Dear All,

I am a newbie to RNAseq data analysis. Recently I have RNA seq data which include 4 samples and each of the sample include triplicates. I used DESeq2 pipeline for analysing the data and in the PCA plot i could see that all rep1s from all 4 samples are clustered together and rep2 from all samples are clustered together and rep3 from all samples are clustered together(rather clustering to their respective samples). My friend who prepared the samples told that he processed rep1 samples, rep2 samples and rep3 samples in consecutive days.

I used removeBatcheffect using the following code on the vsd transformed data

   vsd <- vst(dds)
   plotPCA(vsd, "batch")
   assay(vsd) <- limma::removeBatchEffect(assay(vsd), vsd$batch)
   plotPCA(vsd, "batch")

and the PCA looked far better where the replicates clustered according to their respective samples. But is it possible to remove the batch effect from raw counts or normalised counts in DEseq2 or any other package. Any guidance would be really useful. Thanks in advance.

For the purpose of differential expression, we do not remove the batch effect, but instead include the batch variable in the design, e.g. ~batch + condition.

(This example is given in the first code chunk of the DESeq2 vignette)