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

plotFeaturesDetected

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

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

Arguments

object

Object.

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).

fill

ggproto/ScaleDiscrete. Desired ggplot2 fill scale. Must supply discrete values. When set to NULL, the default ggplot2 color palette will be used. If manual color definitions are desired, we recommend using ggplot2::scale_fill_manual().

To set the discrete fill palette globally, use:

options(acid.fill.discrete = ggplot2::scale_fill_viridis_d())
labels

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

flip

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

...

Additional arguments.

Value

ggplot.

Methods (by class)

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

Note

Updated 2019-09-16.

Examples

data( RangedSummarizedExperiment, SingleCellExperiment, package = "acidtest" ) ## SummarizedExperiment ==== object <- RangedSummarizedExperiment plotFeaturesDetected(object)
## SingleCellExperiment ==== object <- SingleCellExperiment plotFeaturesDetected(object)
#> Aggregating counts using 'sum()'.