Fold-change heatmap — get_foldchange

Visualizes log2 fold-change matrices across comparisons with ComplexHeatmap, supporting clustering and annotations. With only a VISTA object, the function will plot the top DE genes across the stored comparisons.

Usage

get_foldchange_heatmap(
  x,
  sample_comparisons = NULL,
  genes = NULL,
  top_n = 10,
  display_id = NULL,
  display_from = NULL,
  display_orgdb = NULL,
  repair_genes = FALSE,
  show_row_names = NULL,
  label_size = 10,
  label_specific_rows = NULL,
  label_specific_rows_gp = grid::gpar(fontsize = 5),
  show_column_names = TRUE,
  cluster_rows = TRUE,
  show_row_dend = TRUE,
  cluster_columns = TRUE,
  kmeans_k = NULL,
  annotate_columns = FALSE,
  column_anno_palette = "Set2",
  color_default = TRUE,
  col = NULL,
  heatmap_name = NULL,
  show_heatmap_legend = TRUE,
  return_type = c("heatmap", "clusters", "both"),
  ...
)

Arguments

x: A VISTA object with stored differential expression results.
sample_comparisons: Optional character vector of comparison names to include. Defaults to all available comparisons.
genes: Optional character vector of gene identifiers to display. When omitted, VISTA selects the top DE genes from each comparison by absolute log2 fold-change.
top_n: Integer number of genes to select per comparison when genes = NULL. Defaults to 10.
display_id: Optional ID/column name to use for plot labels. If supplied
display_from: Optional source ID type for mapping (used when display_id
display_orgdb: Optional OrgDb object used for ID mapping when
repair_genes: Logical; attempt to simplify gene_id strings by removing prefixes.
show_row_names: Logical; draw row (gene) names. When NULL, VISTA turns labels on automatically for auto-selected genes.
label_size: Numeric font size for row names.
label_specific_rows: Optional character vector of genes to highlight with anno_mark().
label_specific_rows_gp: grid::gpar() object controlling highlighted labels.
show_column_names: Logical; draw column labels.
cluster_rows: Logical; cluster rows.
show_row_dend: Logical; display the row dendrogram.
cluster_columns: Logical; cluster columns.
kmeans_k: Optional integer specifying the number of k-means clusters for rows.
annotate_columns: Logical; add annotation bars keyed to the sample grouping column.
column_anno_palette: Qualitative palette name used for column annotations.
color_default: Logical; use the default diverging palette when TRUE. Set to FALSE to supply col.
col: Optional circlize::colorRamp2 color function used when color_default = FALSE.
heatmap_name: Optional legend title.
show_heatmap_legend: Logical; display the heatmap legend.
return_type: "heatmap", "clusters", or "both" selecting the returned value.
...: Additional arguments forwarded to ComplexHeatmap::Heatmap().

Value

An object returned by this function.

A ComplexHeatmap object, a cluster data frame, or a list containing both depending on return_type.

Examples

v <- example_vista()
comp <- names(comparisons(v))[1]
genes <- unique(stats::na.omit(as.character(comparisons(v)[[comp]]$gene_id)))[1:20]
if (requireNamespace('ComplexHeatmap', quietly = TRUE) &&
    requireNamespace('circlize', quietly = TRUE)) {
  hm <- get_foldchange_heatmap(
    v,
    sample_comparisons = comp,
    genes = genes,
    return_type = 'heatmap'
  )
  ComplexHeatmap::draw(hm)
}

v <- example_vista()
if (requireNamespace("ComplexHeatmap", quietly = TRUE) &&
    requireNamespace("circlize", quietly = TRUE)) {
  hm <- get_foldchange_heatmap(v, return_type = "heatmap")
  ComplexHeatmap::draw(hm)
}