Create a volcano plot showing fold-change (x-axis) versus adjusted p-value significance (y-axis). The function auto-detects a suitable x-axis column if one is not provided and expects an adjusted p-value column for significance coloring.
Usage
plot_volcano(
diff_df,
x_col = NULL,
padj_col = "adjusted_p_values",
label_thresh = 0.1,
padj_thresh = 0.05,
top_n = 5,
title = NULL
)Arguments
- diff_df
Data.frame from `test_differential()` or similar results. Should contain p-values and optionally fold-change columns.
- x_col
Optional column name for the x-axis. If `NULL`, the function will try to auto-detect a suitable numeric column (excluding p-values).
- padj_col
Adjusted p-value column name (default: "adjusted_p_values").
- label_thresh
Fold-change threshold used to annotate points (default: 0.1).
- padj_thresh
Adjusted p-value cutoff for significance (default: 0.05).
- top_n
Number of top significant genes to label (default: 5).
- title
Optional plot title; if `NULL` a default title is used.
Examples
df <- data.frame(
gene = paste0("g", seq_len(10)),
mean_difference = runif(10),
adjusted_p_values = runif(10)
)
# plot_volcano(df, x_col = "mean_difference", padj_col = "adjusted_p_values")