Hello, My setup looks like the following:
sample timepoint condition
s1 0 plus
s2 0 plus
s3 0 minus
s4 0 minus
s5 1 plus
s6 1 plus
s7 1 minus
s8 1 minus
s9 2 plus
s10 2 plus
s11 2 minus
s12 2 minus
I am trying to set up a DEXSeq DTU analysis. I am following this protocol: https://f1000research.com/articles/7-952/v3
So the model is going to be interaction between time and condition. How do I set this up using Dexseq, but at the DTU level? I am not sure what the full or reduced model will be.
Dexseq already requires an interaction term, which is condition:exon. I guess the interaction that I am interested in is condition and timepoint.
This is easier to do using DRIMSeq, as the full model will just have condition:timepoint, with the reduced model not having this interaction.
After thinking this through, I think the models will be:
formulaFullModel = ~ sample + exon + condition:exon + timepoint:exon+ condition:timepoint:exon
formulaReducedModel = ~ sample + exon + condition:exon +timepoint:exon
However, I am wondering though, since we are comparing different isoforms, that the following reduced model makes more sense. Any thoughts?
formulaReducedModel = ~ sample + exon +timepoint:exon
For example, if the usage of an isoform goes from 30% to 40% to 50%, I think that baseline is also important.
Would appreciate if somebody could verify. Thanks in advance.
Apologies for late reply, Nirad. You probably figured it out by now. In the formulae, the 'exon' term would take the baseline transcript usage. The 'condition:exon' and 'timepoint:exon' would capture the changes of condition and timpoint vs the baseline, and 'condition:timepoint:exon' the interactions of condition and timpoint in exon usage. I think you could vary the reduced model depending on the effects that you are interested in capturing in the test.