fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of mmconvert and UCell — release velocity, themes, recent moves, and the top alternatives to consider.
A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
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.
mmconvert does one thing: interpolate between GRCm39 physical positions and the revised Cox genetic map for mouse MUGA array markers. The substantive work all landed in a burst across 2021-2023 — the initial function, the GRCm39 annotation dataset, cross2_to_grcm39(), the recomputed Cox maps and their smoothed replacement. Everything since is upkeep: a warning-message fix in 0.12, and 0.14 is a test adjustment to silence a CRAN Note with no code change at all.
The package has reached the natural end state of a reference-data converter — the reference data stopped moving, so the package stopped moving. Releases now arrive roughly annually and exist to keep CRAN checks green. The 0.14 release shipped the same day as sibling qtl2convert 0.36, confirming these are batch maintenance passes across the maintainer's packages rather than independent development.
Without a new mouse genome build or a revised Cox map, the next release is likely another CRAN-check accommodation rather than new functionality.
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.
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.
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.
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 mmconvert or UCell.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all mmconvert alternatives → · See all UCell alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. mmconvert 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mmconvert 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.
Top mmconvert alternatives in Analytics are ranked by recent ship velocity. Browse the "mmconvert alternatives" section above for the current picks, or visit /alternatives/mmconvert for the full list with editorial commentary on each.
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.