Unsupervised pattern discovery in human chromatin structure through genomic segmentation

Nat Methods. 2012 Mar 18;9(5):473-6. doi: 10.1038/nmeth.1937.


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/.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Bayes Theorem
  • Chromatin / genetics
  • Chromatin / physiology*
  • Genome, Human*
  • Histones / genetics
  • Histones / physiology*
  • Humans
  • K562 Cells
  • Molecular Sequence Data
  • Promoter Regions, Genetic
  • Regulatory Sequences, Nucleic Acid
  • Transcription Factors / genetics
  • Transcription Factors / physiology
  • Transcription Initiation Site*


  • Chromatin
  • Histones
  • Transcription Factors