I didn't find an answer to this searching the forums. I have RNASeq samples with 5'/3' biases that are unevenly distributed amongst the samples. Some of my conditions have more samples with the bias, some less - the reason for these biases is almost certainly different levels of RNA sample fragmentation or other differences in sample prep (PS: I realise that this is not a good start). This makes DESeq2 call DE amongst the bias distributions.
What is the best method for accounting for this variation in an objective way: the RUV package, adding 5'/3' calculated bias ratios to the GLM (e.g. from Picard), using residuals? Any opinions would be greatly appreciated.
Many thanks, J