STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
fect vs GeneNMF
A side-by-side editorial comparison of fect and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fect vs GeneNMF: at a glance
What is fect?
A counterfactual estimator turning itself into a platform for multiple estimands
fect implements counterfactual estimators for panel data with treatment effects — imputation-based fixed effects, interactive fixed effects, matrix completion. The 2026 releases move fast and bundle heavily: 2.1.0 rewrote complex fixed effect handling, 2.2.0 unified cross-validation under a single cv.method parameter and replaced method='gsynth' with an explicit time.component.from switch, 2.4.1 introduced a post-hoc estimand API, and 2.4.5 added group.fe for coarsened fixed effects plus a $sample slot exposing which cells entered estimation.
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.
fect vs GeneNMF: editorial side-by-side
fect
0.0ANALYTICS
A counterfactual estimator turning itself into a platform for multiple estimands
◆ Current state
fect implements counterfactual estimators for panel data with treatment effects — imputation-based fixed effects, interactive fixed effects, matrix completion. The 2026 releases move fast and bundle heavily: 2.1.0 rewrote complex fixed effect handling, 2.2.0 unified cross-validation under a single cv.method parameter and replaced method='gsynth' with an explicit time.component.from switch, 2.4.1 introduced a post-hoc estimand API, and 2.4.5 added group.fe for coarsened fixed effects plus a $sample slot exposing which cells entered estimation.
◆ Where it's heading
The direction is separation of estimation from interpretation. Where the package once returned one effect from one fit, estimand() now dispatches typed estimands — ATT, cumulative ATT, APTT, log ATT — from any imputation fit, with effect() and att.cumu() soft-deprecated but byte-identical pending 3.0.0. Alongside that runs a transparency thread: the $sample matrix, out-of-sample comparison via fect_mspe(), and named component sources instead of opaque method aliases. The release notes are unusually precise about which results change and which do not.
◆ Prediction
The soft-deprecation notice names 3.0.0 as the removal point for effect() and att.cumu(), so a major release consolidating on the estimand() dispatcher is the clearly signposted next step.
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 fect 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 fect 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 fect alternatives → · See all GeneNMF alternatives →
Recent activity from fect and GeneNMF
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agofectAdds group.fe for coarsened fixed effects and a $sample slot
- 3mo agofectPost-hoc estimand API decouples estimands from the fit ⚡
- 4mo agofectUnified cross-validation and explicit control of time components
- 7mo agofectRewrites complex fixed effect handling and fixes speed
- 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
- 11mo agofectAdds heterogeneous treatment effect plots and caps default cores
- 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
Frequently asked questions
What is the difference between fect and GeneNMF?
Both compete on the same themes — r-package — within Analytics. fect 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 fect better than GeneNMF?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fect 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 fect?
Top fect alternatives in Analytics are ranked by recent ship velocity. Browse the "fect alternatives" section above for the current picks, or visit /alternatives/fect 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.