Plot fold-change distributions across comparisons — get_foldchange

Builds boxplots of log2 fold changes for selected genes and comparisons, optionally adding statistics.

Usage

get_foldchange_boxplot(
  x,
  genes = NULL,
  sample_comparisons = NULL,
  display_id = NULL,
  display_from = NULL,
  display_orgdb = NULL,
  facet_scales = "free_x",
  facet_nrow = NULL,
  facet_ncol = NULL,
  facet_by = c("auto", "comparison", "none"),
  p.label = "p.signif",
  stats_group = FALSE,
  stats_method = "t.test"
)

Arguments

x: A VISTA object containing differential expression results.
genes: Optional character vector of gene IDs to include.
sample_comparisons: Optional character vector of comparison names to plot.
display_id: Optional ID/column name used to interpret genes and, when possible, map fold-change gene identifiers to display-friendly labels.
display_from: Optional source ID type for mapping when display_id is not present in rowData(x).
display_orgdb: Optional OrgDb object used for identifier mapping when display_id is not present in rowData(x).
facet_scales: Facet scales argument passed to facet_wrap() when facet_by != "none" (default "free_x").
facet_nrow, facet_ncol: Optional layout passed to facet_wrap() when faceting.
facet_by: Faceting mode: "auto" (default), "comparison", or "none".
p.label: Label type passed to ggpubr::stat_compare_means().
stats_group: Logical; add pairwise statistical tests when TRUE.
stats_method: Statistical method passed to ggpubr::stat_compare_means().

Value

An object returned by this function.

Examples

v <- example_vista()
comp <- names(comparisons(v))[1]
genes <- head(as.character(comparisons(v)[[comp]]$gene_id), 10)
p <- get_foldchange_boxplot(v, sample_comparison = comp, genes = genes)
print(p)