Plot features detected

Visualize the number of features (i.e. genes) detected.

Usage

plotFeaturesDetected

# S4 method for SingleCellExperiment
plotFeaturesDetected(object, ...)

# S4 method for SummarizedExperiment
plotFeaturesDetected(
  object,
  assay = 1L,
  interestingGroups = NULL,
  limit = 0L,
  minCounts = 1L,
  labels = list(title = "Features detected", subtitle = NULL, x = NULL, y = "features"),
  flip = getOption(x = "acid.flip", default = TRUE)
)

Arguments

object

Object.

...

Additional arguments.

assay

vector(1). Assay name or index position.

interestingGroups

character. Groups of interest to use for visualization. Corresponds to factors describing the columns of the object.

limit

numeric(1). Threshold limit.

minCounts

integer(1). Minimum number of counts per feature (i.e. gene).

labels

list. ggplot2 labels. See ggplot2::labs() for details.

flip

logical(1). Flip x and y axes. Recommended for plots containing many samples.

Value

ggplot.

Functions

• plotFeaturesDetected(SingleCellExperiment): Applies aggregateCellsToSamples() calculation to summarize at sample level prior to plotting.
  Passes ... to SummarizedExperiment method.

Note

Updated 2023-08-11.

Examples

data(
    RangedSummarizedExperiment,
    SingleCellExperiment_splatter,
    package = "AcidTest"
)

## SummarizedExperiment ====
object <- RangedSummarizedExperiment
plotFeaturesDetected(object)


## SingleCellExperiment ====
object <- SingleCellExperiment_splatter
plotFeaturesDetected(object)