{
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  "Package": "TCC",
  "Type": "Package",
  "Title": "TCC: Differential expression analysis for tag count data with\nrobust normalization strategies",
  "Version": "1.52.0",
  "Author": "Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji\nKadota",
  "Maintainer": "Jianqiang Sun <sun@bitdessin.dev>, Tomoaki Nishiyama\n<tomoakin@staff.kanazawa-u.ac.jp>",
  "Description": "This package provides a series of functions for performing\ndifferential expression analysis from RNA-seq count data using\nrobust normalization strategy (called DEGES). The basic idea of\nDEGES is that potential differentially expressed genes or\ntranscripts (DEGs) among compared samples should be removed\nbefore data normalization to obtain a well-ranked gene list\nwhere true DEGs are top-ranked and non-DEGs are bottom ranked.\nThis can be done by performing a multi-step normalization\nstrategy (called DEGES for DEG elimination strategy). A major\ncharacteristic of TCC is to provide the robust normalization\nmethods for several kinds of count data (two-group with or\nwithout replicates, multi-group/multi-factor, and so on) by\nvirtue of the use of combinations of functions in depended\npackages.",
  "License": "GPL-2",
  "Copyright": "Authors listed above",
  "biocViews": "ImmunoOncology, Sequencing, DifferentialExpression, RNASeq",
  "Config/pak/sysreqs": "zlib1g-dev",
  "Repository": "https://bioc-release.r-universe.dev",
  "Date/Publication": "2026-04-28 12:38:07 UTC",
  "RemoteUrl": "https://github.com/bioc/TCC",
  "RemoteRef": "RELEASE_3_23",
  "RemoteSha": "6c302b88a3f15dc51f6fe4860637f07d7d2d1832",
  "NeedsCompilation": "no",
  "Packaged": {
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    "User": "root"
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  "MD5sum": "09131c5ada486ecad9ce94b273073f05",
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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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    "twitter": "@refracta_",
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    "sequencing",
    "differentialexpression",
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    "type": "organization",
    "name": "Bioconductor",
    "description": "Software for the analysis and comprehension of high-throughput genomic data"
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  "_cranurl": false,
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    "filterLowCountGenes",
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    "getResult",
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    "plotFCPseudocolor",
    "ROKU",
    "show.TCC",
    "simulateReadCounts",
    "TCC",
    "WAD"
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        "array"
      ],
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        "mock2",
        "mock3",
        "hrcc1",
        "hrcc2",
        "hrcc3"
      ],
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      "table": true,
      "tojson": true
    },
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        "G2_rep2",
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      ],
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      "table": true,
      "tojson": true
    },
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      "object": "hypoData_mg",
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      ],
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      "table": true,
      "tojson": true
    },
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      "object": "hypoData_ts",
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      "class": [
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        "array"
      ],
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        "tissue2",
        "tissue3",
        "tissue4",
        "tissue5",
        "tissue6",
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        "tissue8",
        "tissue9",
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      ],
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      "table": true,
      "tojson": true
    },
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      "title": "DNA microarray data set",
      "object": "nakai",
      "file": "nakai.RData",
      "class": [
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        "array"
      ],
      "fields": [
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        "Liver_fed",
        "Liver_fed",
        "Liver_fed",
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  "_help": [
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      "page": "arab",
      "title": "Arabidopsis RNA-Seq data set",
      "topics": [
        "arab"
      ]
    },
    {
      "page": "calcAUCValue",
      "title": "Calculate AUC value from a TCC-class object",
      "topics": [
        "calcAUCValue"
      ]
    },
    {
      "page": "calcNormFactors",
      "title": "Calculate normalization factors",
      "topics": [
        "calcNormFactors",
        "calcNormFactors,DGEList-method",
        "calcNormFactors,TCC-method"
      ]
    },
    {
      "page": "clusterSample",
      "title": "Perform hierarchical clustering for samples from expression data",
      "topics": [
        "clusterSample"
      ]
    },
    {
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      "title": "Estimate degrees of differential expression (DE) for individual genes",
      "topics": [
        "estimateDE"
      ]
    },
    {
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      "topics": [
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      ]
    },
    {
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      "title": "Obtain normalized count data",
      "topics": [
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      ]
    },
    {
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      "topics": [
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      ]
    },
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      "title": "A simulation dataset for comparing two-group tag count data, focusing on RNA-seq",
      "topics": [
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      "topics": [
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      "topics": [
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      ]
    },
    {
      "page": "makeFCMatrix",
      "title": "Generate the fold change matrix for simulating count data",
      "topics": [
        "makeFCMatrix"
      ]
    },
    {
      "page": "nakai",
      "title": "DNA microarray data set",
      "topics": [
        "nakai"
      ]
    },
    {
      "page": "plot.TCC",
      "title": "Plot a log fold-change versus log average expression (so-called M-A plot)",
      "topics": [
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        "plot.TCC"
      ]
    },
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      "topics": [
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      ]
    },
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      "topics": [
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    },
    {
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      "title": "Generate simulation data from negative binomial (NB) distribution",
      "topics": [
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      "topics": [
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        "TCC"
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