I am looking for recommended methods that perform positional gene enrichment (PGE) analysis in human genomes. What I mean by PGE is to find out, for a given set of genes, if there is any significant positional clustering of these genes along the chromosome or genome.

I think this problem consists of two convoluted tasks: (1) identify positional gene clusters (2) test for the statistical significance of these clusters. Ideally, known biases (e.g. non-random gene density) and multiple testing correction should be accounted for.

Here is one example of a paper that addresses this problem:

De Preter et al. (2008): Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions

I am looking for more recent, stand-alone implementations of such a method (e.g. an R package). A useful software would not necessarily test for positional enrichment of only genes, but could more generally work with any type of feature that has a genomic coordinate (e.g. take a list of known enhancers and identify "super enhancer" regions).

EDIT: From reading the above paper, I realized that the problem is not so much finding significantly enriched regions (this is as simple as performing a hypergeometric test), but to eliminate overlaps. Since I now found out that the authors provide their algorithm as Perl script on their home page, I will start with this method.