GeneTonic {GeneTonic} | R Documentation

## GeneTonic

### Description

GeneTonic, main function for the Shiny app

### Usage

    GeneTonic(dds, res_de, res_enrich, annotation_obj, project_id = "")

### Arguments

`dds` | A `DESeqDataSet` object, normally obtained after running your data through the `DESeq2` framework.
`res_de` | A `DESeqResults` object. As for the `dds` parameter, this is also commonly used in the `DESeq2` framework.
`res_enrich` | A `data.frame` object, storing the result of the functional enrichment analysis. Required columns for enjoying the full functionality of `GeneTonic()` include: a gene set identifier (e.g. GeneOntology id, `gs_id`) and its term description (`gs_description`) a numeric value for the significance of the enrichment (`gs_pvalue`) a column named `gs_genes` containing a comma separated vector of the gene names associated to the term, one for each term the number of genes in the geneset of interest detected as differentially expressed (`gs_de_count`), or in the background set of genes (`gs_bg_count`) See `shake_topGOtableResult()` or `shake_enrichResult()` for examples of such formatting helpers
`annotation_obj` | A `data.frame` object, containing two columns, `gene_id` with a set of unambiguous identifiers (e.g. ENSEMBL ids) and `gene_name`, containing e.g. HGNC-based gene symbols. This object can be constructed via the `org.eg.XX.db` packages, e.g. with convenience functions such as `pcaExplorer::get_annotation_orgdb()`.
`project_id` | A character string, which can be considered as an identifier for the set/session, and will be e.g. used in the title of the report created via `happy_hour()`

### Value

A Shiny app object is returned, for interactive data exploration

### Author(s)

Federico Marini

### 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)

    # now everything is in place to launch the app
    if (interactive())
      GeneTonic(dds = dds_macrophage,
                res_de = res_de,
                res_enrich = res_enrich,
                annotation_obj = anno_df,
                project_id = "myexample")

[Package GeneTonic version 1.2.0 Index]