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Maintenance release addressing the CRAN incoming-pretest checktime
NOTE (Overall checktime > 10 min on r-devel-windows). No
API, output, or dependency changes — every public function behaves
byte-identically.
load_csv() / load_tsv() are now
~10x faster on large files. The internal delimited-file parser
(.split_line, .binary_columns_to_dataset,
.aggregated_columns_to_dataset) was quadratic in the number
of rows because it grew result vectors one element at a time and trimmed
cells character-by-character. It is now vectorised: unquoted lines split
with a single strsplit(), and membership / trim /
lower-case run over a character matrix. Loading the bundled 20,000-row
dataset_real_cancer_drivers_4 sample dropped from ~6.5s to
~0.5s. Parsing results (item sets, item order, universe size, error
conditions) are unchanged — verified by the byte-parity fixtures and the
.split_line / converter unit tests.skip_on_cran() added to the remaining heavy
PDF-rendering integration tests (to_pdf_report share /
cluster pages, to_zip_report) so the on-CRAN test pass
stays light; these still run on CI and under
devtools::check().Version-only release: bumps vennDiagramLab from 2.2.3 to
2.4.1 to keep the R, Python, and web-tool version lines in lockstep with
the Python companion venn-diagram-lab 2.4.1 on PyPI and the
web tool. No new exports, no API or behaviour changes, and no new
dependencies relative to 2.2.3 — the test suite, vignettes, and
documentation are unchanged apart from the version string.
Cross-package patch release matching webtool v2.2.3 and Python v2.2.3, delivered in two additive phases (10 + 11). No breaking changes, no removed APIs.
New rendering and export APIs that bring the R surface in line with the webtool and the Python package:
render_enrichment_bar(result, metric, width, height):
pairwise enrichment bar chart SVG. Bar height encodes -log10(BH-FDR) or
Fold Enrichment, with green / grey colouring at FDR < 0.05 and
significance markers ***/**/*
above each bar.render_enrichment_lollipop(result, metric, width, height):
same data as render_enrichment_bar() rendered as a
stem-and-dot plot, with dot radius scaling by
sqrt(intersection / max_intersection).to_excel_workbook(result, path): 3-sheet xlsx (Jaccard,
Sørensen-Dice, Enrichment) matching the webtool’s ZIP-bundle statistics
file. Pure-R (uses openxlsx).to_zip_report(result, path, include_share, include_cluster):
bundles PDF + 4 SVGs + 3 TSVs + xlsx + README.txt into a single ZIP
archive. Pure-R (uses zip).to_pdf_report() gains include_share = TRUE
(Item Share Distribution page, on by default) and
include_cluster = FALSE (Cluster Heatmap page, opt-in)
flags.Six new public APIs (two render_venn_svg() parameters
plus four exported functions) for inspecting and presenting individual
regions.
render_venn_svg(result, show_items = TRUE, item_options = list(...)):
replaces the per-region count text with the actual item identifiers,
optionally column-paginated, optionally truncated.
item_options recognises max_items_per_region,
ncol_items, truncate_long_names,
line_height, font_size,
show_counts_with_items, ellipsis.render_venn_svg(result, highlight = ...): spotlight
mode. Accepts a character vector of region labels ("AB",
"ABC", …) OR an integer vector of region bitmasks. Sets
that do not contribute to any highlighted region get desaturated to
#cccccc at 25% opacity.intersection_items(result, sets): items appearing in
every set in sets, regardless of other memberships.exclusive_items(result, sets): items in EXACTLY this
combination (not in any other set in the dataset).union_items(result, sets): items in any of the named
sets.parse_region_expression(expr, n_sets): Boolean DSL
parser. Grammar: & intersection,
|/+ union, ~/!
complement, parentheses for grouping, atoms A..I. Returns a
sorted integer vector of region bitmasks suitable for
highlight = ....The four new public functions chain naturally with the existing renderers:
masks <- parse_region_expression("A & B + B & C", n_sets = 4L)
img <- render_venn_svg(result, highlight = masks, show_items = TRUE)
items <- exclusive_items(result, c("A", "B"))openxlsx and zip added to
Imports (both pure-R). No new dependencies in Phase
11.Additive feature release matching the webtool v2.2.2 and Python v2.2.2 releases. No breaking changes, no removed APIs, no new hard dependencies.
item_share_distribution(matrix): per-membership-count
item totals.cluster_set_order(D, linkage): UPGMA / complete /
single linkage on a symmetric distance matrix, with
leaf_order and merges matching the
cross-package convention (smaller-min-leaf on the left).render_share_distribution(dataset): histogram SVG,
480×280 viewBox.render_cluster_heatmap(result, linkage, ...): 1 −
Jaccard reordered heatmap with row and column dendrogram overlays.SvgImage (content,
width, height slots) returned by the two new
plot renderers. render_venn_svg() continues to return a
plain character for backwards compatibility with the v2.0.x
API.Patch release addressing two issues from the CRAN auto-check on v2.0.4.
inst/CITATION no longer errors during CRAN
incoming-feasibility check. The file previously called
utils::packageDescription("vennDiagramLab"), which returns
NA when the package is not yet installed (as during CRAN’s
pre-install incoming check). NA$Version then triggers the
cryptic "$ operator is invalid for atomic vectors" error.
The fix uses the meta variable that R auto-injects when
parsing the CITATION file, the documented pattern from “Writing R
Extensions”. citation("vennDiagramLab") output is unchanged
on installed copies.NOT_CRAN for every chunk in every vignette. v2.0.4
gated only the four obviously-slow chunks (render_upset,
render_network, to_pdf_report,
geom_venn composite), but win-builder still reported
[12m] OK on the
re-building of vignette outputs step. The remaining time
was spent on per-vignette library(vennDiagramLab) calls
(which transitively load ggplot2,
ComplexUpset, ggraph, tidygraph,
rsvg, patchwork, gridExtra,
BiocGenerics — slow on Windows VMs) plus the lightweight
analyze() / render_venn_svg() /
broom chunks across eight vignettes. The setup chunk of
every vignette now sets
knitr::opts_chunk$set(eval = NOT_CRAN), so on CRAN the
rebuild is text-only (~1 minute total). Under
devtools::check() and on the package’s GitHub Actions CI
matrix NOT_CRAN=true and all chunks evaluate normally.
Locally verified: total vignette rebuild dropped from 12 min (Windows) /
~2 min (Mac) to ~12 seconds on Mac.No public-API or feature changes.
inst/CITATION packageDescription() NA crash
during incoming check, (2) overall checktime 20 min > 10 min
(vignettes 12 min — partial gating was insufficient).meta; all vignette chunks gated.Patch release addressing two issues from the CRAN auto-check + human reviewer feedback on v2.0.3.
'Venn Diagram Lab',
'UpSet', 'CSV', 'TSV',
'GMT', 'GMX', 'Jaccard',
'ggplot2', 'tidygraph', 'broom'.
Suppresses the “Possibly misspelled words in DESCRIPTION” NOTE (flagged
GMX, Jaccard, TSV, UpSet, ggplot, tidygraph).render_upset, render_network,
to_pdf_report, geom_venn composite,
rsvg_png/rsvg_pdf export) on
NOT_CRAN. On dev (devtools::check() sets
NOT_CRAN=true) and CI all chunks still build their figures;
the full 590+ test suite + 8 vignettes still execute on the 5-cell
GitHub Actions matrix. On CRAN only the lightweight analysis chunks
evaluate, bringing total checktime well under the 10-minute budget.No public-API or feature changes.
NOT_CRAN gating +
DESCRIPTION quoting.Patch release reducing CRAN auto-check time below the 10-minute target. The full test suite (590+ tests) and integration tests against bundled samples + 44 SVG models pushed the Windows R CMD check to ~41 minutes, which auto-rejected the v2.0.2 incoming pretest.
test-render-pdf,
test-render-svg, test-render-upset,
test-render-network, test-parity-with-webapp)
now call testthat::skip_on_cran() at the top of every
test_that() block. CRAN sees only the fast unit-test slice
(test-analysis, test-classes,
test-statistics, test-broom-tidy,
test-ggplot-layer, test-io,
test-samples, test-proportional,
test-tsv-export). The skipped tests still run on the
package’s GitHub Actions CI matrix (5 cells × 590 tests), where
NOT_CRAN=true triggers the full test suite.No public-API or feature changes; the package’s user-facing behavior is identical.
cat(..., file = path) text-mode
write.skip_on_cran() in slow tests;
expected sub-10-min pretest.Patch release fixing a cross-platform packaging bug that surfaced on the win-builder CRAN check for v2.0.1.
cat(out, file = path) opens the
connection in text mode by default; on Windows that converts
"\n" → "\r\n", breaking the 12 byte-parity
tests against the Python golden fixtures (which use "\n"
only, matching the React webapp’s TSV exports). New private helper
.write_bytes() opens the file in "wb" (binary)
mode and uses writeBin(charToRaw(x), con). Affects
to_region_summary_tsv(), to_matrix_tsv(), and
to_statistics_tsv(). No public-API changes; behavior on
Linux/macOS unchanged.v2.0.1 was submitted to CRAN on 2026-05-07; the win-builder pretest failed with the CRLF bug above before the human reviewer was reached. v2.0.2 is the resubmission with the fix.
Patch release fixing a packaging bug that broke
analyze() for users installing via
remotes::install_github().
analyze() no longer fails with
"no file found" after
remotes::install_github(..., subdir = "r"). Root
cause: the bundled 44 SVG templates, 44 region JSONs, and 5 sample
datasets under r/inst/extdata/ were gitignored; only the
directory structure (via .gitkeep files) was tracked. The
local developer populated them by running
Rscript r/data-raw/sync_data.R before
R CMD build, so the CRAN / Bioconductor tarballs would have
shipped them — but remotes::install_github() builds from
the git tree, where those files were absent. The result: install
succeeds, but
system.file("extdata", "models", "json", package = "vennDiagramLab", mustWork = TRUE)
returns "", and the first analyze() call
throws the cryptic mustWork error.
The fix tracks the synced data files in git (root
.gitignore updated), so install_github now
produces a working install out of the box. The synced files are
regenerated and committed as part of the release workflow; the
r/data-raw/sync_data.R script remains the single source of
truth.
.models_json_dir() (internal) replaced the cryptic
mustWork = TRUE error with an actionable message walking
the user through the clone + sync + R CMD INSTALL workflow
as a fallback. This branch is now defensive — the gitignore fix removed
the trigger — but mis-built installs (hand-edited package directories,
missing rebuilds after a model change) will still see a useful message
instead of "no file found".No public-API changes. No new features.
First public release. Headless companion to the Venn Diagram Lab web tool and
the Python
venn-diagram-lab package, targeting CRAN +
Bioconductor.
VennDataset, RegionData,
RegionResult, StatisticsResult — four S4
classes covering inputs, regions, results, and pairwise statistics.load_csv,
load_tsv, load_gmt, load_gmx)
plus load_sample / list_samples for five
bundled datasets (3 biological, 2 mock).analyze(dataset, model = "auto") — region enumeration
via integer bitmask, model resolution mirroring the web tool.statistics(result) — lazy StatisticsResult
with five pairwise metrics: Jaccard, Dice, overlap coefficient, fold
enrichment, hypergeometric p-value (BH-FDR adjusted).jaccard(),
dice(), overlap_coefficient(),
hypergeometric_p_value(), fold_enrichment(),
bh_fdr(), compute_pairwise().effective_universe(result) — universe N consistent with
the web tool’s binary/aggregated semantics.to_region_summary_tsv(), to_matrix_tsv(),
to_statistics_tsv() — three byte-equivalent writers
matching the React webapp’s TSV exports.dataset_mock_streaming_platforms is xfail-strict due to the
documented row-vs-set divergence in the web tool’s loader.render_venn_svg(result, ...) — templates the bundled
44-model SVG library via xml2 (Count_*, Name*,
Bullet*, Shape* substitution).set_names, colors,
title, show_names, show_counts
overrides per render.analyze(ds, model = "proportional") — area-proportional
2-set (exact) and 3-set (approximate) generator with
solve_2set, solve_3set,
circle_intersection_area,
generate_proportional_svg helpers.render_upset(result, ...) —
ComplexUpset-based UpSet plot with sort modes
(size, degree), color modes
(depth, heatmap, custom), and
threshold / max_columns cutoffs.render_network(result, ...) — force-directed network
via tidygraph + ggraph. Edge metric
configurable (intersection, jaccard,
fold_enrichment, overlap_coefficient);
significance threshold colorizes edges.to_pdf_report(result, path, ...) — multi-page
US-Letter-landscape PDF combining venn + UpSet + statistics + network +
about pages, generated via grDevices::pdf +
patchwork.include_network and include_about.geom_venn(data, ...) — embed a rendered venn as a
ggplot2 layer (annotation_custom + geom_blank + coord_fixed).tidy.RegionResult(),
glance.RegionResult(), augment.RegionResult()
— broom-compatible S3 methods returning tibbles.broom and tibble are Suggests-only
(registered via @exportS3Method) — users not in the
tidyverse pay zero install cost.R CMD check --as-cran:
v01_quickstart — five-step introv02_real_cancer_drivers — long-form biological
walkthrough (Vogelstein / COSMIC / OncoKB / IntOGen)v03_proportional_diagrams — when to use
area-proportional + low-level helpersv04_upset_vs_venn_vs_network — choosing the right
visualizationv05_statistics_deep_dive — Jaccard / Dice /
hypergeometric / BH-FDR workedv06_pipeline_integration — broom + dplyr + targets
pipeline sketchv07_pdf_reports — composite PDF generationv08_custom_styling_and_export — custom names/colors,
geom_venn, multi-format exportrender_upset() and
to_pdf_report() emit a runtime warning about an upstream
ComplexUpset 1.3.3 / ggplot2 4.x
incompatibility (tracking krassowski/complex-upset#213).
Vignette chunks that depend on UpSet rendering are gated on
eval = (getRversion() >= "4.6"). The warning + skip will
be removed when ComplexUpset 1.4+ ships.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.