A principal component analysis of a correlation matrix treats all variables as equally important. A principal component analysis of a covariance matrix gives more weight to variables with larger ...

Finally, documentation is your friend. If you must use global variables, make sure they are explained in a comment, especially if you considered an alternative approach but ended up dismissing it.