SingleCellComplexHeatMap (version 0.1.2)

create_gene_annotations: Create Gene Group Annotations for Heatmap Rows

Description

Creates gene grouping annotations and reorders expression matrices based on gene classifications.

Usage

create_gene_annotations(
  exp_mat,
  percent_mat,
  gene_classification,
  color_palette = "Set1",
  sort_within_groups = TRUE,
  annotation_title = "Gene Group"
)

Value

A list containing exp_mat_ordered (reordered expression matrix), percent_mat_ordered (reordered percentage matrix), row_annotation (ComplexHeatmap row annotation object), row_split_factor (factor for row splitting), and annotation_df (data frame with gene annotations).

Arguments

exp_mat

Expression matrix with genes as rows

percent_mat

Percentage matrix with genes as rows

gene_classification

Named list where names are group labels and values are character vectors of gene names

color_palette

Character string specifying palette name OR character vector of colors (default: "Set1")

sort_within_groups

Logical indicating whether to sort genes within each group (default: TRUE)

annotation_title

Character string for annotation title (default: "Gene Group")

See Also

create_single_cell_complex_heatmap, prepare_expression_matrices

Examples

# Load a small example Seurat object
data("pbmc_small", package = "SeuratObject")
features <- c("CD3D", "CD79A", "MS4A1", "GZMK", "CCL5")

# Prepare expression matrices first
matrices <- prepare_expression_matrices(pbmc_small, features, group_by = "RNA_snn_res.0.8")

# Define gene groups
gene_groups <- list(
  "T-cell Markers" = c("CD3D", "GZMK", "CCL5"),
  "B-cell Markers" = c("CD79A", "MS4A1")
)

# Create gene annotations
annotations <- create_gene_annotations(
  exp_mat = matrices$exp_mat,
  percent_mat = matrices$percent_mat,
  gene_classification = gene_groups,
  color_palette = "Set1"
)

# Access results
ordered_exp_mat <- annotations$exp_mat_ordered