STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
GeneNMF vs ggtrace
A side-by-side editorial comparison of GeneNMF and ggtrace — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
GeneNMF vs ggtrace: 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 ggtrace?
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
GeneNMF vs ggtrace: 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.
ggtrace
0.0ANALYTICS
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
◆ Current state
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
◆ Where it's heading
The package matured from raw tracing primitives into named workflows: 0.6.0 added the sublayer snapshot functions and error-context helpers, 0.7.x has been sanding down how reliably those workflows find and evaluate a method. Three consecutive releases in May 2025, two of them minutes apart, all address the same class of failure — one-liner ggproto methods without braces, and inheritance resolution on instances rather than subclasses. That pattern says the remaining bugs are in method introspection, not in the tracing machinery itself.
◆ Prediction
Expect continued fixes to method resolution as ggplot2's ggproto definitions vary, and realignment work when ggplot2 4.x changes internals this package deliberately reaches into. The entries do not signal new workflow functions.
Alternatives to GeneNMF and ggtrace
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 ggtrace.
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.
eiaapi
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all GeneNMF alternatives → · See all ggtrace alternatives →
Recent activity from GeneNMF and ggtrace
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
- 1y agoggtraceBrace-less one-liner methods traced gracefully
- 1y agoggtraceget_method_inheritance() fixed for class instances
- 1y agoggtraceWorkflow functions recognise one-liner ggproto methods
- 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
- 1y agoggtraceEager layer_is(), clearer method-mismatch errors, consistent tracedump names
- 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
- 1y agoggtracetrace_steps = "all" added; double-evaluation side effects fixed
- 1y agoggtracelayer_is() targets by_layer() downstream directly
- 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity ⚡
- 2y agoGeneNMFFirst stable release published to CRAN
Frequently asked questions
What is the difference between GeneNMF and ggtrace?
Both compete on the same themes — r-package — within Analytics. GeneNMF and ggtrace 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 ggtrace?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GeneNMF and ggtrace 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 ggtrace?
Top ggtrace alternatives in Analytics are ranked by recent ship velocity. Browse the "ggtrace alternatives" section above for the current picks, or visit /alternatives/ggtrace for the full list with editorial commentary on each.