#表达矩阵必须是matrix类数据结构,每一列都是存放一个样本,每一行是一个探针信息或者是注释后的基因名+fit=eBayes(fit)#根据lmFit的拟合结果进行统计推断+deg=topTable(fit,coef=2,number=Inf)#得出差异比较矩阵}#view(deg) 差异表达矩阵deg.png image.png...
library(pheatmap)## 设定差异基因阈值,减少差异基因用于提取表达矩阵 #allDiff_pair=topTable(fit,adjust='BH',coef="group after",number=Inf,p.value=0.05,lfc=0.5)allDiff1_2=topTable(fit2,adjust='fdr',coef=1,number=Inf)allDiff_2<-allDiff1[allDiff1$P.Value<0.05,]head(allDiff_2) ## logFC...
ifelse(DEG$log2FoldChange>logFC_cutoff,'UP','DOWN'),'NOT'))this_tile<-paste0('Cutoff for logFC is ',round(logFC_cutoff,3),'\nThe number of up gene is ',nrow(DEG[DEG$change=='UP