To investigate the tissue-specific disease connections in the network, we used annotations from the 15 chromatin state models available on the Roadmap Epigenomics website to assign chromatin states to different tissues.26 Using posterior probability, we assigned the most probable chromatin states for 127 different tissues, defined via posterior probability, to every 200 base-pair window across the genome. We also consolidated the 127 different tissues into 27 functional groups of tissues; for example, we used four different adipose tissues for the chromatin-state prediction, but we consolidated these into one group called “adipose tissue.”27 To calculate the most probable chromatin state for each functional tissue category, we averaged the posterior probabilities.27 The chromatin-state prediction provides the annotations for the most active to the most quiescent regions of the non-coding genome. In this study, we focused on the active regulatory elements, such as enhancers, promoters, and active transcription start site (TSS); as a proof-of-concept, we only analyzed enhancer-state annotations.