STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
eulerr vs GeneNMF
A side-by-side editorial comparison of eulerr and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
eulerr vs GeneNMF: at a glance
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.
What is GeneNMF?
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
GeneNMF applies non-negative matrix factorization to single-cell expression data to find gene programs, then consolidates programs recurring across samples into meta-programs. Version 0.6.0 replaced the consolidation method: instead of reducing each program to a gene set and taking a consensus, it retains full gene weight vectors and compares them by cosine similarity. Later releases have built reporting and control around that core — a metaprogram composition matrix showing which samples contributed, custom signature databases for enrichment testing, and the ability to drop meta-programs from results.
eulerr vs GeneNMF: editorial side-by-side
eulerr
0.0ANALYTICS
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.
GeneNMF
0.0ANALYTICS
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
◆ Current state
GeneNMF applies non-negative matrix factorization to single-cell expression data to find gene programs, then consolidates programs recurring across samples into meta-programs. Version 0.6.0 replaced the consolidation method: instead of reducing each program to a gene set and taking a consensus, it retains full gene weight vectors and compares them by cosine similarity. Later releases have built reporting and control around that core — a metaprogram composition matrix showing which samples contributed, custom signature databases for enrichment testing, and the ability to drop meta-programs from results.
◆ Where it's heading
The package is moving from producing meta-programs to letting users interrogate and constrain how they were formed. Composition matrices, the drop function and downsampled similarity heatmaps all serve inspection rather than derivation. The parameters added alongside the 0.6.0 rewrite — specificity weighting, cumulative weight thresholds, confidence defined as the fraction of programs containing a gene — turn what were fixed internal choices into stated, tunable ones.
◆ Prediction
Recent releases have been fixes and compatibility work rather than method changes, so the core approach appears settled. The dependency on an RcppML version not on CRAN is the loose end most likely to force the next release.
Alternatives to eulerr and GeneNMF
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 GeneNMF.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all eulerr alternatives → · See all GeneNMF alternatives →
Recent activity from eulerr and GeneNMF
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agoeulerrConfig file added to Rbuildignore to clear a check warning
- 10mo agoeulerrDeprecated Armadillo call replaced and doc links repaired
- 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
- 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
- 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
- 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity ⚡
- 2y agoeulerrStrip order and layout corrected for grouped diagrams
- 2y agoGeneNMFFirst stable release published to CRAN
- 2y agoeulerrInternal documentation and a stale link corrected
- 3y agoeulerrLayout optimization gains a selectable loss function
- 4y agoeulerrCitation added and error messages improved
Frequently asked questions
What is the difference between eulerr and GeneNMF?
Both compete on the same themes — r-package — within Analytics. eulerr and GeneNMF 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 GeneNMF?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. eulerr and GeneNMF 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 GeneNMF?
Top GeneNMF alternatives in Analytics are ranked by recent ship velocity. Browse the "GeneNMF alternatives" section above for the current picks, or visit /alternatives/genenmf for the full list with editorial commentary on each.