gene_plot {GeneTonic} | R Documentation

## Plot expression values for a gene

### Description

Plot expression values (e.g. normalized counts) for a gene of interest, grouped by experimental group(s) of interest

### Usage

    gene_plot(
      dds,
      gene,
      intgroup = "condition",
      assay = "counts",
      annotation_obj = NULL,
      normalized = TRUE,
      transform = TRUE,
      labels_repel = TRUE,
      plot_type = "auto",
      return_data = FALSE
    )

### Arguments

`dds` | A `DESeqDataSet` object, normally obtained after running your data through the `DESeq2` framework.
`gene` | Character, specifies the identifier of the feature (gene) to be plotted
`intgroup` | A character vector of names in `colData(dds)` to use for grouping. Note: the vector components should be categorical variables.
`assay` | Character, specifies with assay of the `dds` object to use for reading out the expression values. Defaults to "counts".
`annotation_obj` | A `data.frame` object with the feature annotation information, with at least two columns, `gene_id` and `gene_name`.
`normalized` | Logical value, whether the expression values should be normalized by their size factor. Defaults to TRUE, applies when `assay` is "counts"
`transform` | Logical value, corresponding whether to have log scale y-axis or not. Defaults to TRUE.
`labels_repel` | Logical value. Whether to use `ggrepel`'s functions to place labels; defaults to TRUE
`plot_type` | Character, one of "auto", "jitteronly", "boxplot", "violin", or "sina". Defines the type of `geom_` to be used for plotting. Defaults to `auto`, which in turn chooses one of the layers according to the number of samples in the smallest group defined via `intgroup`
`return_data` | Logical, whether the function should just return the data.frame of expression values and covariates for custom plotting. Defaults to FALSE.

### Details

The result of this function can be fed directly to `plotly::ggplotly()` for interactive visualization, instead of the static `ggplot` viz.

### Value

A `ggplot` object

### Examples

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

    # 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)
    )

    gene_plot(dds_macrophage,
              gene = "ENSG00000125347",
              intgroup = "condition",
              annotation_obj = anno_df)

[Package GeneTonic version 1.2.0 Index]