Hi guys, I have a simple question. I have RNA-Seq data from different batches. As suggested looking at many posts on-line I have pre-normalized my data (using the TMM from edgeR) then I have corrected them using Combat and then I have re-normalized them (for the library-size) using DESeq2. My question is: is it correct the second normalisation after Combat? Or at least is it not dramatically not-correct? 


Thank you in advance

Best 
A quick note since this is a common problem, but for batch correction you generally need to have multiple conditions per batch. If all your WT samples are in one batch, and all your KD samples are in another batch, you can't correct for it (as an example).

With that being said, you can usually add batch as a covariate to the regression formula in edgeR and DESeq2 as the simpler and more robust option. Your study design would look like the following example for DESeq2:

    > df
         condition   batch
    WT-1        WT batch_1
    WT-2        WT batch_2
    WT-3        WT batch_2
    KO-1        KO batch_1
    KO-2        KO batch_2
    KO-3        KO batch_2

Your regression formula would then be `~ condition + batch`, which means your differential expression results for condition will be corrected for batch.