plotHighestExprs: Plot the features with the highest expression values

In dynverse/scaterlegacy: Single-cell analysis toolkit for gene expression data in R

Description

Plot the features with the highest expression values

Usage

plotHighestExprs(object, col_by_variable = "total_features", n = 50,
  drop_features = NULL, exprs_values = "counts",
  feature_names_to_plot = NULL)

Arguments

object	an SCESet object containing expression values and experimental information. Must have been appropriately prepared.
col_by_variable	variable name (must be a column name of pData(object)) to be used to assign colours to cell-level values.
n	numeric scalar giving the number of the most expressed features to show. Default value is 50.
drop_features	a character, logical or numeric vector indicating which features (e.g. genes, transcripts) to drop when producing the plot. For example, control genes might be dropped to focus attention on contribution from endogenous rather than synthetic genes.
exprs_values	which slot of the assayData in the object should be used to define expression? Valid options are "counts" (default), "tpm", "fpkm" and "exprs".
feature_names_to_plot	character scalar indicating which column of the featureData slot in the object is to be used for the feature names displayed on the plot. Default is NULL, in which case featureNames(object) is used.

Details

Plot the percentage of counts accounted for by the top n most highly expressed features across the dataset.

Value

a ggplot plot object

Examples

data("sc_example_counts")
data("sc_example_cell_info")
pd <- new("AnnotatedDataFrame", data = sc_example_cell_info)
rownames(pd) <- pd$Cell
example_sceset <- newSCESet(countData = sc_example_counts, phenoData = pd)
example_sceset <- calculateQCMetrics(example_sceset, feature_controls = 1:500)
plotHighestExprs(example_sceset, col_by_variable="total_features")
plotHighestExprs(example_sceset, col_by_variable="Mutation_Status")

dynverse/scaterlegacy documentation built on Feb. 17, 2020, 5:07 a.m.