12Gene set enrichment (GSE) testing enhances the biological interpretation of ChIP-13 seq data and other large sets of genomic regions. Our group has previously 14 introduced two GSE methods for genomic regions: ChIP-Enrich for narrow regions 15 and Broad-Enrich for broad genomic regions, such as histone modifications. Here, 16we introduce new methods and extensions that more appropriately analyze sets of 17 genomic regions with vastly different properties. First, we introduce Poly-Enrich, 18Although every cell in our body contains the same DNA, our cells perform vastly 42 different functions due to differences in how our genes are regulated. Certain 43 regions of the genome are bound by DNA binding proteins (transcription factors), 44 which regulate the expression of nearby genes. After an experiment to identify a 45 large set of these regions, we can then model the association of these regions with 46 various cellular pathways and biological processes. This analysis helps understand 47 the overall biological effect that the binding events have on the cells. For example, if 48 genes relating to apoptosis tend to have the transcription factor, Bcl-2, bind more 49 often nearby, then Bcl-2 is likely to have a vital role in regulating apoptosis. The 50 specifics of how to best perform this analysis is still being researched and depends 51 on properties of the set of genomic regions. Here, we introduce a new, more flexible 52 method that counts the number of occurrences per gene and models that in a 53 sophisticated statistical test, and compare it to a previous method. We show that the 54 optimal method depends on multiple factors, and the new method, Poly-Enrich, 55 allows interesting findings in scenarios where the previous method failed. 56 57