{
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  "Title": "Generate Heatmaps Based on Partitioning Around Medoids (PAM)",
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  "Date": "2021-08-24",
  "Author": "Vidal Fey [aut, cre], Henri Sara [aut]",
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  "Maintainer": "Vidal Fey <vidal.fey@gmail.com>",
  "Description": "Data are partitioned (clustered) into k clusters \"around\nmedoids\", which is a more robust version of K-means implemented\nin the function pam() in the 'cluster' package. The PAM\nalgorithm is described in Kaufman and Rousseeuw (1990)\n<doi:10.1002/9780470316801>. Please refer to the pam() function\ndocumentation for more references. Clustered data is plotted as\na split heatmap allowing visualisation of representative\n\"group-clusters\" (medoids) in the data as separated fractions\nof the graph while those \"sub-clusters\" are visualised as a\ntraditional heatmap based on hierarchical clustering.",
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      "title": "Main function to produce a heatmap using PAM clustering.",
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    {
      "page": "PAMhm",
      "title": "Generate Heatmaps Based on Partioning Around Medoids (PAM)",
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        "PAMhm"
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        "Description",
        "Installation",
        "CRAN",
        "Latest development version",
        "Usage",
        "A simple example",
        "A plot with more than one cluster number",
        "A trimmed plot",
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        "Plot with default (winzorized) trimming",
        "Median-centering",
        "Row-wise centering without trimming",
        "References"
      ],
      "created": "2021-09-06 06:50:02",
      "modified": "2021-09-06 06:50:02",
      "commits": 1
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