| plotClusterGeneDot {rliger} | R Documentation |
Make dot plot of gene expression in cell groups
Description
This function produces dot plots. Each column represent a group
of cells specified by groupBy, each row is a gene specified by
features. The color of dots reflects mean of normalized expression of
specified genes in each cell group and sizes reflects the percentage of cells
expressing each gene in a group. We utilize
ComplexHeatmap
for simplified management of adding annotation and slicing subplots. This was
inspired by the implementation in
scCustomize.
Usage
plotClusterGeneDot(
object,
features,
groupBy = NULL,
splitBy = NULL,
featureScaleFunc = function(x) log2(10000 * x + 1),
cellIdx = NULL,
legendColorTitle = "Mean\nExpression",
legendSizeTitle = "Percent\nExpressed",
viridisOption = "magma",
verbose = FALSE,
...
)
Arguments
object |
A liger object |
features |
Use a character vector of gene names to make plain dot plot
like a heatmap. Use a data.frame where the first column is gene names and
second column is a grouping variable (e.g. subset |
groupBy |
The names of the columns in |
splitBy |
The names of the columns in |
featureScaleFunc |
A function object applied to normalized data for
scaling the value for better visualization. Default |
cellIdx |
Valid cell subscription. See |
legendColorTitle |
Title for colorbar legend. Default
|
legendSizeTitle |
Title for size legend. Default
|
viridisOption |
Name of available viridis palette. See
|
verbose |
Logical. Whether to show progress information. Mainly when
subsetting data. Default |
... |
Additional theme setting arguments passed to
|
Details
For ..., please notice that arguments colorMat,
sizeMat, featureAnnDF, cellSplitVar, cellLabels
and viridisOption from .complexHeatmapDotPlot are
already occupied by this function internally. A lot of arguments from
Heatmap have also been occupied: matrix,
name, heatmap_legend_param, rect_gp, col, layer_fun, km, border, border_gp,
column_gap, row_gap, cluster_row_slices, cluster_rows, row_title_gp,
row_names_gp, row_split, row_labels, cluster_column_slices, cluster_columns,
column_split, column_title_gp, column_title, column_labels, column_names_gp,
top_annotation.
Value
HeatmapList object.
Examples
# Use character vector of genes
features <- varFeatures(pbmcPlot)[1:10]
plotClusterGeneDot(pbmcPlot, features = features)
# Use data.frame with grouping information, with more tweak on plot
features <- data.frame(features, rep(letters[1:5], 2))
plotClusterGeneDot(pbmcPlot, features = features,
clusterFeature = TRUE, clusterCell = TRUE, maxDotSize = 6)