I'm wondering when it is appropriate to do a module preservation analysis with WGCNA rather than a consensus module analysis?
In my situation I have expression data from patients before and after starting treatment with a new drug (baseline, and 1, 6, and 14 weeks after commencing treatment).
I've identified modules with WGCNA at each time point. I'd like to know if there are robust modules that are preserved throughout the time course and other modules that are less well preserved.
I'm unsure whether consensus analysis or module preservation is the best way to look at this?
This is a question I've been thinking about as well. Although I don't have the insight of the original authors, here's my reasoning: Consensus module analysis is suitable for figuring out modules that would be shared / common across the independent datasets you're considering. For example, which modules are common between multiple celltypes of a tissue. Module preservation analysis, on the other hand, allows you to say if module X in one cell-type, how well preserved or disrupted it in the other cell type. This allows you to differentiate if a condition or treatment affects different celltypes in the same way or not.
