Volcano plot maker
Upload your DESeq2/limma results and get a clean, publication-ready volcano plot with significance thresholds and labelled genes — no R or Python required.
Why use it
Publication-ready by default
Proper log2 fold-change vs −log10 p-value axes, significance cutoffs, and journal-grade typography (Arial, high-DPI) out of the box.
No coding
Skip the ggplot2/matplotlib boilerplate — describe what you want and adjust thresholds, colours, and labels in plain language.
Export for journals
Download editable SVG or high-resolution PDF/PNG/EPS that meets submission requirements.
How it works
Upload your results
Drop in a CSV with fold-change and p-value (or adjusted p-value) columns from DESeq2, edgeR, or limma.
Set thresholds
Choose your significance and fold-change cutoffs and which genes to label.
Export the figure
Download a publication-ready SVG/PDF, or refine colours and labels first.
What you can do with it
RNA-seq papers
Show up- and down-regulated genes between conditions in one clear figure.
Proteomics & metabolomics
Any differential-abundance analysis maps onto a volcano plot.
Thesis & grant figures
Produce a consistent, styled figure set without wrangling plotting code.
Frequently asked questions
What data do I need for a volcano plot?
A table with a fold-change column (typically log2 fold-change) and a p-value or adjusted p-value column — for example, standard DESeq2 or limma output.
Can I label specific genes?
Yes — label the top significant genes automatically, or name specific genes of interest.
Is the figure publication-ready?
Yes — it uses journal-grade styling and exports editable SVG and high-DPI PDF/PNG/EPS suitable for submission.
Do I need to know R or Python?
No. The volcano plot maker is no-code; you upload data and adjust the plot in plain language.
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