  This work proposes Quor, a simple yet effective nonparametric method to
compare independent samples with respect to corresponding quantiles of their
populations. The method is solely based on the order statistics of the samples,
and independence is its only requirement. All computations are performed using
exact distributions with no need for any asymptotic considerations, and yet can
be run using a fast quadratic-time dynamic programming idea. Computational
performance is essential in high-dimensional domains, such as gene expression
data. We describe the approach and discuss on the most important assumptions,
building a parallel with assumptions and properties of widely used techniques
for the same problem. Experiments using real data from biomedical studies are
performed to empirically compare Quor and other methods in a classification
task over a selection of high-dimensional data sets.
