SingleCellComplexHeatMap (version 0.1.2)

prepare_expression_matrices: Prepare Expression and Percentage Matrices from Seurat DotPlot

Description

Extracts and reshapes expression data from a Seurat DotPlot object into matrices suitable for complex heatmap visualization.

Usage

prepare_expression_matrices(
  seurat_object,
  features,
  group_by = "seurat_clusters",
  idents = NULL,
  split_pattern = "_",
  time_position = 1,
  celltype_start = 2
)

Value

A list containing exp_mat (matrix of scaled expression values), percent_mat (matrix of expression percentages), and dotplot_data (original DotPlot data frame).

Arguments

seurat_object

A Seurat object containing single cell data

features

Character vector of gene names to plot

group_by

Character string specifying the metadata column to group by (default: "seurat_clusters")

idents

Numeric or character vector specifying which cell groups to include (default: NULL for all)

split_pattern

Character string used to split column names for parsing (default: "_")

time_position

Integer indicating position of time point in split names (default: 1)

celltype_start

Integer indicating starting position of cell type in split names (default: 2)

See Also

create_single_cell_complex_heatmap

Examples

# Load a small example Seurat object
data("pbmc_small", package = "SeuratObject")
features <- c("CD3D", "CD79A", "MS4A1")

# Basic usage
matrices <- prepare_expression_matrices(
  seurat_object = pbmc_small,
  features = features,
  group_by = "RNA_snn_res.0.8"
)

# Access the results
expression_matrix <- matrices$exp_mat
percentage_matrix <- matrices$percent_mat