Hi,
I'm quite new to R and DESeq2 and need some help troubleshooting! I'm working on analyzing a dataset comparing 3 groups: patients before and after a treatment against a healthy control (not given treatment).
For the first analysis I wanted compare MDD patients before and after, so I originally subset the data-frame to include just the MDD patients, and then created a factor to describe the timepoint, filtered the counts, and performed a DESeq2 analysis. With this, we get 0 DE genes. In other analysis, such as health control versus patients before treatment, we get anywhere between 0-6 DE genes.... so, something isn't quite working with this method.
It was suggested that we feed DESeq2 all of our data in order to improve the statistical power and then select an analysis within the function using the interaction argument, but after reading the Bioconductor manual this doesn't seem very applicable since our control group doesn't have a before and after, just one timepoint.
Does anyone have any suggestions as to how to better perform this analysis?
Thank you!
Doesn't sound to me like interactions are appropriate. You have before, after, control. Three levels of one factor.