Traditional approaches to summarizing the similarity between two sets of genomic intervals are based upon the number or proportion of intersecting intervals. However, such measures are largely blind to spatial correlations between the two sets where, despite consistent spacing or proximity, intersections are rare (for example, enhancers and transcription start sites rarely overlap, yet they are much closer to one another than two sets of random intervals). Favorov et al  proposed a relative distance metric that describes distribution of relative distances between each interval in one set and the two closest intervals in another set. If there is no spatial correlation between the two sets, one would expect the relative distances to be uniformly distributed among the relative distances ranging from 0 to 0.5. If, however, the intervals tend to be much closer than expected by chance, the distribution of observed relative distances would be shifted towards low relative distance values.
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