# pybedtools.bedtool.BedTool.random_jaccard

BedTool.random_jaccard(other, genome_fn=None, iterations=None, processes=1, _orig_pool=None, shuffle_kwargs=None, jaccard_kwargs=None)

  Computes the naive Jaccard statistic (intersection divided by union).

  Note

  If you don’t need the randomization functionality of this method, you can use the simpler BedTool.jaccard method instead.

  See Favorov et al. (2012) PLoS Comput Biol 8(5): e1002529 for more info on the Jaccard statistic for intersections.

  If `iterations` is None, then do not perform random shufflings.

  If `iterations` is an integer, perform `iterations` random shufflings, each time computing the Jaccard statistic to build an empirical distribution. `genome_fn` will also be needed; optional `processes` will split the iteations across multiple CPUs.

  Returns a tuple of the observed Jaccard statistic and a list of the randomized statistics (which will be an empty list if `iterations` was None).