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Unsupervised pattern discovery in human chromatin structure through genomic segmentation

Nature Methods volume 9, pages 473–476 (2012)Cite this article

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Abstract

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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Figure 1: Heat map of discovered Gaussian parameters in an unsupervised 25-label segmentation trained on 31 tracks of histone modification, transcription-factor binding and open chromatin signal data in 1% of the human genome.
Figure 2: Gene structure in Segway labels.

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Acknowledgements

We thank P.J. Collins for assistance with transient transfection assays, S. Djebali for processing data, C.E. Grant for motif analysis, A. Kundaje for helpful suggestions, and members of the ENCODE Project Consortium, the ENCODE Data Coordination Center and the US National Human Genome Research Institute for providing early public access to the unpublished data used in this work. This work used data produced in the laboratories of B.E. Bernstein (Broad Institute of the Massachusetts Institute of Technology and Harvard University), M.P. Snyder (Stanford University), R.M. Myers (HudsonAlpha Institute for Biotechnology), P.J. Farnham (University of Southern California), V.R. Iyer (University of Texas at Austin), G.E. Crawford (Duke University), J.D. Lieb and T.S. Furey (University of North Carolina at Chapel Hill), J.A. Stamatoyannopoulos (University of Washington), P. Carninci (RIKEN), T.R. Gingeras (Cold Spring Harbor Laboratory), and A. Sidow (Stanford University). This publication was made possible by grants 004695, 004561 and 006259 from National Human Genome Research Institute.

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Author notes

  1. Orion J Buske

    Present address: Present address: Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.,

Authors and Affiliations

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

    Michael M Hoffman, Orion J Buske & William Stafford Noble

  2. Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA

    Jie Wang & Zhiping Weng

  3. Department of Electrical Engineering, University of Washington, Seattle, Washington, USA

    Jeff A Bilmes

  4. Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA

    William Stafford Noble

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  1. Michael M Hoffman
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  5. Jeff A Bilmes
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Contributions

M.M.H., W.S.N. and J.A.B. conceived of the project; M.M.H., W.S.N. and Z.W. designed computational and biological experiments. M.M.H., J.A.B., O.J.B. and J.W. developed software used in this work; M.M.H., O.J.B. and J.W. conducted computational experiments and analyzed data; and M.M.H., W.S.N., Z.W., J.A.B., O.J.B. and J.W. wrote the manuscript.

Corresponding author

Correspondence to William Stafford Noble.

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The authors declare no competing financial interests.

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Supplementary Figures 1–11, Supplementary Tables 1–4, Supplementary Results, Supplementary Discussion (PDF 1780 kb)

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Hoffman, M., Buske, O., Wang, J. et al. Unsupervised pattern discovery in human chromatin structure through genomic segmentation. Nat Methods 9, 473–476 (2012). https://doi.org/10.1038/nmeth.1937

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