Consequence summary bar chart

Summarises variant consequences (e.g. missense, frameshift, synonymous) across one or more samples, producing a stacked or grouped bar chart.

Usage

plot_consequence_summary(
  variants,
  samples = NULL,
  group_by = c("consequence", "gene"),
  top_n = 10L,
  position = c("stack", "fill", "dodge"),
  palette = NULL,
  flip = FALSE,
  interactive = FALSE
)

Arguments

variants

A gvf object from read_vcf() or coerce_variants(), or any data.frame with columns pos, consequence, and optionally gene and sample.

samples

Character vector of sample names to include. NULL (default) uses all samples. Ignored if there is no sample column.

group_by

"consequence" (default) stacks bars by consequence per sample; "gene" stacks by gene per consequence.

top_n

Integer. For group_by = "gene", show only the top N genes by total variant count. Default 10.

position

"stack" (default) or "fill" (proportional) or "dodge".

palette

Named character vector of colours for each consequence/sample category. NULL uses the built-in ggvariant palette.

flip

Logical. If TRUE, flips coordinates for horizontal bars. Default FALSE.

interactive

Logical. If TRUE, returns a plotly interactive plot (requires the plotly package).

Value

A ggplot object.

See also

plot_lollipop(), plot_variant_spectrum(), gv_palette()

Other ggvariant plots: plot_lollipop(), plot_oncoprint(), plot_tmb(), plot_variant_spectrum()

Examples

vcf_file <- system.file("extdata", "example.vcf", package = "ggvariant")
variants <- read_vcf(vcf_file)
#> ℹ Reading VCF: example.vcf
#> ✔ Reading VCF: example.vcf [10ms]
#> 
#> Loaded 19 variant records across 7 chromosomes.

# Consequence counts per sample
plot_consequence_summary(variants)


# Proportional bars
plot_consequence_summary(variants, position = "fill")


# Top 10 genes coloured by consequence
plot_consequence_summary(variants, group_by = "gene", top_n = 10)