Hi I am working on RNA-seq differential expression analysis using DESeq2 in R. My code looks like:
countMatrix2 = as.matrix(read.table("countMatrixName.txt", header = TRUE, row.names = 1)) condition2 <- factor(rep(c("Treatment", "Control"), each=4)) colData2 <- data.frame(condition2) rownames(colData2)<- colnames(countMatrix2) dds2<-DESeqDataSetFromMatrix(countMatrix2, colData2, ~ condition2) # Pre-filtering dds2 <- dds2[rowSums(counts(dds2))>=10,] # Setting the factor levels dds2$condition2 <- relevel(dds2$condition2, ref = "Control") # Differential Expression Analysis dds_des2 <- DESeq(dds2) # Getting result table with alpha = 0.05 res0052 <- results(dds_des2, alpha = 0.05)
From here, I want to know how many genes are expressed (for example simply count > 0) separately in Control group and Treatment group. I am confused because the result table only shows Control vs Treatment information like log2foldchange, p-value, etc. How can I separately observe each condition: Control group and Treatment group? This is my first time to use deseq2, and any thoughts are greatly helpful. Thank you!