Plot group-level deconvolution scores as dot plot

Usage

get_celltype_group_dotplot(
  x,
  group_column = NULL,
  cell_types = NULL,
  top_n = 12,
  summary_fun = c("mean", "median"),
  error = c("se", "sd", "none"),
  add_points = TRUE,
  point_size = 2.5,
  font_size = 12
)

Arguments

x: A VISTA object.
group_column: Column in sample_info(x) that defines groups. If NULL, uses the active VISTA group column when available.
cell_types: Optional character vector of cell types to include.
top_n: Number of top cell types by mean score when cell_types is NULL.
summary_fun: One of "mean" or "median" for group summary.
error: Error-bar type: "se", "sd", or "none".
add_points: Logical; overlay sample-level jittered points.
point_size: Point size for summary points.
font_size: Base font size.

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
get_celltype_group_dotplot(v, group_column = "cond")