View source: R/plotGroupedHeatmap.R
plotGroupedHeatmap | R Documentation |
Create a heatmap of average expression values for each group of cells and specified features in a SingleCellExperiment object.
plotGroupedHeatmap(
object,
features,
group,
block = NULL,
columns = NULL,
exprs_values = "logcounts",
center = FALSE,
scale = FALSE,
zlim = NULL,
colour = color,
swap_rownames = NULL,
color = NULL,
assay.type = exprs_values,
...
)
object |
A SingleCellExperiment object. |
features |
A character (or factor) vector of row names, a logical vector, or integer vector of indices specifying rows of |
group |
String specifying the field of |
block |
String specifying the field of |
columns |
A vector specifying the subset of columns in |
exprs_values |
Alias to |
center |
A logical scalar indicating whether each feature should have its mean expression (specifically, the mean of averages across all groups) centered at zero prior to plotting. |
scale |
A logical scalar specifying whether each row should have its average expression values scaled to unit variance prior to plotting. |
zlim |
A numeric vector of length 2, specifying the upper and lower bounds for colour mapping of expression values.
Values outside this range are set to the most extreme colour.
If |
colour |
A vector of colours specifying the palette to use for increasing expression.
This defaults to viridis if |
swap_rownames |
Column name of |
color |
Alias to |
assay.type |
A string or integer scalar indicating which assay of |
... |
Additional arguments to pass to |
This function shows the average expression values for each group of cells on a heatmap, as defined using the group
factor.
A per-group visualization can be preferable to a per-cell visualization when dealing with large number of cells or groups with different size.
If block
is also specified, the block effect is regressed out of the averages with correctGroupSummary
prior to visualization.
Setting center=TRUE
is useful for examining log-fold changes of each group's expression profile from the average across all groups.
This avoids issues with the entire row appearing a certain colour because the gene is highly/lowly expressed across all cells.
Setting zlim
preserves the dynamic range of colours in the presence of outliers.
Otherwise, the plot may be dominated by a few genes, which will “flatten” the observed colours for the rest of the heatmap.
A heatmap is produced on the current graphics device.
The output of pheatmap
is invisibly returned.
Aaron Lun
pheatmap
, for the underlying function.
plotHeatmap
, for a per-cell heatmap.
example_sce <- mockSCE()
example_sce <- logNormCounts(example_sce)
example_sce$Group <- paste0(example_sce$Treatment, "+", example_sce$Mutation_Status)
plotGroupedHeatmap(example_sce, features=rownames(example_sce)[1:10],
group="Group")
plotGroupedHeatmap(example_sce, features=rownames(example_sce)[1:10],
group="Group", center=TRUE)
plotGroupedHeatmap(example_sce, features=rownames(example_sce)[1:10],
group="Group", block="Cell_Cycle", center=TRUE)
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