I am trying to perform Kruskal-Wallis test on RNA-Seq data, which has 20 genes of interest and looks like following:
Gene_id Con_1 Con_2 Con_3 Mut_1 Mut_2 Mut_3 Gene_001 -0.173575646 0.519571535 -5.87735812 2.023648932 1.94668789 1.56102541 Gene_002 -0.185999458 -0.118197772 0.129667462 -0.071623581 0.249618688 -0.003465339 Gene_003 3.486046831 -5.693834334 -1.088664148 0.009948141 3.682020477 -0.395516967
Only the first 3 rows are shown to demonstrate what data looks like. The first column is the gene id and columns 2-4 (WT) are three independent biological replicates of control and columns (5-7) are three independent biological replicates of mutations (Mut) as treatment. The data has been log transformed.
Here are my questions:
Q #1. A couple of posts on this forum suggested to transpose and/or melt data on R. How exactly should I do it?
Q #2. Given control and treatments have three replicates each, how the Kruskal-Wallis test should be performed? Should I average three replicates for control and average for mutation? In other words, what would be the best way to perform the Kruskal-Wallis test with RNA-seq data where it has replicates?
Any help/suggestion would be appreciated. Thank you.