I'm using DEP R package to perform analysis (including DE analysis) on proteins across different conditions https://bioconductor.org/packages/devel/bioc/vignettes/DEP/inst/doc/DEP.html
The package uses limma for DE analysis
My experiment is structured as :
sample - disease_state( disease / healthy) - environment (env1 / env2)
I wish to perform DE analysis for
- env1 Vs env2 samples
- within diseased, env1 vs env2 samples
- within healthy, env1 vs env2 samples
For 1, I'm just ignoring the disease_state factor and performing differential expression analysis across conditions env1 vs env2. Is this the correct approach ?
For 2, filter out only diseased samples and then then perform differential expression analysis across conditions env1 vs env2. Is this correct ? or do all the healthy samples also need to be somehow included so as not to lose information ?
Please do share any articles which would explain the fundamentals in terms of why one of these approaches are incorrect