showClusterHeatmap — showClusterHeatmap • GiottoVisuals

Creates heatmap based on identified clusters

Usage

showClusterHeatmap(
  gobject,
  spat_unit = NULL,
  feat_type = NULL,
  expression_values = c("normalized", "scaled", "custom"),
  feats = "all",
  cluster_column,
  cor = c("pearson", "spearman"),
  distance = "ward.D",
  show_plot = NULL,
  return_plot = NULL,
  save_plot = NULL,
  save_param = list(),
  default_save_name = "showClusterHeatmap",
  ...
)

Arguments

gobject

giotto object

spat_unit

spatial unit (e.g. "cell")

feat_type

feature type (e.g. "rna", "dna", "protein")

expression_values

expression values to use (e.g. "normalized", "scaled", "custom")

feats

vector of features to use, default to 'all'

cluster_column

name of column to use for clusters (e.g. "leiden_clus")

cor

correlation score to calculate distance (e.g. "pearson", "spearman")

distance

distance method to use for hierarchical clustering, default to "ward.D"

show_plot

logical. show plot

return_plot

logical. return ggplot object

save_plot

logical. save the plot

save_param

list of saving parameters, see showSaveParameters

default_save_name

default save name for saving, don't change, change save_name in save_param

...

Arguments passed on to ComplexHeatmap::Heatmap

matrix: A matrix. Either numeric or character. If it is a simple vector, it will be converted to a one-column matrix.
col: A vector of colors if the color mapping is discrete or a color mapping function if the matrix is continuous numbers (should be generated by colorRamp2). If the matrix is continuous, the value can also be a vector of colors so that colors can be interpolated. Pass to ColorMapping. For more details and examples, please refer to https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#colors .
name: Name of the heatmap. By default the heatmap name is used as the title of the heatmap legend.
na_col: Color for NA values.
rect_gp: Graphic parameters for drawing rectangles (for heatmap body). The value should be specified by gpar and fill parameter is ignored.
color_space: The color space in which colors are interpolated. Only used if matrix is numeric and col is a vector of colors. Pass to colorRamp2.
border: Whether draw border. The value can be logical or a string of color.
border_gp: Graphic parameters for the borders. If you want to set different parameters for different heatmap slices, please consider to use decorate_heatmap_body.
cell_fun: Self-defined function to add graphics on each cell. Seven parameters will be passed into this function: j, i, x, y, width, height, fill which are column index, row index in matrix, coordinate of the cell, the width and height of the cell and the filled color. x, y, width and height are all unit objects.
layer_fun: Similar as cell_fun, but is vectorized. Check https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#customize-the-heatmap-body .
jitter: Random shifts added to the matrix. The value can be logical or a single numeric value. It it is TRUE, random values from uniform distribution between 0 and 1e-10 are generated. If it is a numeric value, the range for the uniform distribution is (0, jitter). It is mainly to solve the problem of "Error: node stack overflow" when there are too many identical rows/columns for plotting the dendrograms. ADD: From version 2.5.6, the error of node stack overflow has been fixed, now this argument is ignored.
row_title: Title on the row.
row_title_side: Will the title be put on the left or right of the heatmap?
row_title_gp: Graphic parameters for row title.
row_title_rot: Rotation of row title.
column_title: Title on the column.
column_title_side: Will the title be put on the top or bottom of the heatmap?
column_title_gp: Graphic parameters for column title.
column_title_rot: Rotation of column titles.
cluster_rows: If the value is a logical, it controls whether to make cluster on rows. The value can also be a hclust or a dendrogram which already contains clustering. Check https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#clustering .
cluster_row_slices: If rows are split into slices, whether perform clustering on the slice means?
clustering_distance_rows: It can be a pre-defined character which is in ("euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski", "pearson", "spearman", "kendall"). It can also be a function. If the function has one argument, the input argument should be a matrix and the returned value should be a dist object. If the function has two arguments, the input arguments are two vectors and the function calculates distance between these two vectors.
clustering_method_rows: Method to perform hierarchical clustering, pass to hclust.
row_dend_side: Should the row dendrogram be put on the left or right of the heatmap?
row_dend_width: Width of the row dendrogram, should be a unit object.
show_row_dend: Whether show row dendrogram?
row_dend_gp: Graphic parameters for the dendrogram segments. If users already provide a dendrogram object with edges rendered, this argument will be ignored.
row_dend_reorder: Apply reordering on row dendrograms. The value can be a logical value or a vector which contains weight which is used to reorder rows. The reordering is applied by reorder.dendrogram.
cluster_columns: Whether make cluster on columns? Same settings as cluster_rows.
cluster_column_slices: If columns are split into slices, whether perform clustering on the slice means?
clustering_distance_columns: Same setting as clustering_distance_rows.
clustering_method_columns: Method to perform hierarchical clustering, pass to hclust.
column_dend_side: Should the column dendrogram be put on the top or bottom of the heatmap?
column_dend_height: height of the column cluster, should be a unit object.
show_column_dend: Whether show column dendrogram?
column_dend_gp: Graphic parameters for dendrogram segments. Same settings as row_dend_gp.
column_dend_reorder: Apply reordering on column dendrograms. Same settings as row_dend_reorder.
row_order: Order of rows. Manually setting row order turns off clustering.
column_order: Order of column.
row_labels: Optional row labels which are put as row names in the heatmap.
row_names_side: Should the row names be put on the left or right of the heatmap?
show_row_names: Whether show row names.
row_names_max_width: Maximum width of row names viewport.
row_names_gp: Graphic parameters for row names.
row_names_rot: Rotation of row names.
row_names_centered: Should row names put centered?
column_labels: Optional column labels which are put as column names in the heatmap.
column_names_side: Should the column names be put on the top or bottom of the heatmap?
column_names_max_height: Maximum height of column names viewport.
show_column_names: Whether show column names.
column_names_gp: Graphic parameters for drawing text.
column_names_rot: Rotation of column names.
column_names_centered: Should column names put centered?
top_annotation: A HeatmapAnnotation object.
bottom_annotation: A HeatmapAnnotation object.
left_annotation: It should be specified by rowAnnotation.
right_annotation: it should be specified by rowAnnotation.
km: Apply k-means clustering on rows. If the value is larger than 1, the heatmap will be split by rows according to the k-means clustering. For each row slice, hierarchical clustering is still applied with parameters above.
split: A vector or a data frame by which the rows are split. But if cluster_rows is a clustering object, split can be a single number indicating to split the dendrogram by cutree.
row_km: Same as km.
row_km_repeats: Number of k-means runs to get a consensus k-means clustering. Note if row_km_repeats is set to more than one, the final number of groups might be smaller than row_km, but this might means the original row_km is not a good choice.
row_split: Same as split.
column_km: K-means clustering on columns.
column_km_repeats: Number of k-means runs to get a consensus k-means clustering. Similar as row_km_repeats.
column_split: Split on columns. For heatmap splitting, please refer to https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#heatmap-split .
gap: Gap between row slices if the heatmap is split by rows. The value should be a unit object.
row_gap: Same as gap.
column_gap: Gap between column slices.
show_parent_dend_line: When heatmap is split, whether to add a dashed line to mark parent dendrogram and children dendrograms?
width: Width of the heatmap body.
height: Height of the heatmap body.
heatmap_width: Width of the whole heatmap (including heatmap components)
heatmap_height: Height of the whole heatmap (including heatmap components). Check https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#size-of-the-heatmap .
show_heatmap_legend: Whether show heatmap legend?
heatmap_legend_param: A list contains parameters for the heatmap legends. See color_mapping_legend,ColorMapping-method for all available parameters.
use_raster: Whether render the heatmap body as a raster image. It helps to reduce file size when the matrix is huge. If number of rows or columns is more than 2000, it is by default turned on. Note if cell_fun is set, use_raster is enforced to be FALSE.
raster_device: Graphic device which is used to generate the raster image.
raster_quality: A value larger than 1.
raster_device_param: A list of further parameters for the selected graphic device. For raster image support, please check https://jokergoo.github.io/ComplexHeatmap-reference/book/a-single-heatmap.html#heatmap-as-raster-image .
raster_resize_mat: Whether resize the matrix to let the dimension of the matrix the same as the dimension of the raster image? The value can be logical. If it is TRUE, mean is used to summarize the sub matrix which corresponds to a single pixel. The value can also be a summary function, e.g. max.
raster_by_magick: Whether to use image_resize to scale the image.
raster_magick_filter: Pass to filter argument of image_resize. A character scalar and all possible values are in filter_types. The default is "Lanczos".
post_fun: A function which will be executed after the heatmap list is drawn.

Value

ggplot

Details

Correlation heatmap of selected clusters.

Examples

g <- GiottoData::loadGiottoMini("visium", verbose = FALSE)
showClusterHeatmap(g, cluster_column = "leiden_clus")
#> Error: package 'ComplexHeatmap' is not yet installed
#> 
#>  To install:
#> if(!requireNamespace('BiocManager', quietly = TRUE)) install.packages('BiocManager');
#> BiocManager::install(c("ComplexHeatmap"))