Plot count and feature correlation

Plot the disambiguated counts per cell vs. features (i.e. genes or transcripts) detected.

Usage

plotCountsVsFeatures(object, ...)

# S4 method for SingleCellExperiment
plotCountsVsFeatures(
  object,
  interestingGroups = NULL,
  trendline = FALSE,
  trans = "log2",
  labels = list(title = "Counts vs. features", subtitle = NULL, x = "counts", y =
    "features")
)

Arguments

object

Object.

interestingGroups

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

trendline

logical(1). Include trendline on plot.

trans

character(1). Name of the axis scale transformation to apply.

For more information:

help(topic = "scale_x_continuous", package = "ggplot2")

labels

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

...

Additional arguments.

Value

ggplot.

Details

"Counts" refer to universal molecular identifier (UMI) counts for droplet-based scRNA-seq data.

Note

Updated 2022-03-07.

See also

plotCountsPerCell().

Author

Michael Steinbaugh, Rory Kirchner

Examples

data(SingleCellExperiment_splatter, package = "AcidTest")

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