Best free tools to plot volcano plots from CSV data

Best Free Tools to Plot Volcano Plots from CSV Data

Hey biotech students & early researchers! 👋

If you’ve just finished your RNA-seq or proteomics analysis, you’re probably staring at a huge CSV file full of log fold changes and p-values, wondering how to make a clear, publication-worthy volcano plot.

Good news: you don’t need expensive software. Here’s a quick roundup of the best free tools (online and open-source) to turn your CSV into an impressive volcano plot in minutes.

🏆 1. VolcaNoseR (R Shiny web app)

Where: https://huygens.science.uva.nl/VolcaNoseR/

Why it’s great:

✅ Completely browser-based — upload your CSV, pick columns, and customize thresholds.

✅ Interactive: hover to see gene/protein names, auto-label top hits.

✅ Download high-res PNG or PDF.

Best for:

Quick, shareable volcano plots — great for thesis presentations or lab meetings.

🐍 2. Python (seaborn / matplotlib scripts)

Why it’s great:

✅ Complete control over style (colors, labels, thresholds).

✅ Can easily automate plots for multiple datasets.

✅ Free & open-source forever.

Best libraries:

pandas to read your CSV

matplotlib and seaborn to plot

numpy for threshold calculations

Downside:

A small learning curve if you’re new to Python. But plenty of volcano plot tutorials are online!

🔬 3. R + ggplot2

Why it’s great:

✅ The gold standard for data visualization in bioinformatics.

✅ ggplot2 gives beautiful, publication-ready plots.

✅ Tons of volcano plot templates on GitHub.

Starter template:

library(ggplot2)

data <- read.csv(“results.csv”)

ggplot(data, aes(x=log2FoldChange, y=-log10(pvalue))) +

  geom_point() +

  theme_minimal()

Best for:

If you’re already using DESeq2 or EdgeR, you’re halfway there — just pipe the results into ggplot2.

🌐 4. GraphPad Prism (demo / limited free)

Why it’s on the list:

While not fully free, GraphPad Prism’s demo lets you create volcano plots from CSV easily. If you’re preparing a thesis figure, this is handy for short-term needs.

📊 5. Galaxy Europe (Web platform)

Where: https://usegalaxy.eu/

Why it’s great:

✅ No coding needed, just upload your data & use volcano plot tools under the Visualization section.

✅ Integrates smoothly if your DE analysis was also done on Galaxy.

✅ 3 quick tips for plotting volcano plots

📝 Use -log10(p-value) on the Y-axis. It makes small p-values (significant hits) show up high on the plot.

🎯 Highlight or color genes of interest (like specific biomarkers) — reviewers and lab mates will thank you.

📁 Always save both your plot image and the underlying filtered CSV data for reproducibility.

🔗 References & handy guides

Illumina (2023). ‘Data visualization for differential gene expression.’ Available at: https://www.illumina.com

Blighe, K. et al. (2022). ‘EnhancedVolcano: publication-ready volcano plots in R.’ Bioinformatics, 38(2), pp. 472–474. DOI: 10.1093/bioinformatics/btab658.

🎉 Summary: Which should you use?

If you want…        Use this tool

Easiest no-code option        VolcaNoseR (web app)

Fully customizable plots        R + ggplot2 or Python

Analysis + plotting combo        Galaxy Europe

Quick thesis figures        GraphPad Prism demo