plotMetaDataHeatmap

plotMetaDataHeatmap

Description

Creates heatmap for genes within aggregated clusters.

Usage

plotMetaDataHeatmap(
  gobject,
  expression_values = c("normalized", "scaled", "custom"),
  metadata_cols = NULL,
  selected_genes = NULL,
  first_meta_col = NULL,
  second_meta_col = NULL,
  show_values = c("zscores", "original", "zscores_rescaled"),
  custom_cluster_order = NULL,
  clus_cor_method = "pearson",
  clus_cluster_method = "complete",
  custom_gene_order = NULL,
  gene_cor_method = "pearson",
  gene_cluster_method = "complete",
  gradient_color = c("blue", "white", "red"),
  gradient_midpoint = 0,
  gradient_limits = NULL,
  x_text_size = 10,
  x_text_angle = 45,
  y_text_size = 10,
  strip_text_size = 8,
  show_plot = NA,
  return_plot = NA,
  save_plot = NA,
  save_param = list(),
  default_save_name = "plotMetaDataHeatmap"
)

Arguments

Argument	Description
gobject	giotto object
expression_values	expression values to use
metadata_cols	annotation columns found in pDataDT(gobject)
selected_genes	subset of genes to use
first_meta_col	if more than 1 metadata column, select the x-axis factor
second_meta_col	if more than 1 metadata column, select the facetting factor
show_values	which values to show on heatmap
custom_cluster_order	custom cluster order (default = NULL)
clus_cor_method	correlation method for clusters
clus_cluster_method	hierarchical cluster method for the clusters
custom_gene_order	custom gene order (default = NULL)
gene_cor_method	correlation method for genes
gene_cluster_method	hierarchical cluster method for the genes
gradient_color	vector with 3 colors for numeric data
gradient_midpoint	midpoint for color gradient
gradient_limits	vector with lower and upper limits
x_text_size	size of x-axis text
x_text_angle	angle of x-axis text
y_text_size	size of y-axis text
strip_text_size	size of strip text
show_plot	show plot
return_plot	return ggplot object
save_plot	directly save the plot [boolean]
save_param	list of saving parameters, see ``showSaveParameters` <#showsaveparameters>`_
default_save_name	default save name

Details

Creates heatmap for the average expression of selected genes in the different annotation/cluster groups.

Calculation of cluster or gene order is done on the provided expression values, but visualization is by default on the z-scores. Other options are the original values or z-scores rescaled per gene (-1 to 1).

Value

ggplot or data.table

Seealso

``plotMetaDataCellsHeatmap` <#plotmetadatacellsheatmap>`_ for numeric cell annotation instead of gene expression.

Examples

data(mini_giotto_single_cell)

# get all genes
all_genes = slot(mini_giotto_single_cell, 'gene_ID')

# look at cell metadata
cell_metadata = pDataDT(mini_giotto_single_cell)

# plot heatmap per cell type, a column name from cell_metadata
plotMetaDataHeatmap(mini_giotto_single_cell,
selected_genes = all_genes[1:10],
metadata_cols = 'cell_types')