I'm trying to do differential gene expression analysis (RNA-Seq data) using Limma and EdgeR How can I adjust my count matrix for technical confounders(RIN, batch)?

a. Is it possible to adjust for confounders within Limma?

b. Can I adjust the count matrix for covariates using linear regression and import the residuals for downstream differential expression analysis using Limma or EdgeR? Thanks!

"Yes, typically one simply adds batch and RIN as covariates if they seem relevant. " Do you mean that you can add covariates into the model matrix e.g. design<-model.matrix(~group+batch+RIN) Thanks!

Yes, correct

Is there a way to visualize the data (residuals) using PCA or MDS plot after performing the linear modeling? I want to do this to confirm the samples no longer cluster by batch.