plotHighestExprs {scater} | R Documentation |
Plot the features with the highest expression values
plotHighestExprs(object, col_by_variable = "total_features", n = 50, drop_features = NULL, exprs_values = "counts", feature_names_to_plot = NULL)
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 colData(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 |
feature_names_to_plot |
character scalar indicating which column of the
featureData slot in the |
Plot the percentage of counts accounted for by the top n most highly expressed features across the dataset.
a ggplot plot object
data("sc_example_counts") data("sc_example_cell_info") example_sce <- SingleCellExperiment( assays = list(counts = sc_example_counts), colData = sc_example_cell_info) example_sce <- calculateQCMetrics(example_sce, feature_controls = list(set1 = 1:500)) plotHighestExprs(example_sce, col_by_variable="total_features") plotHighestExprs(example_sce, col_by_variable="Mutation_Status") plotQC(example_sce, type = "highest-express")