6','mesc_7','mesc_7','mesc_8','mesc_8'),condition = c('A','A','A','A','A','A','A','A','B','B','B','B','B','B','B','B'))
dds2 <- DESeqDataSetFromMatrix(countmatrix,colData=table2,design =~condition)
dds2 <- dds[rowSums(counts(dds2)) > 1,]
head(dds2)
rld1<- rlog(dds2)
plotPCA(rld1, intgroup=c( "name","condition"))
library(ggplot2)
data1 <- plotPCA(rld1, intgroup=c("condition","name"), returnData=TRUE)
percentVar1 <- round(100 * attr(data1, "percentVar"))
p1<- ggplot(data1, aes(PC1, PC2, color=name)) +
geom_point(size=3) +
xlab(paste0("PC1: ",percentVar[1],"% variance")) +
ylab(paste0("PC2: ",percentVar[2],"% variance"))
p1