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Comparison · Analytics

b3gbi vs GeneNMF

A side-by-side editorial comparison of b3gbi and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.

b3gbi vs GeneNMF: at a glance

Featureb3gbiGeneNMF
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesbiodiversity, gbif, uncertainty, bootstrappingsingle-cell-genomics, nmf, gene-programs, bioinformatics
Last editorial update7h ago1h ago
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What is b3gbi?

b3gbi pulled confidence intervals out of its indicator workflow and handed them to dubicube.

b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.

Read the full b3gbi trajectory →

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 →

b3gbi vs GeneNMF: editorial side-by-side

B
b3gbi
ANALYTICS
2.5

b3gbi pulled confidence intervals out of its indicator workflow and handed them to dubicube.

◆ Current state

b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.

◆ Where it's heading

Two forces are shaping releases. Internally, the uncertainty split produced an indicator-specific rule book — species-level indicators bootstrap the whole cube, raw counts resample within year, evenness gets a logit transform — and that rule book is where the statistical thinking now lives. Externally, GBIF's taxonomic backbone migration to the Catalogue of Life forced string taxon keys through process_cube() and the plotting paths, while recurring EEA and MGRS grid-code fixes mark coordinate parsing as the least settled area.

◆ Prediction

The 0.9.4 notes are entirely JOSS review items — contributors, examples, tracked datasets — so the next release is most likely a JOSS-accepted 1.0 rather than new indicator work.

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.

Alternatives to b3gbi 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 b3gbi or GeneNMF.

See all b3gbi alternatives → · See all GeneNMF alternatives →

Recent activity from b3gbi and GeneNMF

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

  1. 4d agob3gbiJOSS review fixes: contributors, examples, tracked data
  2. 1mo agob3gbiEEA grid coordinates no longer scaled by resolution
  3. 1mo agob3gbiadd_ci() no longer crashes on completeness indicators
  4. 1mo agob3gbiString taxon keys for GBIF's Catalogue of Life backbone
  5. 1mo agob3gbiUncertainty split out of the indicator workflow into add_ci()
  6. 1mo agob3gbiFAIR column mapping doc and Zenodo DOI badge
  7. 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
  8. 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
  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 b3gbi and GeneNMF?

They serve adjacent needs but don't currently overlap on shipped themes. b3gbi is currently shipping more aggressively (velocity 2.5 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 b3gbi better than GeneNMF?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. b3gbi is currently shipping more aggressively (velocity 2.5 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 b3gbi?

Top b3gbi alternatives in Analytics are ranked by recent ship velocity. Browse the "b3gbi alternatives" section above for the current picks, or visit /alternatives/b3gbi 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.