Hi, 
 
I am performing a shuffle of reads from a ChIP-Seq experiment over some features in the genome and since I do not know the original distributions I am trying to perform an observed to expected calculation to see which features are enriched. Boiled down this means I have counts of reads mapping to feature x, then I perform a shuffle of the reads over the entire genome, count those and then calculate the count of how many reads mapped to feature x by chance. Unfortunately, I am not quite sure on how to get a p-value from this.  
 
I hope you can help me with this. 
Thank you very much!
 
This looks like a permutation test. Your p-value would be the number of times the permutations give more reads mapping to the feature under consideration divided by the number of permutations. 
And if you're doing multiple tests (i.e. testing many features), you should do a correction for multiple testing. Bonferroni is fine but too conservative, you should prefer FDR.