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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

plotGeneSaturation(object, ...)

# S4 method for bcbioRNASeq
plotGeneSaturation(
  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 2022-05-09.

Author

Michael Steinbaugh, Rory Kirchner, Victor Barrera

Examples

data(bcb)

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

plotGeneSaturation(bcb, label = TRUE)