Fold-change line plot across comparisons

Plots log2 fold-change trajectories for selected genes across multiple comparisons, optionally clustering genes.

Usage

get_foldchange_lineplot(
  x,
  sample_comparisons,
  genes = NULL,
  km = NULL,
  facet_by = c("none", "cluster"),
  alpha = 0.5,
  show_summary = TRUE,
  summary_color = NULL,
  summary_linewidth = 1,
  summary_fun = c("median", "mean")
)

Arguments

x

A VISTA object containing differential expression results.

sample_comparisons

Character vector of comparison names to include.

genes

Optional character vector of gene identifiers to plot. Defaults to all genes.

km

Optional integer specifying the number of k-means clusters to compute; NULL disables clustering.

facet_by

Faceting mode: "none" (default) or "cluster" when k-means clustering is requested.

alpha

Numeric alpha applied to individual gene lines.

show_summary

Logical; overlay a summary line per cluster when TRUE.

summary_color

Color used for the summary line. When NULL, uses the first comparison color (if stored) for consistency across plots.

summary_linewidth

Numeric line width for the summary line.

summary_fun

Character string selecting "median" or "mean" for the summary statistic.

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), 5)
p <- get_foldchange_lineplot(v, sample_comparison = comp, genes = genes)
print(p)
#> $plot
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?
#> `geom_line()`: Each group consists of only one observation.
#> ℹ Do you need to adjust the group aesthetic?

#> 
#> $clustered_data
#>                         gene_id cluster
#> ENSG00000000003 ENSG00000000003     All
#> ENSG00000000419 ENSG00000000419     All
#> ENSG00000000457 ENSG00000000457     All
#> ENSG00000000460 ENSG00000000460     All
#> ENSG00000000971 ENSG00000000971     All
#>