Volcano plot

Effect size against significance, with the calling thresholds drawn. This is the standard first look at a differential analysis: it separates the features that moved a lot from the ones that moved reliably, and shows how many of each the thresholds produce.

Usage

plot_volcano(
  effect,
  p_value,
  label = NULL,
  effect_threshold = 1,
  p_threshold = 0.05,
  label_top = 10,
  palette = "house",
  repel = TRUE,
  xlab = "Effect size",
  ylab = expression(-log[10] ~ italic(P)),
  title = NULL,
  font = "Arial"
)

Arguments

effect

Numeric effect sizes, typically a log fold change.

p_value

Significance values on the same scale as p_threshold.

label

Feature labels.

effect_threshold, p_threshold

Calling thresholds. Features past both are labelled as significant.

label_top

Label the most significant features instead of every significant one. Set to 0 to label none, or Inf to label all.

palette

Palette name passed to get_color().

repel

Repel the labels so they do not overlap.

xlab, ylab, title

Axis and plot labels.

font

Font family used in the plot.

Value

A ggplot object.

Examples

set.seed(1)
effect <- rnorm(2000)
p_value <- runif(2000)^2
p <- plot_volcano(effect, p_value, paste0("gene", seq_along(effect)))