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GeneNMF vs skylight

A side-by-side editorial comparison of GeneNMF and skylight — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

GeneNMF vs skylight: at a glance

FeatureGeneNMFskylight
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessingle-cell-genomics, nmf, gene-programs, bioinformaticsastronomy, illuminance, cpp-port, scientific-computing
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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.

Read the full GeneNMF trajectory →

What is skylight?

A frozen astronomical model quietly became the inner loop of its sibling's optimizer.

skylight returns sun and moon illuminance, azimuth and altitude for a given date, time and location, implemented as a near-verbatim transcription of a 1987 US Naval Observatory circular. The model formulation has not changed since the initial 2022 release and the author states so explicitly. Everything shipped since has been packaging, citation and speed: v1.3 moved the main routine from R to C++, and v1.4 removed a parameter check that was flooding the console with messages.

Read the full skylight trajectory →

GeneNMF vs skylight: editorial side-by-side

G
GeneNMF
ANALYTICS
0.0

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.

S
skylight
ANALYTICS
0.0

A frozen astronomical model quietly became the inner loop of its sibling's optimizer.

◆ Current state

skylight returns sun and moon illuminance, azimuth and altitude for a given date, time and location, implemented as a near-verbatim transcription of a 1987 US Naval Observatory circular. The model formulation has not changed since the initial 2022 release and the author states so explicitly. Everything shipped since has been packaging, citation and speed: v1.3 moved the main routine from R to C++, and v1.4 removed a parameter check that was flooding the console with messages.

◆ Where it's heading

This is a reference implementation of a published algorithm rather than a product accumulating features, and it is being maintained that way. The movement that does occur is driven from downstream: the C++ port was written for the inverse-modelling loop in the sibling skytrackr package, which calls skylight repeatedly during optimization. That reframes skylight from a standalone calculator into the compute kernel another package's fitting routine depends on.

◆ Prediction

With the model formulation deliberately fixed and the C++ path already in place, the next release is most likely another small maintenance fix. The entries give no indication of planned new capability.

Alternatives to GeneNMF and skylight

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 skylight.

See all GeneNMF alternatives → · See all skylight alternatives →

Recent activity from GeneNMF and skylight

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 9mo agoskylightNoisy parameter check removed from console output
  2. 10mo agoskylightCore routine moves from R to C++ for repeated-call speed
  3. 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
  4. 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
  5. 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
  6. 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity
  7. 2y agoGeneNMFFirst stable release published to CRAN
  8. 2y agoskylightCitation updated after the companion paper published
  9. 3y agoskylightSkylight v1.1
  10. 3y agoskylightFirst release: sun and moon illuminance from the 1987 USNO circular

Frequently asked questions

What is the difference between GeneNMF and skylight?

Both compete on the same themes — r-package — within Analytics. GeneNMF and skylight 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 skylight?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GeneNMF and skylight 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 skylight?

Top skylight alternatives in Analytics are ranked by recent ship velocity. Browse the "skylight alternatives" section above for the current picks, or visit /alternatives/skylight for the full list with editorial commentary on each.