STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
Comparison · Analytics
bbk vs GeneNMF
A side-by-side editorial comparison of bbk and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
bbk vs GeneNMF: at a glance
What is bbk?
One R interface is absorbing the world's central bank data portals, one API at a time.
bbk began as a Bundesbank client and has become a single R interface to central bank statistics generally: the ECB, BIS, and the national banks of Switzerland, Canada, the UK, France, Spain, Austria, Sweden, Norway, Portugal, Japan, Poland, the Czech Republic, and now Brazil and Mexico. Each provider gets a consistent set of verbs — a data function, a dimension function for the dataflow structure, and provider-specific extras like PRIBOR or CZEONIA fixings. Response caching, data.table returns, and an updated_after argument for incremental retrieval are shared plumbing rather than per-provider features.
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.
bbk vs GeneNMF: editorial side-by-side
bbk
0.0ANALYTICS
One R interface is absorbing the world's central bank data portals, one API at a time.
◆ Current state
bbk began as a Bundesbank client and has become a single R interface to central bank statistics generally: the ECB, BIS, and the national banks of Switzerland, Canada, the UK, France, Spain, Austria, Sweden, Norway, Portugal, Japan, Poland, the Czech Republic, and now Brazil and Mexico. Each provider gets a consistent set of verbs — a data function, a dimension function for the dataflow structure, and provider-specific extras like PRIBOR or CZEONIA fixings. Response caching, data.table returns, and an updated_after argument for incremental retrieval are shared plumbing rather than per-provider features.
◆ Where it's heading
The expansion is steady and the integration work is what makes it more than a list of wrappers: arguments introduced for one provider get pushed to the others, dimension introspection is being generalised across dataflows, and the bug fixes in recent releases are almost all about the same class of problem — series with missing observations, unsupported frequency codes, or date/value misalignment breaking a parser written for a tidier feed. The maintainer ships the same infrastructure across their packages in lockstep; bbk 0.9.0 and the sibling treasury package's 0.5.0 landed identical opt-in caching within minutes of each other. Geography is the visible frontier, but consistency across an increasingly ragged set of upstream APIs is the actual work.
◆ Prediction
Expect more national central banks to be added on the same template, and the newer providers to be retrofitted with the dimension and updated_after functions the older ones already have.
GeneNMF
0.0ANALYTICS
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 bbk 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 bbk or GeneNMF.
ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
Recent activity from bbk and GeneNMF
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agobbkBrazil and Mexico join, bringing survey expectations data ⚡
- 2mo agobbkCzech National Bank support lands with a broad parser repair
- 3mo agobbkIncremental retrieval generalised beyond the ECB endpoint
- 4mo agobbkOpt-in response caching plus dimension introspection everywhere
- 10mo agobbkBank of Canada data and exchange rates added
- 11mo agoGeneNMFSingle-sample runs fixed; gene weight definition refined
- 11mo agobbkFour European central banks added; validation moves to checkmate
- 1y agoGeneNMFMetaprogram composition exposed and custom signature DBs supported
- 1y agoGeneNMFSimilarity heatmap downsampling and meta-program removal
- 2y agoGeneNMFMeta-programs rebuilt on gene weight vectors and cosine similarity ⚡
- 2y agoGeneNMFFirst stable release published to CRAN
Frequently asked questions
What is the difference between bbk and GeneNMF?
Both compete on the same themes — r-package — within Analytics. bbk and GeneNMF 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 bbk better than GeneNMF?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. bbk and GeneNMF 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 bbk?
Top bbk alternatives in Analytics are ranked by recent ship velocity. Browse the "bbk alternatives" section above for the current picks, or visit /alternatives/bbk 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.