fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of qtl2fst and UCell — release velocity, themes, recent moves, and the top alternatives to consider.
The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
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.
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
The package has settled into the role of a stable satellite of R/qtl2: it tracks the parent package's conventions rather than setting its own. The cores=0 change in 0.32 arrived alongside the identical change in qtl2convert, so the parallel-computing default is being standardized across the maintainer's packages at once. Release intervals have stretched from months to years.
Further releases will most likely mirror changes originating in R/qtl2 or CRAN checks, in the same follow-the-parent pattern as 0.24 and 0.32.
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 qtl2fst 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 qtl2fst 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. qtl2fst 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. qtl2fst 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 qtl2fst alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2fst alternatives" section above for the current picks, or visit /alternatives/qtl2fst 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.