Stop struggling with R or Python code. Plotivy automatically identifies p-value thresholds, log-fold changes, and creates publication-ready volcano plots with a single prompt.
We know the pain. You have DESeq2 or edgeR output, and now you need a publication-quality volcano plot.
ggplot2 syntax errors, matplotlib figure sizes, missing packages... You're a scientist, not a software developer.
Where do I draw the p-value line? What's the right fold-change cutoff? Manually adjusting parameters wastes valuable research time.
Wrong DPI? Axes labels too small? Reviewers rejecting your manuscript because figures don't meet Nature/Cell standards.
Our AI understands volcano plots. It automatically detects your p-value and fold-change columns.
Drag & drop your DESeq2 output, edgeR results, or any CSV with log2FC and p-values.
“Create a volcano plot with p-value < 0.05 and |log2FC| > 1 cutoffs. Label top 10 genes.”
Download at 300+ DPI in PNG, PDF, or TIFF. Automatically meets Nature/Science guidelines.
✨ Plotivy AI understands this natural language and generates the correct matplotlib code automatically.
AI suggests optimal p-value (0.05, 0.01, FDR-adjusted) and fold-change thresholds based on your data distribution.
Smart label placement prevents overlap. Automatically highlights top significant genes or specific genes of interest.
One-click compliance with Nature, Science, Cell, PNAS requirements. Correct DPI, font sizes, and dimensions guaranteed.
Don't like the colors? Just say "change upregulated to green" and Plotivy regenerates instantly.
Co-Scientist explains your plot: "423 genes significantly upregulated, 156 downregulated. Top hit: TP53 (padj = 1.2e-45)."
Get reproducible matplotlib code. Run it again, modify it, or include it in your methods section.