Unsupervised pattern discovery in human chromatin structure through genomic segmentation.

Nat Methods 2012 Mar 18;9(5):473-6. Epub 2012 Mar 18.

Department of Genome Sciences, University of Washington, Seattle, Washington, USA.

We trained Segway, a dynamic Bayesian network method, simultaneously on chromatin data from multiple experiments, including positions of histone modifications, transcription-factor binding and open chromatin, all derived from a human chronic myeloid leukemia cell line. In an unsupervised fashion, we identified patterns associated with transcription start sites, gene ends, enhancers, transcriptional regulator CTCF-binding regions and repressed regions. Software and genome browser tracks are at http://noble.gs.washington.edu/proj/segway/.

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http://dx.doi.org/10.1038/nmeth.1937DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3340533PMC
March 2012
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