Plot the features with the highest expression values

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Description

Plot the features with the highest expression values

Usage

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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

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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")

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