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The rice genome was partitioned into a set of coherent classes in a two-step process
First, the epigenomic datasets were used to infer a small set of chromatin states. Then, in a second step, these states were intersected with transcriptomic and annotation data to generate a more nuanced global classification. The first step employed a hidden Markov modeller ChromHMM to binarize chromatin signals and produce alow-resolution map of chromatin states across…