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Export a complete VISTA asset bundle

export_vista_assets.Rd

Generates a standardized folder with selected VISTA plots, tabular outputs, and a manifest describing all saved files.

Usage

export_vista_assets(
  x,
  out_dir = "vista_assets",
  sample_comparison = NULL,
  display_id = NULL,
  include_plots = c("pca", "mds", "corr_heatmap", "deg_bar", "volcano", "ma",
    "expression_heatmap"),
  include_data = c("comparison", "norm_counts", "sample_info", "row_data", "deg_summary",
    "cutoffs"),
  plot_format = "png",
  width = 8,
  height = 6,
  heatmap_height = 10,
  units = "in",
  dpi = 300,
  top_n_labels = 50,
  heatmap_n_genes = 60,
  write_excel = FALSE,
  overwrite = TRUE
)

Arguments

x

A VISTA object.

out_dir

Output directory for exported assets.

sample_comparison

Optional comparison to use for comparison-specific outputs. Defaults to the first available comparison.

display_id

Optional gene identifier column used in labeling for volcano/MA/heatmap plots.

include_plots

Character vector of plot keys to export. Supported: "pca", "mds", "corr_heatmap", "deg_bar", "deg_pie", "deg_donut", "volcano", "ma", "expression_heatmap".

include_data

Character vector of data keys passed to save_vista_data().

plot_format

Plot format (e.g. "png" or "pdf").

width

Base plot width.

height

Base plot height.

heatmap_height

Height used specifically for expression heatmap export.

units

Plot dimension units.

dpi

Raster resolution for plots.

top_n_labels

Number of top genes to annotate in MA plots.

heatmap_n_genes

Number of top genes used in exported expression heatmaps.

write_excel

Logical; if TRUE, also writes a combined XLSX workbook for all requested include_data tables (requires writexl).

overwrite

Logical; if FALSE, aborts when out_dir already contains files.

Value

Invisibly, a list with out_dir, sample_comparison, manifest, plot_files, and data_files.

Examples

# \donttest{
set.seed(1)
mat <- matrix(rpois(60, lambda = 20), nrow = 10)
rownames(mat) <- paste0("gene", seq_len(nrow(mat)))
colnames(mat) <- paste0("sample", seq_len(ncol(mat)))
se <- SummarizedExperiment::SummarizedExperiment(
  assays = list(norm_counts = mat),
  colData = S4Vectors::DataFrame(
    group = rep(c("ctrl", "trt"), each = 3),
    row.names = colnames(mat)
  ),
  rowData = S4Vectors::DataFrame(
    gene_id = rownames(mat),
    row.names = rownames(mat)
  )
)
de <- data.frame(
  gene_id = rownames(mat),
  log2fc = rnorm(nrow(mat)),
  pvalue = runif(nrow(mat)),
  padj = runif(nrow(mat)),
  regulation = "Other",
  row.names = rownames(mat)
)
v <- as_vista(se, group_column = "group")
md <- S4Vectors::metadata(v)
md$de_results <- S4Vectors::SimpleList(trt_vs_ctrl = de)
md$de_summary <- S4Vectors::SimpleList(trt_vs_ctrl = as.data.frame(table(de$regulation)))
S4Vectors::metadata(v) <- md
out_dir <- tempfile("vista_assets_")
export_vista_assets(
  v,
  out_dir = out_dir,
  include_plots = "pca",
  include_data = c("comparison", "norm_counts")
)
# }