Hi,

I have mice microarray time course data. The study design as follows, mice were treated with two different kinds of drugs "a" and "b" for three time points day1, 2, 3, day0 is used as control for both the groups. Further we extracted the RNA from liver and performed microarray. Next we  wanted to do WGCNA analysis. Since we are interested to check the correlation of genes with traits I have created categorical trait but not sure whether it is a right way of doing it or no. So kindly help me with this. I have attached the trait file please have a look.

I want to correlate the conditions with genes is it possible?  My question is can I use it as a trait file???

Regards,

Shalini

I assume your interested in finding clusters of genes changing over time in response to two different treatments relative to baseline.  If that is the case, turn your data frame into a model matrix using just the days column, like so:

traits <- model.matrix(~day, data = traits.df)

Hi,

I was able to design a trait file. But do you think doing Intramodular analysis is logical?  Because unlike the example analysis my traits are binary. My trait file looks like this.

You can certainly use correlation to relate a binary trait to a module eigengene, to genes, and you can relate intra-modular connectivity to gene-trait association statistics (some people may prefer the Student t-test or Mann-Whitney (for binary traits) or perhaps Kruskal-Wallis (for categorical traits with more than 2 levels)).

The problem with your data is that you only have two observations in most groups (I see one group with 3 observations). That's an incredibly low number to do any binary comparisons on. 

Peter