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  "Title": "Gene Set Analysis Using the Gene Set Ordinal Association Test",
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  "Description": "Perform gene set enrichment analyses using the Gene set\nOrdinal Association Test (GOAT) algorithm and visualize your\nresults. Koopmans, F. (2024) <doi:10.1038/s42003-024-06454-5>.",
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    "available_genesets_goatrepo",
    "cluster_genesets",
    "darken_color",
    "download_genesets_goatrepo",
    "download_goat_manuscript_data",
    "filter_genesets",
    "gg_color_hue",
    "go_gene2go",
    "go_obo",
    "goat_logo",
    "goat_print_version",
    "goat_version",
    "hgnc_idmap_table",
    "lighten_color",
    "load_genesets_gmtfile",
    "load_genesets_go_bioconductor",
    "load_genesets_go_fromfile",
    "load_genesets_syngo",
    "minlog10_fixzero",
    "padjust_genesets",
    "partition_genes",
    "plot_heatmap",
    "plot_lollipop",
    "plot_network",
    "plot_volcano",
    "rankscore",
    "rankscore_fixed_order",
    "reduce_genesets",
    "save_genesets",
    "score_geneset_directionality",
    "score_geneset_oddsratio",
    "string_trunc_right",
    "symbol_to_entrez",
    "taxonomy_identifiers",
    "test_genesets",
    "test_genesets_fisherexact",
    "test_genesets_goat_bootstrap",
    "test_genesets_goat_fitfunction",
    "test_genesets_goat_precomputed",
    "test_genesets_gsea",
    "test_genesets_hypergeometric",
    "treemap_data",
    "treemap_plot"
  ],
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      "name": "goat_nulldistributions",
      "title": "Precomputed parameters used by the GOAT algorithm",
      "object": "goat_nulldistributions",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "N",
        "mu",
        "sigma_0",
        "sigma_1",
        "sigma_2",
        "sigma_3",
        "sigma_4",
        "sigma_5",
        "sigma_6",
        "sigma_7",
        "sigma_8",
        "sigma_9",
        "xi_0",
        "xi_1",
        "xi_2",
        "xi_3",
        "xi_4",
        "xi_5",
        "xi_6",
        "xi_7",
        "xi_8",
        "xi_9",
        "xi_10",
        "xi_11"
      ],
      "rows": 19901,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "available_genesets_goatrepo",
      "title": "Discover available geneset collections from the GOAT GitHub repository",
      "topics": [
        "available_genesets_goatrepo"
      ]
    },
    {
      "page": "cluster_genesets",
      "title": "cluster significant genesets from 'test_genesets()' by geneset similarity (separately for each 'geneset source')",
      "topics": [
        "cluster_genesets"
      ]
    },
    {
      "page": "darken_color",
      "title": "naively darken a color by mixing in black",
      "topics": [
        "darken_color"
      ]
    },
    {
      "page": "download_genesets_goatrepo",
      "title": "Download and parse geneset collections from the GOAT GitHub repository",
      "topics": [
        "download_genesets_goatrepo"
      ]
    },
    {
      "page": "download_goat_manuscript_data",
      "title": "Download the datasets that were used in the GOAT manuscript",
      "topics": [
        "download_goat_manuscript_data"
      ]
    },
    {
      "page": "filter_genesets",
      "title": "filter a geneset table; intersect with an array of genes-of-interest then apply cutoffs on min/max genes per geneset",
      "topics": [
        "filter_genesets"
      ]
    },
    {
      "page": "gg_color_hue",
      "title": "generate colours analogous to ggplot's default palette",
      "topics": [
        "gg_color_hue"
      ]
    },
    {
      "page": "go_gene2go",
      "title": "parse gene2go file",
      "topics": [
        "go_gene2go"
      ]
    },
    {
      "page": "go_obo",
      "title": "simple vectorized parsing of GO OBO file without any dependencies (beyond dplyr/tibble/tidyr)",
      "topics": [
        "go_obo"
      ]
    },
    {
      "page": "goat_logo",
      "title": "ASCII logo for this package",
      "topics": [
        "goat_logo"
      ]
    },
    {
      "page": "goat_nulldistributions",
      "title": "Precomputed parameters used by the GOAT algorithm",
      "topics": [
        "goat_nulldistributions"
      ]
    },
    {
      "page": "goat_print_version",
      "title": "Print package version and logo to console",
      "topics": [
        "goat_print_version"
      ]
    },
    {
      "page": "goat_version",
      "title": "Return goat package version as a string",
      "topics": [
        "goat_version"
      ]
    },
    {
      "page": "hgnc_idmap_table",
      "title": "Parse HGNC gene identifier lookup table that was downloaded from genenames.org into a table with HGNC ID, symbol, synonym (NA if unavailable), entrez ID",
      "topics": [
        "hgnc_idmap_table"
      ]
    },
    {
      "page": "lighten_color",
      "title": "naively lighten a color by mixing in white",
      "topics": [
        "lighten_color"
      ]
    },
    {
      "page": "load_genesets_gmtfile",
      "title": "parse genesets in GMT format where gene identifiers are numeric Entrez gene IDs",
      "topics": [
        "load_genesets_gmtfile"
      ]
    },
    {
      "page": "load_genesets_go_bioconductor",
      "title": "Load GO annotations via Bioconductor packages (e.g. org.Hs.eg.db for Human)",
      "topics": [
        "load_genesets_go_bioconductor"
      ]
    },
    {
      "page": "load_genesets_go_fromfile",
      "title": "construct a geneset table from gene2go and OBO files",
      "topics": [
        "load_genesets_go_fromfile"
      ]
    },
    {
      "page": "load_genesets_syngo",
      "title": "parse genesets from the SynGO database",
      "topics": [
        "load_genesets_syngo"
      ]
    },
    {
      "page": "minlog10_fixzero",
      "title": "-log10 transform a vector of p-values, replacing zeros with some limit/threshold",
      "topics": [
        "minlog10_fixzero"
      ]
    },
    {
      "page": "padjust_genesets",
      "title": "Adjust p-values for all genesets, grouped by 'source' then adjust for the number of 'sources'",
      "topics": [
        "padjust_genesets"
      ]
    },
    {
      "page": "partition_genes",
      "title": "Classify genes into 2 groups, e.g. to define significant or topN genes, resulting in a 'signif' column with boolean values",
      "topics": [
        "partition_genes"
      ]
    },
    {
      "page": "plot_heatmap",
      "title": "plot the geneset similarity matrix as a heatmap",
      "topics": [
        "plot_heatmap"
      ]
    },
    {
      "page": "plot_lollipop",
      "title": "Lollipop chart or barplot visualization of geneset enrichment testing results",
      "topics": [
        "plot_lollipop"
      ]
    },
    {
      "page": "plot_network",
      "title": "plot geneset distance matrix as a network",
      "topics": [
        "plot_network"
      ]
    },
    {
      "page": "plot_volcano",
      "title": "For each provided geneset, a volcano plot of all genelist log2fc and p-values with respective geneset constituents highlighted",
      "topics": [
        "plot_volcano"
      ]
    },
    {
      "page": "rankscore",
      "title": "compute rank^2 scores and rescale these between 0~1000 (with further precision captured by decimals)",
      "topics": [
        "rankscore"
      ]
    },
    {
      "page": "rankscore_fixed_order",
      "title": "Gene score array, from low to high scores",
      "topics": [
        "rankscore_fixed_order"
      ]
    },
    {
      "page": "reduce_genesets",
      "title": "Reduce the set of significant genesets to a minimum",
      "topics": [
        "reduce_genesets"
      ]
    },
    {
      "page": "save_genesets",
      "title": "Write a geneset table to file.",
      "topics": [
        "save_genesets"
      ]
    },
    {
      "page": "score_geneset_directionality",
      "title": "Compute a score between -1 and 1 representing the proportion of up- or down-regulated genes for each geneset, weighted by gene effectsizes",
      "topics": [
        "score_geneset_directionality"
      ]
    },
    {
      "page": "score_geneset_oddsratio",
      "title": "Compute odds-ratio for each geneset",
      "topics": [
        "score_geneset_oddsratio"
      ]
    },
    {
      "page": "string_trunc_right",
      "title": "simple string truncation",
      "topics": [
        "string_trunc_right"
      ]
    },
    {
      "page": "symbol_to_entrez",
      "title": "Map the the symbol column in a table to HGNC human gene IDs by matching official gene symbols and synonyms",
      "topics": [
        "symbol_to_entrez"
      ]
    },
    {
      "page": "taxonomy_identifiers",
      "title": "Lookup table for taxonomy identifiers, their names and respective Bioconductor packages",
      "topics": [
        "taxonomy_identifiers"
      ]
    },
    {
      "page": "test_genesets",
      "title": "Perform geneset enrichment testing using any supported method",
      "topics": [
        "test_genesets"
      ]
    },
    {
      "page": "test_genesets_fisherexact",
      "title": "Geneset ORA using Fisher-exact test",
      "topics": [
        "test_genesets_fisherexact"
      ]
    },
    {
      "page": "test_genesets_goat_bootstrap",
      "title": "Naive GOAT variant where we estimate null parameters for each geneset size independently",
      "topics": [
        "test_genesets_goat_bootstrap"
      ]
    },
    {
      "page": "test_genesets_goat_fitfunction",
      "title": "Variant of the main GOAT function 'test_genesets_goat_precomputed' that does not use previously prepared parameters",
      "topics": [
        "test_genesets_goat_fitfunction"
      ]
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      "page": "test_genesets_goat_precomputed",
      "title": "Test geneset enrichment with the Geneset Ordinal Association Test (GOAT) algorithm",
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      "page": "test_genesets_hypergeometric",
      "title": "Geneset ORA using hypergeometric test",
      "topics": [
        "test_genesets_hypergeometric"
      ]
    },
    {
      "page": "treemap_data",
      "title": "Construct tree and treemap data structures from geneset parent/child relations",
      "topics": [
        "treemap_data"
      ]
    },
    {
      "page": "treemap_plot",
      "title": "Plot a treemap",
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