gs_summary_overview {GeneTonic} | R Documentation

## Plots a summary of enrichment results

### Description

Plots a summary of enrichment results for one set

### Usage

    gs_summary_overview(
      res_enrich,
      n_gs = 20,
      p_value_column = "gs_pvalue",
      color_by = "z_score"
    )

### Arguments

`res_enrich` | A `data.frame` object, storing the result of the functional enrichment analysis. See more in the main function, `GeneTonic()`, to check the formatting requirements (a minimal set of columns should be present).
`n_gs` | Integer value, corresponding to the maximal number of gene sets to be displayed
`p_value_column` | Character string, specifying the column of `res_enrich` where the p-value to be represented is specified. Defaults to `gs_pvalue` (it could have other values, in case more than one p-value - or an adjusted p-value - have been specified).
`color_by` | Character, specifying the column of `res_enrich` to be used for coloring the plotted gene sets. Defaults sensibly to `z_score`.

### Value

A `ggplot` object

### See Also

`gs_summary_overview_pair()`, `gs_horizon()`

### Examples

    library("macrophage")
    library("DESeq2")
    library("org.Hs.eg.db")
    library("AnnotationDbi")

    # dds object
    data("gse", package = "macrophage")
    dds_macrophage <- DESeqDataSet(gse, design = ~line + condition)
    rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
    dds_macrophage <- estimateSizeFactors(dds_macrophage)

    # annotation object
    anno_df <- data.frame(
      gene_id = rownames(dds_macrophage),
      gene_name = mapIds(org.Hs.eg.db,
                         keys = rownames(dds_macrophage),
                         column = "SYMBOL",
                         keytype = "ENSEMBL"),
      stringsAsFactors = FALSE,
      row.names = rownames(dds_macrophage)
    )

    # res object
    data(res_de_macrophage, package = "GeneTonic")
    res_de <- res_macrophage_IFNg_vs_naive

    # res_enrich object
    data(res_enrich_macrophage, package = "GeneTonic")
    res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive)
    res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

    gs_summary_overview(res_enrich)

[Package GeneTonic version 1.0.1 Index]