Skip to contents

Plot pathway-specific expression heatmaps from enrichment output

get_pathway_heatmap.Rd

This wrapper bridges enrichment results and expression heatmaps. It extracts genes from selected pathways (via get_pathway_genes()), maps them to the VISTA feature IDs, and forwards to get_expression_heatmap().

Usage

get_pathway_heatmap(
  vista_obj,
  enrichment,
  samples,
  pathways = NULL,
  top_n = 5,
  pathway_column = c("Description", "ID"),
  gene_column = c("auto", "geneID", "core_enrichment"),
  gene_sep = "/",
  gene_mode = c("union", "intersection"),
  gene_id_column = NULL,
  max_genes = NULL,
  return_type = c("heatmap", "both", "genes"),
  ...
)

Arguments

vista_obj

A VISTA object.

enrichment

An enrichResult/gseaResult, or a list with element enrich as returned by get_*_enrichment() helpers.

samples

Character vector of group labels to include (same semantics as get_expression_heatmap()).

pathways

Optional pathway names to include. When NULL, top pathways are selected using top_n.

top_n

Number of top pathways used when pathways = NULL. Default: 5.

pathway_column

Pathway matching column, "Description" (default) or "ID".

gene_column

Pathway gene-member column. "auto" uses "geneID" or "core_enrichment" based on availability.

gene_sep

Delimiter used to parse pathway gene strings (default "/").

gene_mode

How to combine pathway genes for plotting: "union" (default) or "intersection".

gene_id_column

Optional column in rowData(vista_obj) used to map enrichment genes back to VISTA rownames (e.g., "SYMBOL" or "ENTREZID"). Leave NULL when enrichment genes already match VISTA rownames.

max_genes

Optional cap on the number of genes passed to the heatmap.

return_type

One of "heatmap" (default), "both", or "genes".

...

Additional arguments passed to get_expression_heatmap().

Value

Depending on return_type:

  • "heatmap": a ComplexHeatmap object from get_expression_heatmap().

  • "both": list with heatmap, genes, and pathway_genes.

  • "genes": character vector of mapped genes selected for plotting.

Examples

if (FALSE) { # \dontrun{
data("count_data", package = "VISTA")
data("sample_metadata", package = "VISTA")

vista <- create_vista(
  counts = count_data,
  sample_info = sample_metadata,
  column_geneid = "gene_id",
  group_column = "cond_long",
  group_numerator = "treatment1",
  group_denominator = "control"
)

msig <- get_msigdb_enrichment(
  vista,
  sample_comparison = names(comparisons(vista))[1],
  regulation = "Up",
  species = "Homo sapiens",
  from_type = "ENSEMBL"
)

get_pathway_heatmap(
  vista,
  enrichment = msig,
  samples = c("control", "treatment1"),
  top_n = 3,
  value_transform = "zscore",
  annotate_columns = TRUE,
  summarise_replicates = FALSE
)
} # }