本文中的数据包括配对的18个肝细胞癌和癌旁样本
0.加载包
library(limma)
1.导入数据
行是基因，列是样本
exp <- readRDS("exp_mRNA.rds")
2.分组标签
# group
group_list <- factor(rep(c("Normal", "Tumor"),18))
design <- model.matrix(~group_list)
colnames(design) <- levels(group_list)
rownames(design) <- colnames(exp)
3.识别差异基因
# limma DEG
fit <- lmFit(exp, design)
fit <- eBayes(fit, trend = TRUE)
output <- topTable(fit, coef = 2, n = Inf, sort.by = "p")
4.选取p值<0.05，| logFC | > 1的基因
output1 <- topTable(fit, coef = 2, n = Inf, sort.by = "p", p.value = 0.05, lfc = 1)
