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  "Title": "Bayesian hierarchical model for genome-wide nucleosome\npositioning with high-throughput short-read data (MNase-Seq)",
  "Description": "This package detects nucleosome positions genome-wide from\npaired-end or single-end MNase-Seq reads using a Bayesian\nhierarchical model. Read positions are modelled as a mixture of\nStudent's t-distributions with an informative\nMultinomial-Dirichlet prior on nucleosome locations, and the\nnumber of nucleosomes is estimated with a reversible jump\nMarkov chain Monte Carlo (RJMCMC) algorithm. Functions are\nprovided to split chromosomes into segments for parallel\nanalysis, merge and post-process the predictions, and plot\nnucleosome positions alongside read coverage. This package\nimplements the method described in Samb et al. 2015\n(DOI:10.1515/sagmb-2014-0098).",
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  "Date/Publication": "2026-11-03 22:51:23 UTC",
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  "Author": "Pascal Belleau [aut] (ORCID: <https://orcid.org/0000-0002-0802-1071>),\nRawane Samb [aut],\nAstrid Deschênes [cre, aut] (ORCID:\n<https://orcid.org/0000-0001-7846-6749>),\nKhader Khadraoui [aut],\nLajmi Lakhal-Chaieb [aut],\nArnaud Droit [aut]",
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        "RJMCMCNucleosomes"
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      "title": "Nucleosome Positioning",
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      "headings": [
        "Licensing and citing",
        "Introduction",
        "Installation",
        "Loading the RJMCMCNucleosomes package",
        "RJMCMCNucleosomes analysis",
        "RJMCMCNucleosomes analysis step by step",
        "Split the analyzed region into segments",
        "Run RJMCMCNucleosomes for nucleosome predictions",
        "Regroup all regions",
        "Post-process predictions",
        "Visualization of the predicted nucleosomes",
        "RJMCMCNucleosomes analysis of one chromosome in one step",
        "Acknowledgements",
        "Session info",
        "References"
      ],
      "created": "2016-12-19 23:27:58",
      "modified": "2026-11-03 22:42:51",
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