Plot feature (gene) detection saturation — plotFeatureSaturation • bcbioRNASeq

We should observe a linear trend in the number of genes detected with the number of mapped reads, which indicates that the sample input was not overloaded.

Usage

plotFeatureSaturation(object, ...)

# S4 method for bcbioRNASeq
plotFeatureSaturation(
  object,
  interestingGroups = NULL,
  minCounts = 1L,
  perMillion = TRUE,
  trendline = FALSE,
  label = getOption(x = "acid.label", default = FALSE),
  labels = list(title = "Gene saturation", subtitle = NULL, x = "mapped reads", y =
    "gene count")
)

Arguments

object: Object.
interestingGroups: character. Groups of interest to use for visualization. Corresponds to factors describing the columns of the object.
minCounts: integer(1). Minimum number of counts per feature (i.e. gene).
perMillion: logical(1). Display as counts per million.
trendline: logical(1). Include trendline on plot.
label: logical(1). Superimpose sample text labels on the plot.
labels: list. ggplot2 labels. See ggplot2::labs() for details.
...: Additional arguments.

Value

ggplot.

Note

Updated 2023-10-05.

Author

Michael Steinbaugh, Rory Kirchner, Victor Barrera

Examples

data(bcb)

## bcbioRNASeq ====
plotFeatureSaturation(bcb, label = FALSE)

plotFeatureSaturation(bcb, label = TRUE)