I have 150 samples of expression data for two different conditions(or experiments).
can correlation (e.g. cor() in R) be enough to tell relations between random or pre-selected sets of genes?
Also what extra work required/better to do to validate it (only computationally) more or to go further?
NOTE: lets assume we pick only correlations between genes which p-vale <0.005 and cor > 0.70 or < -0.70 , if you also thing another correlation value is better, please tell.
Data type: expression
Conditions samples: A = 90 samples , B = 60 samples , Total = 150
Genes: a set of desired genes
Aim: find correlation between those genes.
I appreciate your comments