Imagine I have 200 samples, and for each, I have expression values of 500 genes (so it's a matrix with 500 rows and 200 columns). Expression values are normalized, it’s TPM. I need to compute a distance between the samples. What is the better way of doing it? Should I take log(TPM+1), then scale with z-transformation, and do Euclidean distance? Or there is a better way? And should I scale rows (calculate z-scores within genes but across samples) or columns?