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  "Title": "Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)",
  "Author": "Katherine S. Pollard, with Mark J. van der Laan\n<laan@stat.berkeley.edu> and Greg Wall",
  "Maintainer": "Katherine S. Pollard <katherine.pollard@gladstone.ucsf.edu>",
  "Description": "The HOPACH clustering algorithm builds a hierarchical tree\nof clusters by recursively partitioning a data set, while\nordering and possibly collapsing clusters at each level. The\nalgorithm uses the Mean/Median Split Silhouette (MSS) criteria\nto identify the level of the tree with maximally homogeneous\nclusters. It also runs the tree down to produce a final ordered\nlist of the elements. The non-parametric bootstrap allows one\nto estimate the probability that each element belongs to each\ncluster (fuzzy clustering).",
  "License": "GPL (>= 2)",
  "URL": "http://www.stat.berkeley.edu/~laan/, http://docpollard.org/",
  "biocViews": "Clustering",
  "Repository": "https://bioc-release.r-universe.dev",
  "Date/Publication": "2026-04-28 12:30:47 UTC",
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    "author": "A Wokaty <andres.wokaty@sph.cuny.edu>",
    "committer": "A Wokaty <andres.wokaty@sph.cuny.edu>",
    "message": "bump x.y.z version to even y prior to creation of RELEASE_3_23 branch\n",
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    },
    {
      "package": "methods",
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    },
    {
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    },
    {
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    "type": "organization",
    "name": "Bioconductor",
    "description": "Software for the analysis and comprehension of high-throughput genomic data"
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    "extra/citation.json",
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    "manual.pdf"
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  "_cranurl": false,
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    "boothopach",
    "bootmedoids",
    "bootplot",
    "coerce",
    "collap",
    "correlationordering",
    "cutdigits",
    "cutzeros",
    "digits",
    "dissabscor",
    "dissabscosangle",
    "disscor",
    "disscosangle",
    "disseuclid",
    "dissmatrix",
    "dissvector",
    "distancematrix",
    "distancevector",
    "dplot",
    "hdist",
    "hopach",
    "hopach2tree",
    "improveordering",
    "is.hdist",
    "labelstomss",
    "makeoutput",
    "makeTree",
    "msscheck",
    "msscollap",
    "msscomplete",
    "mssinitlevel",
    "mssmulticollap",
    "mssnextlevel",
    "mssrundown",
    "msssplitcluster",
    "newnextlevel",
    "newsplitcluster",
    "nonzeros",
    "orderelements",
    "paircoll",
    "prune",
    "show",
    "silcheck",
    "vdissabscor",
    "vdissabscosangle",
    "vdissabseuclid",
    "vdisscor",
    "vdisscosangle",
    "vdisseuclid",
    "vectmatrix"
  ],
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      "name": "golub",
      "title": "Gene expression dataset from Golub et al. (1999)",
      "object": "golub",
      "file": "golub.RData",
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        "array"
      ],
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      "rows": 3051,
      "table": true,
      "tojson": true
    },
    {
      "name": "golub.cl",
      "title": "Gene expression dataset from Golub et al. (1999)",
      "object": "golub",
      "file": "golub.RData",
      "class": [
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      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "golub.gnames",
      "title": "Gene expression dataset from Golub et al. (1999)",
      "object": "golub",
      "file": "golub.RData",
      "class": [
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      ],
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      "rows": 3051,
      "table": true,
      "tojson": true
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  ],
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    {
      "page": "boot2fuzzy",
      "title": "function to write MapleTree files for viewing bootstrap estimated cluster membership probabilities based on hopach clustering results",
      "topics": [
        "boot2fuzzy"
      ]
    },
    {
      "page": "bootstrap",
      "title": "functions to perform non-parametric bootstrap resampling of hopach clustering results",
      "topics": [
        "boothopach",
        "bootmedoids"
      ]
    },
    {
      "page": "bootplot",
      "title": "function to make a barplot of bootstrap estimated cluster membership probabilities",
      "topics": [
        "bootplot"
      ]
    },
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      "title": "function to compute empirical correlation between distance in a list and distance by a metric",
      "topics": [
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        "improveordering"
      ]
    },
    {
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      "title": "functions to compute pair wise distances between vectors",
      "topics": [
        "dissmatrix",
        "dissvector",
        "distancematrix",
        "distancevector",
        "vectmatrix"
      ]
    },
    {
      "page": "dplot",
      "title": "function to make a pseudo-color image of a distance matrix with the row and column ordering based on HOPACH clustering results.",
      "topics": [
        "dplot"
      ]
    },
    {
      "page": "golub",
      "title": "Gene expression dataset from Golub et al. (1999)",
      "topics": [
        "golub",
        "golub.cl",
        "golub.gnames"
      ]
    },
    {
      "page": "hdist-class",
      "title": "Class \"hdist\" - S4 class to hold distance matrices.",
      "topics": [
        "as.hdist",
        "as.hdist,matrix-method",
        "as.matrix,hdist-method",
        "as.vector,hdist,missing-method",
        "as.vector,hdist-method",
        "coerce,hdist,matrix-method",
        "coerce,matrix,hdist-method",
        "dim,hdist-method",
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        "hdist",
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    },
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      "title": "function to perform HOPACH hierarchical clustering",
      "topics": [
        "hopach"
      ]
    },
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      "title": "function to write MapleTree files for viewing hopach hierarchical clustering results",
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        "silcheck"
      ]
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      "title": "function to write a text file with hopach output",
      "topics": [
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      ]
    },
    {
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      "topics": [
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      ]
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    "cluster",
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      "filename": "hopach.pdf",
      "title": "hopach",
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      "created": "2013-11-01 19:52:49",
      "modified": "2013-11-01 19:52:49",
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