gs_mds {GeneTonic} | R Documentation

## Multi Dimensional Scaling plot for gene sets

### Description

Multi Dimensional Scaling plot for gene sets, extracted from a `res_enrich` object

### Usage

    gs_mds(
      res_enrich,
      res_de,
      annotation_obj,
      gtl = NULL,
      n_gs = nrow(res_enrich),
      gs_ids = NULL,
      similarity_measure = "kappa_matrix",
      mds_k = 2,
      mds_labels = 0,
      mds_colorby = "z_score",
      gs_labels = NULL,
      plot_title = NULL,
      return_data = FALSE
    )

### 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).
`res_de` | A `DESeqResults` object.
`annotation_obj` | A `data.frame` object with the feature annotation information, with at least two columns, `gene_id` and `gene_name`.
`gtl` | A `GeneTonic`-list object, containing in its slots the arguments specified above: `dds`, `res_de`, `res_enrich`, and `annotation_obj` - the names of the list must be specified following the content they are expecting
`n_gs` | Integer value, corresponding to the maximal number of gene sets to be included (from the top ranked ones). Defaults to the number of rows of `res_enrich`
`gs_ids` | Character vector, containing a subset of `gs_id` as they are available in `res_enrich`. Lists the gene sets to be included, additionally to the ones specified via `n_gs`. Defaults to NULL.
`similarity_measure` | Character, currently defaults to `kappa_matrix`, to specify how to compute the similarity measure between gene sets
`mds_k` | Integer value, number of dimensions to compute in the multi dimensional scaling procedure
`mds_labels` | Integer, defines the number of labels to be plotted on top of the scatter plot for the provided gene sets.
`mds_colorby` | Character specifying the column of `res_enrich` to be used for coloring the plotted gene sets. Defaults sensibly to `z_score`.
`gs_labels` | Character vector, containing a subset of `gs_id` as they are available in `res_enrich`. Lists the gene sets to be labeled.
`plot_title` | Character string, used as title for the plot. If left `NULL`, it defaults to a general description of the plot and of the DE contrast
`return_data` | Logical, whether the function should just return the data.frame of the MDS coordinates, related to the original `res_enrich` object. Defaults to FALSE.

### Value

A `ggplot` object

### See Also

`create_kappa_matrix()` is used to calculate the similarity between gene sets

### 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_mds(res_enrich,
      res_de,
      anno_df,
      n_gs = 200,
      mds_labels = 10
    )

[Package GeneTonic version 1.4.1 Index]