The comparison you've done seems exactly right to test whether treatment 2 modifies or enhances the effect of treatment 1. Have you examined an MDS plot to see whether the different groups appear separate?

https://www.genome.jp/dbget-bin/www_bget?K00004 I'm looking into Enzyme Commission (EC) numbers and I've noticed many annotations have the following scenarios: * Multiple ECs * An EC without only 3 levels According to Expasy (https://enzyme.expasy.org/EC/1.1.1.-): ``` 1.-.-.-: Oxidoreductases 1.1.-.-: Acting on the CH-OH group of donors...

There's no need for form a contrast because the score variable is already in the model. A continuous variable is its own contrast. Just run the usual limma pipeline and test for `score`: ``` fit

Oh wow, bedops closest-features, how did I overlook that!! I didn't know about it; thank you! Your awk script is beautiful. This worked perfectly for me, thank you so much Alex. I had been struggling with this for days.

Thank you Pierre! I'll try this out with my full data set.

I happend to see one paper doing the similar thing, share it with you guys, "A systematic evaluation of normalization methods and probe replicability using infinium EPIC methylation data". Hope it will help.