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Description
Chromatin state discovery and characterization (example)
ChromHMM is software for learning and characterizing chromatin states.
ChromHMM can integrate multiple chromatin datasets such as ChIP-seq data of
various histone modifications to discover de novo the major re-occuring
combinatorial and spatial patterns of marks. ChromHMM is based on a
multivariate Hidden Markov Model that explicitly models the presence or
absence of each chromatin mark. The resulting model can then be used to
systematically annotate a genome in one or more cell types. By automatically
computing state enrichments for large-scale functional and annotation datasets
ChromHMM facilitates the biological characterization of each state. ChromHMM
also produces files with genome-wide maps of chromatin state annotations that
can be directly visualized in a genome browser.
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This package provides example to work with ChromHMM.
