I have been following the last DESeq2 pipeline to perform an RNAseq analysis with a dataset with low rin samples in the experimental (or treated) and high rin on the control ones.
I read a paper in which they perform RNAseq analysis with time-course RNA degradation and conclude that including RIN value as a covariate can mitigate some of the effects of low RIN in samples.
My question is how I should construct the design in the DESeq2 object:
~conditions+rin ~conditions*rin ~conditions:rin
none of them... :)
I cannot find proper resources where explain how to construct these models (I am new to the field...) and I recognise I crashed against a wall with these kinds of things. I would appreciate also some links to good resources to be able to understand which one is correct and why.
Thank you in advance!