Choosing UpSet vs Venn vs Network
In vennDiagramLab: Headless Venn Diagram Analysis and Rendering

knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
# Skip evaluation of all chunks on CRAN's auto-check farm to fit the
# 10-minute build budget. Locally, on CI, and under devtools::check(),
# NOT_CRAN=true and all chunks evaluate normally. The vignette source
# (which CRAN users see in browseVignettes() / vignette()) is unchanged.
NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true")
knitr::opts_chunk$set(eval = NOT_CRAN)

Choosing UpSet vs Venn vs Network

vennDiagramLab ships three complementary visualizations of the same underlying region structure. This vignette explains when to use which.

library(vennDiagramLab)
result <- analyze(load_sample("dataset_real_cancer_drivers_4"))
length(result@dataset@set_names)

Quick guidance

| # of sets | Recommended primary view | Why | |---|---|---| | 2 | Venn | obvious, area-proportional possible | | 3 | Venn | classic three-circle layout reads instantly | | 4 | Venn (Edwards) | still readable as a Venn | | 5–6 | UpSet | Venn becomes hard to read; UpSet bars are clearer | | 7+ | UpSet (primary) + Network (relationships) | Venn is essentially unusable |

For high set counts (5+), the Network view adds something neither representation provides: it shows the pairwise relationships as a graph, where edge weight is intersection size or significance.

Venn

svg <- render_venn_svg(result, title = "4-set Venn (cancer drivers)")
nchar(svg)

The SVG is plain text — embed it in a notebook with htmltools::HTML(svg) or save to disk and reference from Markdown.

UpSet

render_upset(result, sort_by = "size", color_mode = "depth")

(The chunk above is gated on R >= 4.6 because the CRAN release of ComplexUpset (1.3.3) is incompatible with ggplot2 >= 4.0 on older R.)

Network

render_network(result, edge_metric = "intersection")

Each node is a set, sized by inclusive cardinality. Each edge is a pair, weighted by the chosen edge_metric ("intersection", "jaccard", "fold_enrichment", or "overlap_coefficient"). Edges below the significance threshold are colored differently.

When the three views disagree

Sometimes a region looks "small" on a Venn but lights up bright on a Network because the fold-enrichment is high relative to expectation. That's not a contradiction — Venn shows raw counts, Network can show normalized strength. Use both.

What's next

vignette("v05_statistics_deep_dive") — what the network's significance threshold actually means.
vignette("v07_pdf_reports") — generate a single PDF that includes all three views.