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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