nVenn2: Faster, simpler generalized quasi-proportional Venn diagrams
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ID: 319146
2026
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Abstract
Abstract Proportional Venn diagrams provide a compact representation of the relationships between sets. Each relationship is represented with a region whose area reflects the number of elements shared by a given combination of sets. This means that the number of regions grows exponentially with the number of sets, which is why proportional Venn diagrams with more than five sets are cumbersome to interpret and seldom used. However, Venn diagrams with a large number of sets may still be legible if enough regions are empty and do not need to be represented. Here, we present nVenn2, the second version of the nVenn algorithm, to create quasi-proportional Venn diagrams. This new version uses a different, more flexible approach which includes steps to minimize the complexity of the diagram. Thus, computation time for nVenn2 mainly grows with the number of non-empty diagram regions, rather than with the number of sets. This property allows users to create interpretable quasi-proportional Venn diagrams with large numbers of sets. The nVenn2 algorithm is freely available as an executable program, as a web page, as an R package (nVennR2) and as a Python package (nVennPy). All interfaces allow users to edit the appearance of the resulting diagram.
| Reference Key |
openalex_W7166553713
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| Authors | Samuel Pis-Vigil, María González-Pereira, Magda R. Hamczyk, Vı́ctor Quesada |
| Journal | Bioinformatics advances |
| Year | 2026 |
| DOI |
10.1093/bioadv/vbag183
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| URL | |
| Keywords | Keywords not found |
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