STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
dynwrap vs GeneNMF
A side-by-side editorial comparison of dynwrap and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:bioinformatics
dynwrap vs GeneNMF: at a glance
What is dynwrap?
A dormant trajectory-inference wrapper wakes up for maintenance only
dynwrap is the dynverse component that wraps single-cell trajectory inference methods behind a common interface, handling containerised method execution and the trajectory data model. The visible history is dominated by a burst of feature work in 2019 and then near-silence: the only recent release, v1.3.0, is a package modernisation with a minimum-version bump and no user-facing capability. The three entries in the feed span seven years.
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.
dynwrap vs GeneNMF: editorial side-by-side
dynwrap
0.0ANALYTICS
A dormant trajectory-inference wrapper wakes up for maintenance only
◆ Current state
dynwrap is the dynverse component that wraps single-cell trajectory inference methods behind a common interface, handling containerised method execution and the trajectory data model. The visible history is dominated by a burst of feature work in 2019 and then near-silence: the only recent release, v1.3.0, is a package modernisation with a minimum-version bump and no user-facing capability. The three entries in the feed span seven years.
◆ Where it's heading
The direction is custodial rather than developmental. The 2019 releases built out the substance — RNA velocity in the wrapper, velocity-oriented topologies, directed geodesic distances, Singularity 3.0 and sparse matrices throughout — and nothing since has extended it. The 2026 release reads as keeping the package installable against a modern R toolchain, which is what a maintained dependency of a benchmark suite needs rather than what an actively developed tool looks like.
◆ Prediction
On this evidence, expect further releases to be compatibility maintenance triggered by R or dependency changes; the entries give no indication of resumed feature work.
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 dynwrap 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 dynwrap 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 dynwrap alternatives → · See all GeneNMF alternatives →
Recent activity from dynwrap and GeneNMF
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agodynwrapPackage modernisation, no user-facing change
- 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
- 7y agodynwrapRNA velocity support and directed geodesic distances
- 7y agodynwrap1.0.0: Singularity 3.0 only, sparse matrices throughout
Frequently asked questions
What is the difference between dynwrap and GeneNMF?
Both compete on the same themes — bioinformatics — within Analytics. dynwrap 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 dynwrap better than GeneNMF?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dynwrap 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 dynwrap?
Top dynwrap alternatives in Analytics are ranked by recent ship velocity. Browse the "dynwrap alternatives" section above for the current picks, or visit /alternatives/dynwrap 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.