I have a dataset (human microarray) with a total of 36 samples; 9 subjects x 2 conditions x 2 tissue types.
I want to examine the relationship in expression between the two tissue types under both conditions. I've used co-inertia analysis to get an idea of the overall similarity, along with a very basic correlation of average gene expression across all arrays between the two tissues. I've also started using CCA to look at correlation between variables.
What I'd like to do is find a subset of genes that is highly correlated (or more specifically, shows greatest covariance) between the two tissue types and also a subset that has least covariance.
What would be the best approach for this?