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GeneNMF vs invasimapr

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

GeneNMF vs invasimapr: at a glance

FeatureGeneNMFinvasimapr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessingle-cell-genomics, nmf, gene-programs, bioinformaticsinvasion ecology, species traits, biodiversity, research software
Last editorial update53m ago6h ago
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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 invasimapr?

invasimapr halved its install size and became citable; the science stayed put.

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

Read the full invasimapr trajectory →

GeneNMF vs invasimapr: 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.

I
invasimapr
ANALYTICS
0.0

invasimapr halved its install size and became citable; the science stayed put.

◆ Current state

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

◆ Where it's heading

The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.

◆ Prediction

Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.

Alternatives to GeneNMF and invasimapr

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 invasimapr.

See all GeneNMF alternatives → · See all invasimapr alternatives →

Recent activity from GeneNMF and invasimapr

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

  1. 1mo agoinvasimaprVersion bump; notes identical to 0.2.0
  2. 1mo agoinvasimaprB-Cubed standards alignment; install slimmed to 56 MB
  3. 1mo agoinvasimaprinvasimapr v0.1.0: First citable release
  4. 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
  5. 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
  6. 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
  7. 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity
  8. 2y agoGeneNMFFirst stable release published to CRAN

Frequently asked questions

What is the difference between GeneNMF and invasimapr?

They serve adjacent needs but don't currently overlap on shipped themes. GeneNMF and invasimapr 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 invasimapr?

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

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