fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of qtl2convert and tglkmeans — release velocity, themes, recent moves, and the top alternatives to consider.
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().
A k-means implementation that just told users their Spearman clustering on missing data was wrong
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
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().
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.
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.
tglkmeans is a multi-core k-means implementation with seeding, aimed at single-cell and other large matrix workloads. Version 0.4.0 flipped the id_column default and moved to R's random number generator, 0.5.x added count-matrix downsampling and fixed id handling, and 0.6.3 in May 2026 is a correctness release: Spearman distance was ranking missing values as the largest value instead of dropping them, and predict_tgl_kmeans() with Euclidean distance did not reproduce the training metric when a cluster center had a missing dimension.
The package handles missing data across three distance metrics, and 0.6.3 shows those paths had drifted apart — Spearman behaved unlike Euclidean and Pearson, and prediction behaved unlike training. Both fixes change results on affected data, and the release notes are careful to bound exactly where: Spearman on data with NAs changes, complete data does not. Performance work runs alongside, with the dense per-thread vote matrix removed from the reassignment step.
With the metric paths now aligned on missing-value handling, further work is more likely to target the parallel reassignment internals than the distance semantics.
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 tglkmeans.
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 qtl2convert alternatives → · See all tglkmeans alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. qtl2convert and tglkmeans 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. qtl2convert and tglkmeans 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 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.
Top tglkmeans alternatives in Analytics are ranked by recent ship velocity. Browse the "tglkmeans alternatives" section above for the current picks, or visit /alternatives/tglkmeans for the full list with editorial commentary on each.