Hello all,
I have some very generic/naive questions regarding EdgeR. My apologies if these questions were already asked, I could not find them answered clearly on the forum.
1. Build a generic design matrix
From EdgeR's documentation, in chapter "3.3 Experiments with all combinations of multiple factors", I read: "A simple, multi-purpose approach is to combine all the experimental factors into one combined factor"
If I understand correctly, this approach allows to specify a generic design matrix (only replicates are identified as such). Then, comparisons between conditions of interest are carried out using contrasts during statistical testing procedure. Does that sound corrrect ?
Does that mean that design matrix information is not required during estimation of dispersion ? In other terms, could you confirm that using this approach is theoretically equivalent to the classic approach where conditions are separated in design matrix ?
A systematic use of this strategy would help me for automatization of an analysis, and I was wondering whether it makes sense or not.
2. QC plots
While 'playing' with edgeR, I generated the attached plots. I believe these plots give important information about quality for downstream processes and I think it might be important to provide them for every analysis.
Unfortunately, the details of EdgeR's method are too elaborated for my understanding. I would like to know if there is a simple way to explain what is important to look for in them.
By reading documentation, I made myself a representation of what they mean but it is for sure incomplete and likely to be incorrect... I would appreciate a piece of advice from experts. Apologies if figures title/axes/legend don't make sense, I made some of them from what I thought I understood...
Thank you very much for your help.
Hello and thank you !
Ok
~0 + group
is what I was thinking about (generic design matrix), with groups defining combinations of experimental conditions as in you example. Then, that should allow me to compareWT
vsMut
using contrasts(1, 1, -1, -1)
, as well asUntreated
vsTreated
using a different contrast matrix(1, -1, 1, -1)
when applying statistical test. Is that approach correct and equivalent to defining separate factors for WT/Mut and Treated/Untreated in design matrix ?If so, this would be enough for my 'automation' needs.
Yup, that'd be the equivalent.
Awesome, thank you very much for your help.