Hi all,

I am doing an RNA-seq analysis. I have two CSV files, and I want to get a set of data of my genes during P Values to know which genes in each CSV file are up regulated. EdgeR achieves the tables in differential gene expression in R studio, and the script is written down. I use the codes for both tables that I have for gene counts achieved by ht-seq. At frist i want to know which genes are common among two tables and then use a python script to build a set or table to tell me which genes in each table are up regulated and which are not from the mutual ones that i find. The P value that i consider is < 5% . How can I do it by python? Also there is a point that i have to mention that the genes orders(first column) in the tables are not the same and they are different!

library(edgeR)

group <- factor(c(rep("pro-vaccine",30),rep("pre_vaccine",20)))
x<-read.csv("table_50_ID.csv")
y<-DGEList(counts = x, group=group)
y<-calcNormFactors(y)
design<-model.matrix(~group)
y<-estimateDisp(y,design)
fit<-glmFit(y,design)
lrt<-glmLRT(fit,coef = 2)
deg <-topTags(lrt, n = Inf , p= 0.05)$table
up <-deg[deg$logFC > 0,]
down <-deg[deg$logFC < 0,]
write.csv(up, file="up.csv")
write.csv(down, file="down.csv")

Here is also my tables shapes in R studio:

Thanks in advance