Gene Ontology Plot
Chart overview
A Gene Ontology enrichment plot summarizes the results of an over-representation analysis (ORA) or gene set enrichment analysis (GSEA) by displaying the most significant GO terms ranked by adjusted p-value.
Key points
- In the bubble chart format, each GO term is a circle whose size encodes the number of genes in the overlap between the query gene list and the GO term gene set, and whose color encodes the adjusted p-value from deep red (most significant) to pale yellow (least significant).
- The x-axis shows the gene ratio (overlap/term size) or normalized enrichment score.
- In the bar chart format, bars extend to represent gene count or GeneRatio and are color-mapped by -log10 adjusted p-value.
Example Visualization
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Generate publication-ready gene ontology plots with AI in seconds. No coding required – just describe your data and let AI do the work.
View example prompt
"Create a GO enrichment bubble chart from my ORA results with columns: GO_term, gene_count, gene_ratio, p_adjust, ontology. Plot gene_ratio on the x-axis, GO terms on the y-axis sorted by significance. Scale bubble size by gene_count and color by -log10 adjusted p-value using a red-yellow gradient. Split into three panels for BP, MF, and CC ontologies. Add a colorbar legend and size legend. Format for a Cell or Molecular Cell figure panel at 300 DPI."
How to create this chart in 30 seconds
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AI Generation
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Customize & Export
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Python Code Example
Console Output
Figure saved: plotivy-gene-ontology-plot.png
Common Use Cases
- 1Interpreting RNA-seq differential expression results: identifying enriched biological processes
- 2Proteomics: characterizing the functional categories of co-regulated protein clusters
- 3Single-cell RNA-seq: annotating marker gene lists from unsupervised cluster analysis
- 4CRISPR screen hits: categorizing functionally enriched pathways among essential genes
Pro Tips
Apply semantic similarity reduction (REVIGO or simplify in clusterProfiler) to remove redundant GO terms
Report both the gene ratio and the absolute gene count since a high ratio in a tiny term can be misleading
Select only the top 10-20 terms per ontology to keep the figure interpretable in a journal panel
Always state the background gene set used for enrichment testing (all expressed genes, not entire genome)
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.