{
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  "Type": "Package",
  "Title": "Perform Chromatin Segmentation Analysis in R by Calling ChromHMM",
  "Version": "1.18.0",
  "Description": "Chromatin segmentation analysis transforms ChIP-seq data\ninto signals over the genome. The latter represents the\nobserved states in a multivariate Markov model to predict the\nchromatin's underlying states. ChromHMM, written in Java,\nintegrates histone modification datasets to learn the chromatin\nstates de-novo. The goal of this package is to call chromHMM\nfrom within R, capture the output files in an S4 object and\ninterface to other relevant Bioconductor analysis tools. In\naddition, segmenter provides functions to test, select and\nvisualize the output of the segmentation.",
  "Authors@R": "person(\"Mahmoud\", \"Ahmed\",\nemail = \"mahmoud.s.fahmy@students.kasralainy.edu.eg\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-4377-6541\"))",
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  "Repository": "Bioconductor 3.23",
  "Date/Publication": "2026-04-28 12:56:25 UTC",
  "RemoteUrl": "https://github.com/bioc/segmenter",
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  "Packaged": {
    "Date": "2026-11-01 18:51:04 UTC",
    "User": "root"
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  "Author": "Mahmoud Ahmed [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-4377-6541>)",
  "Maintainer": "Mahmoud Ahmed <mahmoud.s.fahmy@students.kasralainy.edu.eg>",
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  "_created": "2026-11-01T18:51:04.000Z",
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        "This package!",
        "Getting started",
        "Segmentation analysis using segmenter",
        "Inputs",
        "Model learning",
        "Output segmentation Object",
        "Comparing models",
        "Interpreting models parameters",
        "Emissions & transitions",
        "Overlap Enrichemnt",
        "Genomic locations enrichment",
        "Segments",
        "Final remarks"
      ],
      "created": "2021-04-19 01:29:27",
      "modified": "2021-06-09 06:31:41",
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