Plot heatmap of missing values

Create a heatmap of the data matrix, indicating which values are missing and observed, respectively.

plotMissingValuesHeatmap(sce, assayMissing)

Arguments

sce

A SummarizedExperiment object.

assayMissing

Character scalar indicating the name of a logical assay of sce representing the missingness pattern. "FALSE" entries should represent observed values, while "TRUE" entries represent missing values.

Value

A ComplexHeatmap object.

Author

Charlotte Soneson

Examples

sce <- importExperiment(system.file("extdata", "mq_example",
                                    "1356_proteinGroups.txt",
                                    package = "einprot"),
                        iColPattern = "^iBAQ\\.")$sce
SummarizedExperiment::assay(sce, "iBAQ")[
    SummarizedExperiment::assay(sce, "iBAQ") == 0] <- NA
SummarizedExperiment::assay(sce, "missing") <-
    is.na(SummarizedExperiment::assay(sce, "iBAQ"))
plotMissingValuesHeatmap(sce, "missing")