You should process the data separately and once you have the expression matrix you can use methods like PCA to check if the variability of your data is being driven by the condition of interest. If this is not the case, you have a batch effect on your dataset. If you know what is causing the batch effect you can remove the batch effect using limma function removeBatchEffect() or model this batch effect in the design formula if you're using DESeq2 (the latter is indicated for DESeq2 DE analysis). If you don't know what is causing the batch effect you can use a tool like sva to find surrogate variables that will represent batch variables and either model them during your DE analysis or correct for them before your analysis, depending on which tool you'll use for the DE test.