plotMetadata {scater} | R Documentation

## Plot metadata for cells or features

### Description

Plot metadata for cells or features

### Usage

    plotMetadata(object, aesth = aes_string(x = "log10(total_counts)", y =
      "total_features"), shape = NULL, alpha = NULL, size = NULL,
      theme_size = 10)

### Arguments

`object` | a data.frame (or object that can be coerced to such) object containing metadata in columns to plot.
`aesth` | aesthetics function call to pass to ggplot. This function expects at least x and y variables to be supplied. The default is to plot total_features against log10(total_counts).
`shape` | numeric scalar to define the plotting shape. Ignored if shape is included in the `aesth` argument.
`alpha` | numeric scalar (in the interval 0 to 1) to define the alpha level (transparency) of plotted points. Ignored if alpha is included in the `aesth` argument.
`size` | numeric scalar to define the plotting size. Ignored if size is included in the `aesth` argument.
`theme_size` | numeric scalar giving default font size for plotting theme (default is 10)

### Details

Plot cell or feature metadata from an SingleCellExperiment object. If one variable is supplied then a density plot will be returned. If both variables are continuous (numeric) then a scatter plot will be returned. If one variable is discrete and one continuous then a violin plot with jittered points overlaid will be returned. If both variables are discrete then a jitter plot will be produced. The object returned is a ggplot object, so further layers and plotting options (titles, facets, themes etc) can be added.

### Value

a ggplot plot object

### Examples

    data("sc_example_counts")
    data("sc_example_cell_info")
    example_sce <- SingleCellExperiment(
    assays = list(counts = sc_example_counts), colData = sc_example_cell_info)
    example_sce <- calculateQCMetrics(example_sce)
    plotMetadata(colData(example_sce))

[Package scater version 1.6.3 Index]