| plotCountsPerFeature | R Documentation | 
Generally, we expect similar count spreads for all genes between samples unless the library sizes or total RNA expression are different.
plotCountsPerFeature(object, ...)
## S4 method for signature 'SingleCellExperiment'
plotCountsPerFeature(object, ...)
## S4 method for signature 'SummarizedExperiment'
plotCountsPerFeature(
  object,
  assay = 1L,
  interestingGroups = NULL,
  geom = c("boxplot", "density", "jitter"),
  trans = c("identity", "log2", "log10"),
  labels = list(title = "Counts per feature", subtitle = NULL, sampleAxis = NULL,
    countAxis = "counts"),
  flip = getOption(x = "acid.flip", default = TRUE),
  minMethod = c("absolute", "perRow")
)
| object | Object. | 
| ... | Additional arguments. | 
| assay | 
 | 
| interestingGroups | 
 | 
| geom | 
 | 
| trans | 
 | 
| labels | 
 | 
| flip | 
 | 
| minMethod | 
 
 | 
ggplot.
plotCountsPerFeature(SingleCellExperiment): Applies aggregateCellsToSamples()
calculation to summarize at sample level prior to plotting.
Passes ... to SummarizedExperiment method.
Updated 2023-08-11.
data(
    RangedSummarizedExperiment,
    SingleCellExperiment_splatter,
    package = "AcidTest"
)
## SummarizedExperiment ====
object <- RangedSummarizedExperiment
plotCountsPerFeature(object, geom = "boxplot")
plotCountsPerFeature(object, geom = "density")
## SingleCellExperiment ====
object <- SingleCellExperiment_splatter
plotCountsPerFeature(object)
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