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Create Volcano Plot for Differential Expression Results

Source: R/plot_volcano.R
plot_volcano.Rd

Generates a customizable volcano plot visualizing differential expression results, highlighting significant genes based on both fold change and statistical significance. The plot supports various customization options including color schemes, point sizes, and gene labeling.

Usage

plot_volcano(
  devil.res,
  lfc_cut = 1,
  pval_cut = 0.05,
  labels = TRUE,
  colors = c("gray", "forestgreen", "steelblue", "indianred"),
  color_alpha = 0.7,
  point_size = 1,
  center = TRUE,
  title = "Volcano plot"
)

Arguments

devil.res

A tibble from test_de() containing columns:

  • name: Gene identifiers

  • adj_pval: Adjusted p-values

  • lfc: Log2 fold changes

lfc_cut

Numeric. Absolute log2 fold change threshold for significance. Default: 1

pval_cut

Numeric. Adjusted p-value threshold for significance. Default: 0.05

labels

Logical. Whether to label genes meeting both significance criteria. Default: TRUE

colors

Character vector of length 4 specifying colors for:

  1. Non-significant genes

  2. Fold-change significant only

  3. P-value significant only

  4. Both significant Default: c("gray", "forestgreen", "steelblue", "indianred")

color_alpha

Numeric between 0 and 1. Transparency level for points. Default: 0.7

point_size

Numeric. Size of plotting points. Default: 1

center

Logical. Whether to center the x-axis at zero. Default: TRUE

title

Character. Plot title. Default: "Volcano plot"

Value

A ggplot2 object containing the volcano plot.

Details

The function creates a scatter plot with:

  • X-axis: Log2 fold change

  • Y-axis: -Log10 adjusted p-value Points are colored based on significance categories:

  1. Non-significant: Neither p-value nor fold change threshold met

  2. LFC significant: Only fold change threshold met

  3. P-value significant: Only p-value threshold met

  4. Both significant: Both thresholds met

The plot includes dashed lines indicating significance thresholds and optionally labels genes meeting both significance criteria.

Note

  • Genes with adj_pval = 0 are assigned the smallest non-zero p-value in the dataset

  • NA values are removed with a warning

  • Gene labels are placed with overlap prevention

Examples

if (FALSE) { # \dontrun{
# Basic volcano plot
plot_volcano(de_results)

# Custom thresholds and colors
plot_volcano(de_results,
            lfc_cut = 2,
            pval_cut = 0.01,
            colors = c("grey80", "blue", "green", "red"))

# Without gene labels
plot_volcano(de_results, labels = FALSE)
} # }