I am trying to automate an RNA-seq protocol based on the normalisation function
RUVs which determines k factors of unwanted variation in your dataset that are then fitted in the
model.matrix that you provide to edgeR in a way like this
design <- model.matrix(~0+treatments + W_1 + W_2 + W_3 + W_4 + W_5, data=pData(set)). This example has
k=5 factors of unwanted variation (stored in my
pData(set) object). If with another dataset I had three factors of unwanted variation, then the code would be
design <- model.matrix(~0+treatments + W_1 + W_2 + W_3, data=pData(set)).
How can I have a "generalised" version of the code that accounts for all the unwanted factors of variation in my
pData(set) object without the need to manually type them into the formula?
Thanks in advance Luca