binary phenotype or discrete traits in wgcna analysis

Question

[l0o0]

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?

[O.rka]

Any luck or progress on this?

Answer 1

[Kevin Blighe]

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