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  "Package": "HTGM2D",
  "Version": "1.1.1",
  "Date": "2026-02-03",
  "Title": "Two Dimensional High Throughput 'GoMiner'",
  "Authors@R": "c(\nperson(\"Barry\", \"Zeeberg\", email = \"barryz2013@gmail.com\",\nrole = c(\"aut\", \"cre\")))",
  "Maintainer": "Barry Zeeberg <barryz2013@gmail.com>",
  "Author": "Barry Zeeberg [aut, cre]",
  "LazyData": "true",
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  "Description": "The Gene Ontology (GO) Consortium\n<https://geneontology.org/> organizes genes into hierarchical\ncategories based on biological process (BP), molecular function\n(MF) and cellular component (CC, i.e., subcellular\nlocalization). Tools such as 'GoMiner' (see Zeeberg, B.R.,\nFeng, W., Wang, G. et al. (2003) <doi:10.1186/gb-2003-4-4-r28>)\ncan leverage GO to perform ontological analysis of microarray\nand proteomics studies, typically generating a list of\nsignificant functional categories. Microarray studies are\nusually analyzed with BP, whereas proteomics researchers often\nprefer CC. To capture the benefit of both of those ontologies,\nI developed a two-dimensional version of 'High-Throughput\nGoMiner' ('HTGM2D'). I generate a 2D heat map whose axes are\nany two of BP, MF, or CC, and the value within a picture\nelement of the heat map reflects the Jaccard metric p-value for\nthe number of genes in common for the corresponding pair.",
  "License": "GPL (>= 2)",
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  "Repository": "https://barryzee.r-universe.dev",
  "Date/Publication": "2026-02-03 23:00:32 UTC",
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      "package": "HTGM",
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    "compareGoMinerHTGM2D",
    "HTGM2D",
    "HTGM2Ddriver",
    "Jaccard",
    "JaccardHeatMap"
  ],
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      ],
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    },
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      ]
    },
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      "title": "HTGM2D",
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