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  "Title": "Gene regulator enrichment analysis",
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  "Description": "This package is a pipeline to identify the key gene\nregulators in a biological process, for example in cell\ndifferentiation and in cell development after stimulation.\nThere are four major steps in this pipeline: (1) differential\nexpression analysis; (2) regulator-target network inference;\n(3) enrichment analysis; and (4) regulators scoring and\nranking.",
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  "Collate": "'COEN.R' 'globals.R' 'DEA.R' 'GRN.R' 'data.R'\n'regenrichClasses.R' 'genericMethods.R' 'localUtils.R'\n'plots.R' 'regFET.R' 'regSEA.R' 'regenrich_diffExpr.R'\n'regenrich_enrich.R' 'regenrich_network.R'\n'regenrich_rankScore.R' 'results.R' 'show.R' 'topNet.R'",
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  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-05-09 17:08:07 UTC",
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  "Author": "Weiyang Tao [cre, aut],\nAridaman Pandit [aut]",
  "Maintainer": "Weiyang Tao <weiyangtao1513@gmail.com>",
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      "title": "dimention of `TopNetwork` object",
      "topics": [
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    {
      "page": "Enrich-class",
      "title": "Enrich class",
      "topics": [
        "Enrich-class"
      ]
    },
    {
      "page": "getResultsNames",
      "title": "Inference the name of results of DESeq analysis by a formula (or model matrix) and sample information",
      "topics": [
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      ]
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    {
      "page": "headTailScore",
      "title": "head or tail of Score object",
      "topics": [
        "head,Score-method",
        "tail,Score-method"
      ]
    },
    {
      "page": "Lyme_GSE63085",
      "title": "Example RNAseq dataset [Human]",
      "topics": [
        "Lyme_GSE63085"
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    },
    {
      "page": "newDeaSet",
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    {
      "page": "newTopNetwork",
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      "title": "Plot results of FET/GSEA enrichment analysis",
      "topics": [
        "plot_Enrich",
        "plot_Enrich,RegenrichSet-method"
      ]
    },
    {
      "page": "plotOrders",
      "title": "Compare the orders of two vectors",
      "topics": [
        "plotOrders"
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    },
    {
      "page": "plotRegTarExpr",
      "title": "Plot regulator and its targets expression",
      "topics": [
        "plotRegTarExpr"
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    },
    {
      "page": "plotSoftPower",
      "title": "Plot soft power for WGCNA analysis",
      "topics": [
        "plotSoftPower"
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    {
      "page": "print.Score",
      "title": "Print Score object",
      "topics": [
        "print.Score"
      ]
    },
    {
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      "title": "Differential expression analysis step",
      "topics": [
        "regenrich_diffExpr",
        "regenrich_diffExpr,RegenrichSet-method"
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    },
    {
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      "title": "Enrichment analysis step",
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        "regenrich_enrich,RegenrichSet-method"
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    },
    {
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      "title": "Regulator-target network inference step",
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        "regenrich_network,RegenrichSet-method",
        "regenrich_network<-",
        "regenrich_network<-,RegenrichSet,data.frame-method",
        "regenrich_network<-,RegenrichSet,TopNetwork-method"
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    {
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        "regenrich_rankScore",
        "regenrich_rankScore,RegenrichSet-method"
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    {
      "page": "RegenrichSet",
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        "results_enrich",
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        "results_topNet"
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      "source": "RegEnrich.Rmd",
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      "title": "RegEnrich: an R package for gene regulator enrichment analysis",
      "author": "Weiyang Tao, Aridaman Pandit ",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "A quick example",
        "Including RegEnrich library",
        "Initializing RegenrichSet object",
        "Runing four major steps and obtaining results",
        "RegenrichSet object initialization",
        "The RegenrichSet object",
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        "Enrichment analysis",
        "Fisher's exact test (FET)",
        "Gene set enrichment analysis (GSEA)",
        "Regulator scoring and ranking",
        "Case studies",
        "Case 1: Microarray (single-channel) data",
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        "Reading the data",
        "RegEnrich analysis",
        "Case 2: RNAseq read count data",
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        "References"
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      "modified": "2020-07-21 13:47:18",
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