plotHeatmap {scater} | R Documentation |
Create a heatmap of expression values for each cell and specified features in a SingleCellExperiment object.
plotHeatmap(object, features, columns = NULL, exprs_values = "logcounts", center = FALSE, zlim = NULL, symmetric = FALSE, color = NULL, colour_columns_by = NULL, by_exprs_values = exprs_values, by_show_single = FALSE, show_colnames = TRUE, ...)
object |
A SingleCellExperiment object. |
features |
A character vector of row names, a logical vector of integer vector of indices specifying rows of |
columns |
A vector specifying the subset of columns in |
exprs_values |
A string or integer scalar indicating which assay of |
center |
A logical scalar indicating whether each row should have its mean expression centered at zero prior to plotting. |
zlim |
A numeric vector of length 2, specifying the upper and lower bounds for the expression values.
This winsorizes the expression matrix prior to plotting (but after centering, if |
symmetric |
A logical scalar specifying whether the default |
color |
A vector of colours specifying the palette to use for mapping expression values to colours.
This defaults to the default setting in |
colour_columns_by |
A list of values specifying how the columns should be annotated with colours.
Each entry of the list can be of the form described by |
by_exprs_values |
A string or integer scalar specifying which assay to obtain expression values from,
for colouring of column-level data - see |
by_show_single |
Logical scalar specifying whether single-level factors should be used for column-level colouring, see |
show_colnames |
Logical scalar specifying whether column names should be shown, if available in |
... |
Additional arguments to pass to |
Setting center=TRUE
is useful for examining log-fold changes of each cell's expression profile from the average across all cells.
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
example(normalizeSCE) # borrowing the example objects in here. plotHeatmap(example_sce, features=rownames(example_sce)[1:10]) plotHeatmap(example_sce, features=rownames(example_sce)[1:10], center=TRUE, symmetric=TRUE) plotHeatmap(example_sce, features=rownames(example_sce)[1:10], colour_columns_by=c("Mutation_Status", "Cell_Cycle"))