How to design WGCNA: one analysis over all sample or seperate analysis (using consensus module analysis)?
I have (wild type /mutant) (male / female) (3 developmental stages) * (each 3 replicates ) total 36 samples.
Seeing sexual difference in [WT vs MT] is the main goal.
Samples in each developmental stages (12 samples) were prepared, sequenced, and analyzed seperately.
I currently have DESeq normalized read count data as the result.
I am confused about which is the most appropriate method to do WGCNA.
- Use all samples in one adjacency matrix to identify modules once.
- Separate by condition to identify modules seperately.
(If so, should I seperate by sex/ genotype/ time ?)
- Separate by condition and identify consensus module.
Currently, I am thinking of seperating samples by developmental stages and identifying consensus modules to avoid batch effect.
Which analysis best fit the purpose? What critetria should I consider when I choose between these different analysis?
If I seperate by developmental stages, I have 12 samples each. I read that at least 15 samples are
needed. Also, to compare between male vs female / WT vs mutant, I only have 3 replicates each. Is the sample size too small?
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