Heatmap of Top Differentially Expressed Genes

Creates a heatmap from a normalized count matrix, optionally highlighting the top DE genes.

Usage

bb_heatmap(
  counts,
  de_result = NULL,
  n_genes = 50L,
  annotation_col = NULL,
  scale = c("row", "column", "none"),
  cluster_rows = TRUE,
  cluster_cols = TRUE,
  color_palette = NULL
)

Arguments

counts

Numeric matrix. Normalized count matrix (genes x samples).

de_result

A data.frame with DE results. If provided, the top n_genes by adjusted p-value are shown.

n_genes

Integer. Number of top genes to display. Default 50.

annotation_col

A data.frame for column (sample) annotations. Rownames must match column names of counts.

scale

Character. Scale rows ("row"), columns ("column"), or neither ("none"). Default "row".

cluster_rows

Logical. Cluster rows. Default TRUE.

cluster_cols

Logical. Cluster columns. Default TRUE.

color_palette

Character vector. Colors for the heatmap gradient.

Value

A ggplot2::ggplot object.

Examples

set.seed(42)
counts <- matrix(rpois(500, 100), nrow = 50, ncol = 10,
  dimnames = list(paste0("gene", 1:50), paste0("S", 1:10)))
bb_heatmap(counts, n_genes = 20)