STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
GeneNMF vs semmcci
A side-by-side editorial comparison of GeneNMF and semmcci — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
GeneNMF vs semmcci: 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 semmcci?
Monte Carlo confidence intervals for SEM, now mostly reacting to upstream deprecations
semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.
GeneNMF vs semmcci: 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.
semmcci
0.0ANALYTICS
Monte Carlo confidence intervals for SEM, now mostly reacting to upstream deprecations
◆ Current state
semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.
◆ Where it's heading
The functional build-out finished some time ago. MCGeneric() in 1.1.3 and Func()/MCFunc() in 1.1.4 opened the package to user-defined functions of parameters, which is the natural end point for a Monte Carlo interval tool — once arbitrary functions are supported, there is little left to add. Since then releases have tracked lavaan's changes rather than semmcci's own direction, and the gap between them has stretched from months to over a year.
◆ Prediction
Expect the next release to be triggered by another lavaan deprecation rather than by new capability.
Alternatives to GeneNMF and semmcci
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 semmcci.
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 semmcci alternatives →
Recent activity from GeneNMF and semmcci
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agosemmccilavaan getCov() deprecation handled in tests
- 10mo agosemmcciMinor method edits
- 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 agosemmcciUser-defined parameter functions via Func() and MCFunc()
- 2y agoGeneNMFFirst stable release published to CRAN
- 2y agosemmcciMCGeneric() opens up arbitrary parameter targets
- 3y agosemmcciMultiple-imputation support via MCMI()
- 3y agosemmcciData generation internals refactored
Frequently asked questions
What is the difference between GeneNMF and semmcci?
Both compete on the same themes — r-package — within Analytics. GeneNMF and semmcci 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 semmcci?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GeneNMF and semmcci 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 semmcci?
Top semmcci alternatives in Analytics are ranked by recent ship velocity. Browse the "semmcci alternatives" section above for the current picks, or visit /alternatives/semmcci for the full list with editorial commentary on each.