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  "Title": "'C++' Implementations of Functional Enrichment Analysis",
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  "Authors@R": "person(given = \"Guangchuang\", family = \"Yu\",\nemail = \"guangchuangyu@gmail.com\", role  = c(\"aut\", \"cre\"))",
  "Maintainer": "Guangchuang Yu <guangchuangyu@gmail.com>",
  "Description": "Fast implementations of functional enrichment analysis\nmethods using 'C++' via 'Rcpp'. Currently provides\nOver-Representation Analysis (ORA), Gene Set Enrichment\nAnalysis (GSEA), Weighted Enrichment Analysis for ORA and GSEA,\nNetwork-based Set Enrichment Analysis (NSEA), multi-layer\nnetwork-based enrichment, and multi-omics integration\nworkflows. Additional features include early fusion at the\nfeature level, late fusion at the pathway level, multi-omics\ncontribution tracing, topology-aware explanation helpers,\nBayesian term selection, and extremely fast Random Walk with\nRestart (RWR) using 'RcppEigen'. The enrichment methods build\non GSEA by Subramanian et al. (2005)\n<doi:10.1073/pnas.0506580102>, the multilevel strategy derived\nfrom 'fgsea' by Korotkevich et al. (2021) <doi:10.1101/060012>,\nand network-based enrichment ideas described by Glaab et al.\n(2012) <doi:10.1093/bioinformatics/bts389>.",
  "License": "Artistic-2.0",
  "Encoding": "UTF-8",
  "URL": "https://yulab-smu.top/biomedical-knowledge-mining-book/",
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    "bayes_enrich",
    "bayes_summary",
    "classify_omics_pattern",
    "collapse_multilayer_scores",
    "EXTID2NAME",
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    "geneID",
    "geneInCategory",
    "get_mnsea_contribution",
    "get_omics_contribution",
    "gsea",
    "gsea_gson",
    "gseaScores",
    "gsfilter",
    "harmonize_ids",
    "mnsea",
    "mnsea_gson",
    "nsea",
    "nsea_gson",
    "ora",
    "ora_gson",
    "prepare_multilayer_network",
    "prepare_network",
    "propagate_multilayer",
    "select_features_for_ora",
    "setReadable",
    "show",
    "summary"
  ],
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    {
      "page": "aggregate_enrichment",
      "title": "Aggregate multiple enrichment results (Late Fusion)",
      "topics": [
        "aggregate_enrichment"
      ]
    },
    {
      "page": "aggregate_omics",
      "title": "Aggregate multi-omics gene/protein-level statistics",
      "topics": [
        "aggregate_omics"
      ]
    },
    {
      "page": "as_enrichResult",
      "title": "as_enrichResult",
      "topics": [
        "as_enrichResult",
        "as_enrichResult.default"
      ]
    },
    {
      "page": "as_gseaResult",
      "title": "as_gseaResult",
      "topics": [
        "as_gseaResult",
        "as_gseaResult.default"
      ]
    },
    {
      "page": "bayes_enrich",
      "title": "Bayesian term selection for enrichment results",
      "topics": [
        "bayes_enrich"
      ]
    },
    {
      "page": "bayes_summary",
      "title": "Summarize Bayesian enrichment results",
      "topics": [
        "bayes_summary"
      ]
    },
    {
      "page": "classify_omics_pattern",
      "title": "Classify pathway-level multi-omics patterns",
      "topics": [
        "classify_omics_pattern"
      ]
    },
    {
      "page": "collapse_multilayer_scores",
      "title": "Collapse multi-layer diffusion scores",
      "topics": [
        "collapse_multilayer_scores"
      ]
    },
    {
      "page": "compareClusterResult-class",
      "title": "Class \"compareClusterResult\" This class represents the comparison result of gene clusters by GO categories at specific level or GO enrichment analysis.",
      "topics": [
        "compareClusterResult-class",
        "plot,compareClusterResult-method",
        "show,compareClusterResult-method",
        "summary,compareClusterResult-method"
      ]
    },
    {
      "page": "enrichResult-class",
      "title": "Class \"enrichResult\" This class represents the result of enrichment analysis.",
      "topics": [
        "enrichResult-class",
        "show,enrichResult-method",
        "summary,enrichResult-method"
      ]
    },
    {
      "page": "EXTID2NAME",
      "title": "EXTID2NAME",
      "topics": [
        "EXTID2NAME"
      ]
    },
    {
      "page": "extract_mnsea_subnetwork",
      "title": "Extract pathway subnetwork data from a 'mnseaResult'",
      "topics": [
        "extract_mnsea_subnetwork"
      ]
    },
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      "title": "geneID generic",
      "topics": [
        "geneID"
      ]
    },
    {
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      "title": "geneInCategory generic",
      "topics": [
        "geneInCategory"
      ]
    },
    {
      "page": "get_mnsea_contribution",
      "title": "Get cached contribution tables from a 'mnseaResult'",
      "topics": [
        "get_mnsea_contribution"
      ]
    },
    {
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      "title": "Get gene-level omics contribution for a specific pathway",
      "topics": [
        "get_omics_contribution"
      ]
    },
    {
      "page": "gsea",
      "title": "Gene Set Enrichment Analysis (GSEA)",
      "topics": [
        "gsea"
      ]
    },
    {
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      "title": "gsea_gson",
      "topics": [
        "gsea_gson"
      ]
    },
    {
      "page": "gseaResult-class",
      "title": "Class \"gseaResult\" This class represents the result of GSEA analysis",
      "topics": [
        "gseahResult-class",
        "gseaResult-class",
        "show,gseaResult-method",
        "summary,gseaResult-method"
      ]
    },
    {
      "page": "gseaScores",
      "title": "Calculate GSEA Running Enrichment Scores",
      "topics": [
        "gseaScores"
      ]
    },
    {
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      "title": "gsfilter",
      "topics": [
        "gsfilter"
      ]
    },
    {
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      "title": "Harmonize feature IDs to a target space",
      "topics": [
        "harmonize_ids"
      ]
    },
    {
      "page": "mnsea",
      "title": "Multi-layer Network-based Gene Set Enrichment Analysis",
      "topics": [
        "mnsea"
      ]
    },
    {
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      "title": "Multi-layer NSEA using a GSON object",
      "topics": [
        "mnsea_gson"
      ]
    },
    {
      "page": "mnseaResult-class",
      "title": "Class \"mnseaResult\" This class represents the result of multi-layer Network-based Set Enrichment Analysis.",
      "topics": [
        "mnseaResult-class"
      ]
    },
    {
      "page": "nsea",
      "title": "Network-based Gene Set Enrichment Analysis",
      "topics": [
        "nsea"
      ]
    },
    {
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      "title": "Network-based GSEA using a GSON object",
      "topics": [
        "nsea_gson"
      ]
    },
    {
      "page": "nseaResult-class",
      "title": "Class \"nseaResult\" This class represents the result of Network-based Set Enrichment Analysis (NSEA).",
      "topics": [
        "nseaResult-class"
      ]
    },
    {
      "page": "ora",
      "title": "Over-Representation Analysis (ORA)",
      "topics": [
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        "show,mnseaResult-method",
        "show,nseaResult-method"
      ]
    },
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