I am conducting analyses based on 1000 Genomes paper and I am basically doing the same they did only using my own sets of data. But I am confused if it comes to p value - how do I estimate p value of enrichment(depletion) in such an analyses (the fragment from the 1000 genome paper below describes the analyses but the method for p value is not presented)?

"6.5. Overlap enrichment analysis of SVs versus genomic
elements
Contributed by: Yan Zhang, Mark Gerstein
We performed permutation tests for several functional genomic elements (ED Table 6.5.1., below) intersecting with SVs. We employed a “partial overlap statistic” and an “engulf overlap statistic” respectively in two series of tests, whereby the partial overlap statistic reflects the count of genomic elements (e.g. CDS) showing at least 1 bp overlap with SV intervals (e.g. deletions), and engulf overlap statistic reflects the count of genomic elements that are fully imbedded in at least one SV interval. In the permutation tests, the null distribution (random background) of the overlap measures is calculated from true genomic elements intersecting randomly shuffled SV locations. **We generated 1,000 randomlyshuffled SV sets. Each shuffled set contains the same number of SVs, same proportion of SVs, and same length distribution as the real set. For deletions, we additionally generated 1000 randomly shuffled sets in each allele frequency bin of (0, 0.001], (0.001,0.01], and (0.01,1]. Taking heterogeneity of chromosomes into account, we required that shuffled SVs are still located on the same chromosome, and removed hg19 gap locations. BEDTools88 was used for bed file operation and generating shuffled sets. The enrichment of genomic element-SV overlap is expressed as log2 fold change of the observed overlap statistic versus the mean of the null distribution. Positive (negative) log2 fold change indicates enriched (depleted) genomic element-SV overlap compared to random background. Each pair of genomic element type and SV type was tested individually. Empirical p-value were calculated,** and reported to be significant if p-value <0.01"
source: doi:10.1038/nature15394 RESEARCH SUPPLEMENTARY INFORMATION

Which part of that in particular do you have questions about?