Plot cell-type composition as stacked bars

Usage

plot_celltype_barplot(
  x,
  group_column = NULL,
  samples = NULL,
  font_size = 12,
  cell_types = NULL,
  top_n = NULL,
  collapse_other = TRUE,
  normalize = c("sample", "none"),
  facet_by_group = TRUE
)

Arguments

x: A VISTA object.
group_column: Optional column in sample_info(x) used to facet/order samples. If NULL, uses the active VISTA group column when available.
samples: Optional character vector of sample names to include.
font_size: Base font size.
cell_types: Optional character vector of cell types to keep.
top_n: Optional top-N cell types by mean score (ignored when cell_types is provided).
collapse_other: Logical; collapse non-selected cell types into "Other".
normalize: One of "sample" (default; per-sample relative scores) or "none".
facet_by_group: Logical; facet by group when group_column is available.

Value

A ggplot object.

Examples

mat <- matrix(rpois(20, lambda = 20), nrow = 5)
rownames(mat) <- paste0("gene", seq_len(5))
colnames(mat) <- paste0("sample", seq_len(4))
se <- SummarizedExperiment::SummarizedExperiment(
  assays = list(norm_counts = mat),
  colData = S4Vectors::DataFrame(
    cond = c("A", "A", "B", "B"),
    row.names = colnames(mat)
  ),
  rowData = S4Vectors::DataFrame(
    gene_id = rownames(mat),
    row.names = rownames(mat)
  )
)
v <- as_vista(se, group_column = "cond")
md <- S4Vectors::metadata(v)
md$cell_fractions <- data.frame(
  fibroblast = c(0.2, 0.3, 0.4, 0.5),
  epithelial = c(0.8, 0.7, 0.6, 0.5),
  row.names = colnames(mat)
)
S4Vectors::metadata(v) <- md
plot_celltype_barplot(v, group_column = "cond")