R_Code :RNAseq_DEGs

library(DESeq2)
library(dplyr)

# 读取表达矩阵
mycounts <- read.csv("Input File Format/mycounts.csv",row.names = 1)

# 查看读入的表达矩阵
head(mycounts)
dim(mycounts)

# 去除表达量全为0的行
mycounts_1 <- mycounts[rowSums(mycounts) != 0,]
#查看去除后的剩余的基因数目
dim(mycounts_1)

# 读取分组文件
mymeta <- read.csv("Input File Format/mymeta.csv",stringsAsFactors = T)
mymeta
colnames(mycounts_1) == mymeta$id

dds <- DESeqDataSetFromMatrix(countData = mycounts_1, colData = mymeta,design = ~dex)
dds <- DESeq(dds)
res <- results(dds)

head(res)
res_1 <- data.frame(res)
head(res_1)

res_1 %>%
mutate(group = case_when(
log2FoldChange >= 1 & pvalue <= 0.05 ~ "UP",
log2FoldChange <= -1 & pvalue <= 0.05 ~ "DOWN",
TRUE ~ "NOT_CHANGE"
)) -> res_2

table(res_2$group)

write.csv(res_2, file = "diff_expr_result.csv", quote = F)

Demo Data csv:

2025060214542848 2025060214542958

本站原创,如若转载,请注明出处:https://www.ouq.net/3755.html

(0)
打赏 微信打赏,为服务器增加50M流量 微信打赏,为服务器增加50M流量 支付宝打赏,为服务器增加50M流量 支付宝打赏,为服务器增加50M流量
上一篇 05/27/2025 23:29
下一篇 06/02/2025 23:12

相关推荐