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Changelog

Source: NEWS.md

ggvolc 0.3.0

Better significance handling, auto-labels & interactivity

  • Significance on the adjusted p-value (FDR) by default. ggvolc() gains a sig_col argument ("padj" or "pvalue") and now defaults to "padj", so hits are called on the FDR — the recommended cutoff in most DE workflows — with the y-axis and the significance segment following the choice so the plot stays internally consistent. Set sig_col = "pvalue" for the raw p-value. When the default "padj" is used but the data has no adjusted-p column, ggvolc falls back to the raw p-value automatically.
  • Robust to p == 0. DESeq2 and edgeR can report a p-value of exactly 0 (floating-point underflow) for the strongest genes; -log10(0) is Inf, which ggplot2 silently drops — so the most significant genes used to vanish from the plot. Those values are now capped to a finite ceiling (just above the most significant real gene) and a message reports how many were adjusted.
  • label_top = N. Automatically highlight and label the N most significant genes without building a separate data2. Combines with an explicit data2 when both are supplied.
  • label_dir. Choose the direction the labelled genes are drawn from: "both" (default), "up", "down", or "each" (top N upregulated and top N downregulated). Pairs with label_top, e.g. label_top = 10, label_dir = "each".
  • title argument. The plot title is now configurable and defaults to NULL (no title), replacing the previous hardcoded placeholder title.
  • Interactive volcano plots. ggvolc(..., interactive = TRUE) returns a ggiraph girafe widget where hovering a point reveals the gene name and its statistics. ggiraph is an optional (Suggests) dependency, so the core package still installs without it.
  • New internal helper: neglog10_cap().
  • The README is now generated from README.Rmd (via devtools::build_readme()) so every example plot is rendered from live code and kept in sync with the package.
  • DESCRIPTION now declares R (>= 4.1.0), matching the native pipe (|>) used internally (previously mis-declared as >= 3.5.0).

ggvolc 0.2.0

Multi-pipeline support & gt tables

  • DESeq2, edgeR, and limma auto-detection: ggvolc() and genes_table() now accept output from all three major DE pipelines. Column names are automatically mapped internally — no manual renaming needed.
    • DESeq2: log2FoldChange, pvalue, padj, baseMean
    • edgeR: logFC, PValue, FDR, logCPM
    • limma: logFC, P.Value, adj.P.Val, AveExpr
  • Gene identifiers stored as row names (common in edgeR/limma) are automatically promoted to a genes column.
  • genes_table() rewritten with gt + patchwork:
    • Replaces gridExtra::grid.arrange with patchwork::wrap_table()
    • Gene table rendered as a gt table with formatted numerics, color-coded p-values, and directional log2FC coloring
    • p-value / adjusted-p columns use grid-safe scientific notation (1.0e-08) so exponents render correctly once the table is composed into the plot graphic by patchwork
    • Returns a proper patchwork object (composable, ggsave()-able)
  • New internal helpers: standardize_de_columns(), detect_de_source()
  • Added testthat test suite covering all three DE formats, column detection, attention genes, plot options, and the new gene table.
  • Dependencies: replaced gridExtra with gt and patchwork.
  • Version bump to 0.2.0.

ggvolc 0.1.0

CRAN release: 2026-01-16

Initial CRAN Release

  • Initial release of ggvolc package
  • Create customizable volcano plots for differential gene expression analysis
  • Functions included:
  • Features:
    • Highlight genes of interest
    • Adjustable significance thresholds (p-value and fold change)
    • Customizable colors for up/down regulated genes
    • Optional significance segment lines
    • Size scaling by log2FoldChange or p-value
    • Integration with ggplot2 for additional customization
  • Example datasets included:
    • all_genes: Complete differential expression results
    • attention_genes: Subset of genes to highlight