Paste 2, 3, or 4 lists and get the overlaps, unique members, and exact region counts. Built for comparing gene lists and any sets, with a downloadable SVG diagram and a full intersection table.
6 unique items
6 unique items
| Region | Count | Members |
|---|---|---|
| Upregulated only | 3 | tp53, brca1, kras |
| Downregulated only | 3 | cdk4, mdm2, rb1 |
| Upregulated ∩ Downregulated | 3 | egfr, myc, pten |
The Venn diagram, introduced by John Venn (1880), is the most intuitive way to show how lists relate, but its value in research comes from the exact arithmetic underneath: the intersection is what appears in every list, and the set difference is what is unique to one. This generator assigns each unique item to exactly one region based on the full combination of lists it belongs to, so the counts are mutually exclusive and always sum to the total number of unique items.
In genomics the diagram answers a constant question: how much do two conditions share? Comparing genes upregulated in one treatment against those in another, or the hits from two screens, immediately shows the common core and the condition-specific tails. The shared set is often what you carry forward into pathway or enrichment analysis, which is why this tool lists the exact members of every overlap, not just the counts.
Two and three lists draw cleanly as circles, but four lists cannot be drawn with circles because circles cannot produce all fifteen required regions; the standard solution is four ellipses. Whatever the geometry, the intersection table is the authoritative output, so the numbers remain precise even when a four-set figure is visually dense. For an alternative that scales past four sets without the visual crowding, an UpSet plot is often preferred, and a heatmap generator can show membership as a matrix.
A Venn diagram summarizes overlap but does not test whether the overlap is larger than chance; that requires a hypergeometric or Fisher exact test, and multiple comparisons across many gene sets need correction, which the false discovery rate calculator handles. For a complete differential-expression analysis with statistics and publication-ready figures, the bioinformatics analysis service takes it from raw data to results.
Each list in its own box, one item per line. Name each set so the figure and table are labelled.
Two or three sets draw as circles; add a fourth for the four-ellipse layout.
The diagram shows each region count, and the table lists the exact members of every intersection.
Export a scalable vector diagram for your figure, or copy the members of any overlap.
Next step
Differential-expression comparison, enrichment context, and publication-ready figures, handled by a PhD statistician.
Our promise: Free pipeline re-run and figure revisions if reviewers push back.
Timeline
Most projects deliver in under 2 weeks. We confirm an exact date in your quote.
If reviewers push back
If reviewers question the pipeline, parameters, or figures, we re-run the analysis and revise free.
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NDA available on request before any project discussion. Your data, study design, and manuscript stay private either way.
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Paste each list into a separate box, one item per line, and the generator computes which items are unique to each list and which are shared, then draws overlapping circles with the count in each region. Every unique item is assigned to exactly one region based on the full combination of lists it appears in, so the region counts are mutually exclusive and add up to the total number of unique items. You can download the diagram as an SVG and read the exact members of every region in the table below.
Yes. This generator handles 2, 3, or 4 lists. Two and three lists are drawn with the familiar overlapping circles, while four lists use the standard four-ellipse layout because four circles cannot show all fifteen possible overlaps. Whatever the number of sets, the intersection table below the diagram lists the exact count and members of every region, so the data is precise even where a four-set diagram is visually dense.
The overlapping region is the intersection, the set of items that appear in all of the overlapping lists. The non-overlapping part of a circle is the set difference, the items unique to that list. In this tool, each row of the region table is labelled with the exact combination of sets it represents, such as an item being in the first and third list but not the second.
Paste each gene list, for example genes upregulated in one condition and downregulated in another, into a separate box. The generator shows how many genes are shared between conditions and how many are unique to each, which is a common first step in differential expression analysis. The exact gene names in each overlap are listed in the region table so you can copy the shared set forward into enrichment analysis.
By default the comparison is case insensitive, so GENE1 and gene1 are treated as the same item, which is usually what you want for gene symbols pasted from different sources. A case-sensitive toggle is available when capitalization is meaningful, for example when comparing identifiers where case distinguishes different entities. Duplicate items within a single list are counted once.
Yes. The diagram downloads as a scalable vector graphic (SVG), which stays sharp at any size and can be edited in Illustrator or Inkscape or dropped straight into a figure. The region table can be read on screen so you can copy the exact members of any overlap into your analysis or supplementary materials.
To test whether an overlap of gene sets is larger than chance across many comparisons, the false discovery rate calculator corrects for multiple testing. To visualize expression across shared genes, the heatmap generator renders a clustered matrix, and the volcano plot generator shows fold change against significance. For an end-to-end analysis of your data, the bioinformatics analysis service delivers publication-ready results.
Reviewed by
Dr. Sarah Mitchell holds a PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health and has over 15 years of experience in systematic review methodology and meta-analysis. She has authored or co-authored 40+ peer-reviewed publications in journals including the Journal of Clinical Epidemiology, BMC Medical Research Methodology, and Research Synthesis Methods. A former Cochrane Review Group statistician and current editorial board member of Systematic Reviews, Dr. Mitchell has supervised 200+ evidence synthesis projects across clinical medicine, public health, and social sciences. She reviews all Research Gold tools to ensure statistical accuracy and compliance with Cochrane Handbook and PRISMA 2020 standards.
Our PhD statisticians run the complete pipeline: differential expression with multiple-testing correction, survival modelling, dimensionality reduction, and publication-ready figures with a reproducible methods section. Constant pricing, most projects delivered in under two weeks.
Our promise: Free pipeline re-run and figure revisions if reviewers push back.
Your project is led by a named PhD methodologist with real credentials and published work.
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