Volcano Plot Generator for RNA-seq & Proteomics—No R or Python Required

A volcano plot needs one feature identifier, one numeric log₂ fold-change column, and one significance column containing a p-value, adjusted p-value, FDR, or q-value. The generator detects common headers including gene, symbol, protein, log2FoldChange, logFC, pvalue, padj, FDR, and qvalue, then displays the mapping for review.

Adjusted p-values or FDR are generally more defensible for high-throughput experiments because thousands of features are tested simultaneously. Use the significance measure produced by the statistical analysis, keep its original meaning, and identify it in the axis label, figure caption, or methods section so readers can interpret the cutoff correctly.

Calculate log₂ fold change and p-values with an appropriate differential-expression or statistical workflow before plotting. DESeq2, edgeR, and limma can produce these columns for sequencing data, while proteomics pipelines provide comparable effect-size and significance fields. The Volcano Plot Generator visualizes those results; it does not replace the underlying statistical analysis.

Copy the feature, log₂ fold-change, and significance columns from Excel and paste them directly into the data field; tab-separated cells are detected automatically. You can also save the worksheet as CSV or TSV and upload it. The browser draws the plot without requiring R, Python, package installation, or command-line setup.

A common starting point is |log₂FC| ≥ 1 with adjusted p-value or FDR ≤ 0.05, but the correct thresholds depend on experimental design, statistical power, field standards, and the prespecified analysis plan. The controls visualize the rule you enter; they do not select or validate the scientific decision for you.

Volcano plots can represent any feature-level comparison that includes an effect-size column and a valid significance column. Use protein IDs, metabolites, SNPs, miRNAs, screening hits, or other identifiers in the feature field. Review domain-specific preprocessing and multiple-testing rules before interpreting the highlighted points as biological or clinical candidates.

SVG export preserves vector points, text, threshold lines, and labels for later editing. PNG provides a high-resolution raster version for documents and slides. Before submission, confirm the target journal’s figure width, font size, color requirements, caption format, and accepted file types, then verify every plotted value against the source analysis.

Pasted and uploaded tables are parsed locally in the browser, so the source data does not leave the device during plotting or download. Data is sent to PaperBanana only when you explicitly open an account feature that creates an editable project. Review institutional data-handling requirements before using any cloud editing workflow.