Hi guys, I know that DESeq as well as EdgeR perform differential gene expression analysis from RNA seq experiments using counts. I have normalized my data.frame using an independent method (qsmooth not in the pipeline of the two packages). The input/output of the normalisation are log2(counts). Now, I would like to perform differential gene expression analysis between the conditions of my dataset using quasi-likelihood negative binomial method. I know that the function voom of Limma allows the transformation of counts to log2-counts per million for subsequent linear model. However it is not clear if this is the case in my analytical condition. Can anyone please explain/suggest me how to proceed for differential expression analysis using my log2 normalized counts?
Thank you a lot!