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GeneNMF vs silx

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

GeneNMF vs silx: at a glance

FeatureGeneNMFsilx
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themessingle-cell-genomics, nmf, gene-programs, bioinformaticsscientific-computing, data-visualization, synchrotron, qt
Last editorial update1d ago2h 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 silx?

silx settles into maintenance a release after its PySide6 migration

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

Read the full silx trajectory →

GeneNMF vs silx: 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
silx
ANALYTICS
5.0

silx settles into maintenance a release after its PySide6 migration

◆ Current state

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

◆ Where it's heading

The cadence has slowed markedly since April, and the content has shifted from structural change to plotting and colormap refinement. That is the expected shape after a binding migration: downstream beamline code needs a stable target, so the project trades feature velocity for a quiet surface. The gap between 3.0.1 in May and 3.1.0 in August is the clearest signal of the deliberate slowdown.

◆ Prediction

Expect further point releases servicing the plotting and fitting widgets rather than another structural change, with feature work continuing to arrive in the 3.1.x minors rather than patches.

Alternatives to GeneNMF and silx

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 silx.

See all GeneNMF alternatives → · See all silx alternatives →

Recent activity from GeneNMF and silx

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

  1. 5h agosilxFitWidget fix for loading a fit function from file
  2. 9d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
  3. 3mo agosilx3.0.1: silx view fails to disable HDF5 file locking
  4. 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required
  5. 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
  6. 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
  7. 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
  8. 1y agosilx2.2.2: plot axes limits, OpenGL axes and libhdf5 1.14 fixes
  9. 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
  10. 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity
  11. 2y agoGeneNMFFirst stable release published to CRAN

Frequently asked questions

What is the difference between GeneNMF and silx?

They serve adjacent needs but don't currently overlap on shipped themes. silx is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is GeneNMF better than silx?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. silx is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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 silx?

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