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qtl2convert vs UCell

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

Shared themes:r-package

qtl2convert vs UCell: at a glance

Featureqtl2convertUCell
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, genetics, format-conversion, cran-maintenancer-package, single-cell, gene-signatures, bioconductor
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

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 →

What is UCell?

A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next

UCell scores gene signatures in single-cell data using a rank-based metric that is robust to dataset composition. Its release history reads as a sequence of ecosystem accommodations: Bioconductor submission in 2.0, SmoothKNN() for k-nearest-neighbor smoothing of scores in 2.2, smoothing applied directly to expression slots in 2.4, Seurat v5 assay compatibility in 2.6, multi-layer Seurat v5 objects in 2.8, and a missing_genes parameter in 2.14 that lets callers impute or skip signature genes absent from the data. Version 2.16 tracks Bioconductor 3.23 and points at a new publication and a Python implementation, pyUCell.

Read the full UCell trajectory →

qtl2convert vs UCell: editorial side-by-side

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.

U
UCell
ANALYTICS
0.0

A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next

◆ Current state

UCell scores gene signatures in single-cell data using a rank-based metric that is robust to dataset composition. Its release history reads as a sequence of ecosystem accommodations: Bioconductor submission in 2.0, SmoothKNN() for k-nearest-neighbor smoothing of scores in 2.2, smoothing applied directly to expression slots in 2.4, Seurat v5 assay compatibility in 2.6, multi-layer Seurat v5 objects in 2.8, and a missing_genes parameter in 2.14 that lets callers impute or skip signature genes absent from the data. Version 2.16 tracks Bioconductor 3.23 and points at a new publication and a Python implementation, pyUCell.

◆ Where it's heading

Two threads run through this. The scoring algorithm itself has barely changed — the rank-based core is stable, and 2.14's reformatting to gene indices rather than string matching is a speed change, not a method change. What does change constantly is object-format compatibility, which is the tax of living between Seurat and SingleCellExperiment. The pyUCell reference in 2.16 is the first sign of the method reaching beyond R, though these notes say nothing about its scope.

◆ Prediction

The cadence is locked to Bioconductor's twice-yearly release train, so the next version will most likely accompany Bioconductor 3.24 with whatever Seurat or SingleCellExperiment changes it brings.

Alternatives to qtl2convert and UCell

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 qtl2convert or UCell.

See all qtl2convert alternatives → · See all UCell alternatives →

Recent activity from qtl2convert and UCell

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. 3mo agoUCellTracks Bioconductor 3.23 and points to a Python port
  5. 9mo agoUCellUCell version 2.14
  6. 2y agoUCellUCell version 2.8
  7. 2y agoqtl2convertBug fix in probs_doqtl_to_qtl2()
  8. 2y agoUCellUCell version 2.6
  9. 3y agoUCellUCell version 2.4
  10. 3y agoUCellUCell version 2.2
  11. 4y agoqtl2convertMaintenance release for a NEWS.md typo
  12. 4y agoqtl2convertAdds cross2_ril_to_genril() for RIL cross conversion

Frequently asked questions

What is the difference between qtl2convert and UCell?

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

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

What are the best alternatives to UCell?

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