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Comparison · Analytics

GeneNMF vs simmer.plot

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

Shared themes:r-package

GeneNMF vs simmer.plot: at a glance

FeatureGeneNMFsimmer.plot
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessingle-cell-genomics, nmf, gene-programs, bioinformaticsdiscrete-event-simulation, simmer, ggplot2, visualisation
Last editorial update1h ago46m 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 simmer.plot?

The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.

simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.

Read the full simmer.plot trajectory →

GeneNMF vs simmer.plot: 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
simmer.plot
ANALYTICS
0.0

The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.

◆ Current state

simmer.plot renders discrete-event simulation output — S3 plot() methods over get_mon_arrivals(), get_mon_attributes() and get_mon_resources(), plus trajectory diagrams drawn through DiagrammeR. Since 0.1.12 the methods attach to the monitoring data itself rather than the simulation environment, and 0.1.18 finished that migration by deleting the deprecated environment-level methods.

◆ Where it's heading

This package moves when something it depends on moves. Its history is a sequence of parser fixes for new simmer trajectory formats, DiagrammeR and tidyr and dplyr version bumps, and ggplot2 workarounds. The one clear internal decision — plotting monitor output instead of the environment — was made in 2017 and completed six years later. The 2025 release fixes documentation cross-references and nothing else.

◆ Prediction

The next release most likely follows a simmer trajectory-format change or a CRAN documentation policy, matching every recent entry. There is no visible feature work in the pipeline.

Alternatives to GeneNMF and simmer.plot

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 simmer.plot.

See all GeneNMF alternatives → · See all simmer.plot alternatives →

Recent activity from GeneNMF and simmer.plot

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

  1. 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
  2. 1y agosimmer.plotDocumentation cross-reference fixes
  3. 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
  4. 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
  5. 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity
  6. 2y agoGeneNMFFirst stable release published to CRAN
  7. 3y agosimmer.plotActivity tags and named rollbacks; deprecated plot methods removed
  8. 4y agosimmer.plotZero-capacity utilization fixed; usage limits exposed
  9. 6y agosimmer.plotRollback pointer fix and upstream bug workarounds
  10. 8y agosimmer.plotResource plot factors keep the supplied order
  11. 8y agosimmer.plotUpdate for DiagrammeR 1.0.0

Frequently asked questions

What is the difference between GeneNMF and simmer.plot?

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

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

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