Dear Biostars, I performed DEG analysis for mouse RNA-Seq data using DESeq2. I have the following problem. I hope you can help me. I have 3 different treatments and one control group. Each condition has 2 biological replicates. I have the following code.
## generate a metadata condition <- c('control','control','lif','lif','il6','il6', 'cytokine','cytokine'). sample <- c('con1','con2','lif1','lif2', 'il6.1','il6.2','cyto1','cyto2') Metadata <- data.frame(sample,condition ) head(data) con1 con2 lif1 lif2 il6.1 il6.2 cyto1 cyto2 ENSMUSG00000000001 3110 3141 3299 3148 3698 3214 3239 3402
I am not showing my codes to make dds object, as it is hard for me to format codes here. In summary , my code worked ,and I tried to get results table using the above data with 8 samples. For result, I used the following code , by changing "il6" to other conditions.
IL6DEseqresult <- as.data.frame(results(dds, c("condition", "il6","control"), alpha = 0.05))
However, when I performed the same analysis starting with less number of samples I got very different padj, which affected my significant gene lists. I mean I started by subsetting two contrasting groups, and then get the dds object with control, and lif group. In this was I just had four samples (control1, control2, lif1, lif2), and I repeated the same for other groups. I got very different padj value. So , I am not sure , which strategy is a correct way. Can you please help me ? Thank you.