Thank you so much for your clarification and advice, andres.
I have a gene expression dataset. 20 samples for case status and 20 samples for control status of a disease. I have created a separate network for case samples and a separate network for control samples. Now, these two networks have got their own module sets.
how can I relate the disease status (case, control) to my networks and identify important modules?
I have a feeling that I am doing it all wrong. I will be thankful if you can point out what I am doing wrong here.
1 answer
When I have a relatively simple experimental design (case vs control) I would rather perform a consensus network analysis instead of building two independent network. Your approach would be fine if you have a more complex study design e.g., samples collected from multiple tissues, sex, age or continuous traits.
In conclusion: 1) build a consensus network; 2) run the module-trait relationship protocol to find cluster of co-expressed genes between case and control samples
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