(the default discretization threshold in ChromHMM). We trained several models with the number of states ranging from 10 states to 25 states. We decided to use a 15-state model (Fig. 4a-f, Extended Data 2b) for all further analyses since it captured all the key interactions between the chromatin marks, and because larger numbers of states did not capture sufficiently distinct interactions. The trained model was then used to compute the posterior probability of each state for each genomic bin in each reference epigenome. The regions were labeled using the state with the maximum posterior probability.
