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  "Date": "2021-05-16",
  "Title": "Model-based gene set analysis",
  "Author": "Sebastian Bauer <mail@sebastianbauer.info>, Julien Gagneur\n<gagneur@genzentrum.lmu.de>",
  "Maintainer": "Sebastian Bauer <mail@sebastianbauer.info>",
  "Description": "Model-based Gene Set Analysis (MGSA) is a Bayesian\nmodeling approach for gene set enrichment. The package mgsa\nimplements MGSA and tools to use MGSA together with the Gene\nOntology.",
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    "extra/citation.html",
    "extra/citation.json",
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  "_realowner": "bioc",
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    "alphaPost",
    "betaMcmcPost",
    "betaPost",
    "itemAnnotations",
    "itemIndices",
    "mgsa",
    "nsamples",
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    "setsMcmcPost",
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    "show",
    "steps",
    "studySetSizeInPopulation",
    "subMgsaSets"
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      "title": "Example GO sets for mgsa",
      "object": "example",
      "file": "example.rda",
      "class": [
        "MgsaSets"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    },
    {
      "name": "example_o",
      "title": "Example objects for mgsa",
      "object": "example",
      "file": "example.rda",
      "class": [
        "character"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
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      "page": "mgsa-package",
      "title": "Model-based gene set analysis",
      "topics": [
        "mgsa-package"
      ]
    },
    {
      "page": "alphaMcmcPost-methods",
      "title": "posterior estimates of the parameter alpha for each MCMC run",
      "topics": [
        "alphaMcmcPost",
        "alphaMcmcPost,MgsaMcmcResults-method"
      ]
    },
    {
      "page": "alphaPost-methods",
      "title": "Posterior for alpha",
      "topics": [
        "alphaPost",
        "alphaPost,MgsaResults-method"
      ]
    },
    {
      "page": "betaMcmcPost-methods",
      "title": "posterior estimates of the parameter beta for each MCMC run",
      "topics": [
        "betaMcmcPost",
        "betaMcmcPost,MgsaMcmcResults-method"
      ]
    },
    {
      "page": "betaPost-methods",
      "title": "Posterior for beta",
      "topics": [
        "betaPost",
        "betaPost,MgsaResults-method"
      ]
    },
    {
      "page": "createMgsaGoSets",
      "title": "This functions takes a 1:1 mapping of go.ids to items and returns a full MgsaGOSets instance. The structure of GO is gathered from GO.db. It is sufficient to specify just the directly asserted mapping (or annotation), i.e., the most specific ones. The true path rule is taken account, that is, if an item is annotated to a term then it will be also annotated to more general terms (some people prefer to say that just the transitive closure is calculated).",
      "topics": [
        "createMgsaGoSets"
      ]
    },
    {
      "page": "example-go",
      "title": "Example GO sets for mgsa",
      "topics": [
        "example-go",
        "example_go"
      ]
    },
    {
      "page": "example-o",
      "title": "Example objects for mgsa",
      "topics": [
        "example-o",
        "example_o"
      ]
    },
    {
      "page": "itemAnnotations-methods",
      "title": "Item annotations of a MgsaSets",
      "topics": [
        "itemAnnotations",
        "itemAnnotations,MgsaSets,character-method",
        "itemAnnotations,MgsaSets,missing-method"
      ]
    },
    {
      "page": "itemIndices-methods",
      "title": "Item indices of a MgsaSets",
      "topics": [
        "itemIndices",
        "itemIndices,MgsaSets,character-method",
        "itemIndices,MgsaSets,numeric-method"
      ]
    },
    {
      "page": "length-methods",
      "title": "Length of a MgsaSets.",
      "topics": [
        "length,MgsaSets-method"
      ]
    },
    {
      "page": "mgsa-methods",
      "title": "Performs an MGSA analysis",
      "topics": [
        "mgsa",
        "mgsa,character,list-method",
        "mgsa,character,MgsaSets-method",
        "mgsa,integer,list-method",
        "mgsa,logical,list-method",
        "mgsa,numeric,list-method"
      ]
    },
    {
      "page": "MgsaGoSets-class",
      "title": "Gene Ontology annotations",
      "topics": [
        "MgsaGoSets-class"
      ]
    },
    {
      "page": "MgsaMcmcResults-class",
      "title": "Instances of this class are used to hold the additional information that was provided by running (possibly multiple times) an MCMC algorithm.",
      "topics": [
        "MgsaMcmcResults-class"
      ]
    },
    {
      "page": "MgsaResults-class",
      "title": "Results of an MGSA analysis",
      "topics": [
        "MgsaResults-class"
      ]
    },
    {
      "page": "MgsaSets-class",
      "title": "Sets of items and their annotations",
      "topics": [
        "MgsaSets-class"
      ]
    },
    {
      "page": "nsamples-methods",
      "title": "How many samples per MCMC run collected",
      "topics": [
        "nsamples",
        "nsamples,MgsaMcmcResults-method"
      ]
    },
    {
      "page": "plot-MgsaResults-method",
      "title": "Plot method for MgsaResults objects",
      "topics": [
        "plot,MgsaResults-method"
      ]
    },
    {
      "page": "pMcmcPost-methods",
      "title": "posterior estimates of the parameter p for each MCMC run",
      "topics": [
        "pMcmcPost",
        "pMcmcPost,MgsaMcmcResults-method"
      ]
    },
    {
      "page": "populationSize-methods",
      "title": "Size of the population of a MgsaResults",
      "topics": [
        "populationSize",
        "populationSize,MgsaResults-method"
      ]
    },
    {
      "page": "pPost-methods",
      "title": "Posterior for beta",
      "topics": [
        "pPost",
        "pPost,MgsaResults-method"
      ]
    },
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      "title": "Read a Gene Ontology annotation file",
      "topics": [
        "readGAF"
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    },
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      "title": "How many MCMC runs",
      "topics": [
        "restarts",
        "restarts,MgsaMcmcResults-method"
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    },
    {
      "page": "setAnnotations-methods",
      "title": "Set annotations of a MgsaSets",
      "topics": [
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        "setAnnotations,MgsaSets,character-method",
        "setAnnotations,MgsaSets,missing-method"
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    },
    {
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      "title": "posterior estimates of the the set marginal probabilities for each MCMC run",
      "topics": [
        "setsMcmcPost",
        "setsMcmcPost,MgsaMcmcResults-method"
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    },
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      "topics": [
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        "setsResults,MgsaResults-method"
      ]
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