binary phenotype or discrete traits in wgcna analysis
In WGCNA R package how do you correlate identified co-expression modules with binary phenotype data ? All the papers and tutorial material I have seen works with quantitative data. Does psuedo numbering traits ( 1 for control and 2 for disease sample) make any sense or are there any other options ?
In another case, i have different tissue, the information all I have is that these samples are from different tissue. How do I apply these data to WGCNA?
1 answer
Just encode them as numerical 0 and 1. Or, if you want to do something more elaborate, build a binary logistic regression model:
glm(BinaryTrait ~ Module1, ...)
Kevin
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