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GeneNMF vs qtl2convert

A side-by-side editorial comparison of GeneNMF and qtl2convert — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

GeneNMF vs qtl2convert: at a glance

FeatureGeneNMFqtl2convert
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessingle-cell-genomics, nmf, gene-programs, bioinformaticsr-package, genetics, format-conversion, cran-maintenance
Last editorial update50m ago4h 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 qtl2convert?

A conversion utility in pure maintenance mode, tracking R-devel breakage release by release

qtl2convert is the format-shim of the R/qtl2 ecosystem: it moves genotype probabilities and genetic maps between DOQTL, R/qtl and R/qtl2 representations. The last three releases contain no new conversion functions at all — 0.32 fixed a C string comparison flagged by CRAN, 0.34 restored attribute-clearing that R-devel 4.7 changed underneath the package, and 0.36 adjusted parallel core defaults plus a test tweak. The functional surface has been stable since 0.26 added cross2_ril_to_genril().

Read the full qtl2convert trajectory →

GeneNMF vs qtl2convert: 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.

Q
qtl2convert
ANALYTICS
0.0

A conversion utility in pure maintenance mode, tracking R-devel breakage release by release

◆ Current state

qtl2convert is the format-shim of the R/qtl2 ecosystem: it moves genotype probabilities and genetic maps between DOQTL, R/qtl and R/qtl2 representations. The last three releases contain no new conversion functions at all — 0.32 fixed a C string comparison flagged by CRAN, 0.34 restored attribute-clearing that R-devel 4.7 changed underneath the package, and 0.36 adjusted parallel core defaults plus a test tweak. The functional surface has been stable since 0.26 added cross2_ril_to_genril().

◆ Where it's heading

This is a package whose release cadence is driven by its dependencies, not its roadmap. Two of the last three releases exist purely because upstream R or CRAN's check suite moved; the maintainer responds within weeks and ships. The cores=0 change in 0.36 is the only user-visible behavior shift in over a year, and it landed simultaneously in sibling package qtl2fst — this is a maintainer-wide convention change, not a qtl2convert decision.

◆ Prediction

Expect the next release to be triggered by another R-devel or CRAN check change rather than a feature request, following the same pattern as 0.32 and 0.34.

Alternatives to GeneNMF and qtl2convert

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 qtl2convert.

See all GeneNMF alternatives → · See all qtl2convert alternatives →

Recent activity from GeneNMF and qtl2convert

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

  1. 1mo agoqtl2convertcores=0 now leaves one core free instead of taking all
  2. 2mo agoqtl2convertAttribute-clearing fix for R-devel 4.7
  3. 3mo agoqtl2convertC string comparison fix in encode_geno()
  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 agoqtl2convertBug fix in probs_doqtl_to_qtl2()
  9. 2y agoGeneNMFFirst stable release published to CRAN
  10. 4y agoqtl2convertMaintenance release for a NEWS.md typo
  11. 4y agoqtl2convertAdds cross2_ril_to_genril() for RIL cross conversion

Frequently asked questions

What is the difference between GeneNMF and qtl2convert?

Both compete on the same themes — r-package — within Analytics. GeneNMF and qtl2convert 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 qtl2convert?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. GeneNMF and qtl2convert 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 qtl2convert?

Top qtl2convert alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2convert alternatives" section above for the current picks, or visit /alternatives/qtl2convert for the full list with editorial commentary on each.