← Back to home
Comparison · Analytics

eulerr vs STACAS

A side-by-side editorial comparison of eulerr and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

eulerr vs STACAS: at a glance

FeatureeulerrSTACAS
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themeseuler-diagrams, set-visualization, optimization, cpp-backendsingle-cell, batch-correction, data-integration, seurat
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is eulerr?

The area-proportional Euler diagram package is finished software, and maintained like it.

eulerr generates area-proportional Euler and Venn diagrams by numerically optimizing shape positions and sizes to match set relationships, with the fitting done in C++. The last feature release was 7.0.0 in December 2022, which made the optimization's loss function user-selectable. Everything since has been maintenance: documentation URL corrections, a strip-layout fix when grouping, an Armadillo deprecation, and an R CMD check warning about an unignored config file.

Read the full eulerr trajectory →

What is STACAS?

Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.

STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.

Read the full STACAS trajectory →

eulerr vs STACAS: editorial side-by-side

E
eulerr
ANALYTICS
0.0

The area-proportional Euler diagram package is finished software, and maintained like it.

◆ Current state

eulerr generates area-proportional Euler and Venn diagrams by numerically optimizing shape positions and sizes to match set relationships, with the fitting done in C++. The last feature release was 7.0.0 in December 2022, which made the optimization's loss function user-selectable. Everything since has been maintenance: documentation URL corrections, a strip-layout fix when grouping, an Armadillo deprecation, and an R CMD check warning about an unignored config file.

◆ Where it's heading

This is a mature package whose problem is solved, and the release pattern reflects that — three of the last four releases changed nothing a user would see. What activity remains is tracking its dependencies rather than its own roadmap: keeping up with Armadillo's deprecations and R CMD check policy is the whole of recent work. The two September 2025 releases an hour apart are a fix and its follow-up, not a development cycle restarting.

◆ Prediction

The pattern points to continued upkeep triggered by upstream C++ and CRAN check changes rather than new capability. If anything does move, the configurable loss function added in 7.0.0 is the surface with room left in it.

S
STACAS
ANALYTICS
0.0

Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.

◆ Current state

STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.

◆ Where it's heading

The method work concentrated in version 2.0 and has been stable since; everything after is Seurat compatibility and operational robustness. Versions 2.1.1 through 2.3.0 track Seurat v5 assays, v3-to-v5 conversion, multi-layer objects and SCT normalisation, with the genuinely useful additions — a reference seed dataset, max.seed.datasets for large-scale integration, min.sample.size — arriving as side effects of that work. The package is from the same lab as GeneNMF, and its release rhythm follows the single-cell ecosystem's upstream churn rather than an internal roadmap.

◆ Prediction

Expect the next release to follow further Seurat object-model changes, which have driven the last three. Nothing in the entries indicates new anchor-scoring or correction methodology in progress.

Alternatives to eulerr and STACAS

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either eulerr or STACAS.

See all eulerr alternatives → · See all STACAS alternatives →

Recent activity from eulerr and STACAS

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 10mo agoeulerrConfig file added to Rbuildignore to clear a check warning
  2. 10mo agoeulerrDeprecated Armadillo call replaced and doc links repaired
  3. 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
  4. 2y agoeulerrStrip order and layout corrected for grouped diagrams
  5. 2y agoeulerrInternal documentation and a stale link corrected
  6. 2y agoSTACASscale.data option for extreme batch effects; gene name conversion table
  7. 3y agoSTACASReference seeding, gene symbol standardisation, large-scale integration path
  8. 3y agoeulerrLayout optimization gains a selectable loss function
  9. 4y agoSTACASSemi-supervised integration and rPCA anchor downweighting
  10. 4y agoeulerrCitation added and error messages improved
  11. 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support

Frequently asked questions

What is the difference between eulerr and STACAS?

Both compete on the same themes — r-package — within Analytics. eulerr and STACAS are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is eulerr better than STACAS?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. eulerr and STACAS are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to eulerr?

Top eulerr alternatives in Analytics are ranked by recent ship velocity. Browse the "eulerr alternatives" section above for the current picks, or visit /alternatives/eulerr for the full list with editorial commentary on each.

What are the best alternatives to STACAS?

Top STACAS alternatives in Analytics are ranked by recent ship velocity. Browse the "STACAS alternatives" section above for the current picks, or visit /alternatives/stacas for the full list with editorial commentary on each.