Hello, I have several replicates of a certain variable (at least 5). I would like to compare these distributions to see how similar they are with each other. I have TPMs as a measurement as well as counts (if necessary). They are not normally distributed and I read that the Mann-Whitney U-Test is an appropriate statistical test. I read about this in the illumina replicate manual but it there are no real explanation as to how this applies or can be used. I tried running it with R (using wilcox.test) but I continuously get p-values above 0.05.

I am also unsure as to how to compare multiple replicates, I am currently only comparing two of the 5 replicates. Is there another method I could use to compare these distributions to see their similarities and differences (preferably with a statistical test that gives me some sort of number and p-value)? Or is there a way to improve how I'm running my U-Test?

Thank you!

This is the code I am using to compare my two out of five replicates:

 wilcox.test(TPM~REPLICATE, data=test)

In my data sheet I have one column with all of the TPMs of the two replicates and in the REPLICATE column I have "1" indicating the TPM is from the first replicates and "2" for the second replicate.