I am running a Genome Wide Association test, using a quantitative phenotype. This phenotype can have quite a spread with some extreme outliers, which invalidates the normality assumption for linear regression. I have tried doing various transformation to the phenotype data (log, power, ...) but still end up with a few individuals heavily weighting the results. I currently have my data in PLINK format.
I was wondering if there was a way to run a non parametric test, such as the Mann-Whitney U test?