STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
GeneNMF vs rainette
A side-by-side editorial comparison of GeneNMF and rainette — release velocity, themes, recent moves, and the top alternatives to consider.
GeneNMF vs rainette: at a glance
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.
What is rainette?
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
An R implementation of the Reinert textual clustering method, with interactive explorers for browsing clusters. The two substantive releases are behind it: 0.2.0 renamed the core segment-size arguments, fixed segment merging that had been crossing document boundaries, and added a document browser plus per-document cluster tables; 0.3.0 reworked the double classification in rainette2() with full and parallel arguments and much faster computation. The 2026 release is a vctrs compatibility fix plus a colors argument on rainette_plot().
GeneNMF vs rainette: editorial side-by-side
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.
rainette
0.0ANALYTICS
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
◆ Current state
An R implementation of the Reinert textual clustering method, with interactive explorers for browsing clusters. The two substantive releases are behind it: 0.2.0 renamed the core segment-size arguments, fixed segment merging that had been crossing document boundaries, and added a document browser plus per-document cluster tables; 0.3.0 reworked the double classification in rainette2() with full and parallel arguments and much faster computation. The 2026 release is a vctrs compatibility fix plus a colors argument on rainette_plot().
◆ Where it's heading
The package moved from correct-enough to trustworthy and then to maintained: results-changing fixes first, performance and options second, and now only upstream compatibility and small user-requested arguments. Wordcloud plots were flagged for deprecation in 0.3.0 and pulled from the explorers, narrowing the output surface rather than growing it. The same maintainer's questionr followed the same pattern in the same period.
◆ Prediction
The deprecated wordcloud plot type is the obvious removal candidate, since it has carried a warning since 0.3.0 and has already been dropped from the interactive explorers.
Alternatives to GeneNMF and rainette
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 GeneNMF or rainette.
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 GeneNMF alternatives → · See all rainette alternatives →
Recent activity from GeneNMF and rainette
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agorainettevctrs compatibility fix and custom cluster colors
- 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 agoGeneNMFFirst stable release published to CRAN
- 3y agorainetteR 3.6 palette compatibility and dendrogram fix
- 4y agorainetteDouble classification reworked with restricted crossings and parallelism
- 4y agorainetteMerged segments visible in the document browser
- 4y agorainetteCRAN v0.2.0 ⚡
Frequently asked questions
What is the difference between GeneNMF and rainette?
They serve adjacent needs but don't currently overlap on shipped themes. GeneNMF and rainette 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 GeneNMF better than rainette?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GeneNMF and rainette 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 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.
What are the best alternatives to rainette?
Top rainette alternatives in Analytics are ranked by recent ship velocity. Browse the "rainette alternatives" section above for the current picks, or visit /alternatives/rainette for the full list with editorial commentary on each.