pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
A side-by-side editorial comparison of goat and mice — release velocity, themes, recent moves, and the top alternatives to consider.
A gene-set enrichment package that outgrew its human-only origins, then went quiet.
GOAT is a CRAN-published R package for gene set enrichment testing, now at 1.1.4. The visible arc runs from a 2024 beta through a first public CRAN release to a 1.1 line that broadened the package past human gene sets and added persistence for completed analyses. Recent releases are small: the newest ships an igraph handle on plot_network() plus bug fixes.
mice can finally predict, not just estimate, from multiply imputed data.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
GOAT is a CRAN-published R package for gene set enrichment testing, now at 1.1.4. The visible arc runs from a 2024 beta through a first public CRAN release to a 1.1 line that broadened the package past human gene sets and added persistence for completed analyses. Recent releases are small: the newest ships an igraph handle on plot_network() plus bug fixes.
The substantive expansion happened in the 1.1 cycle; everything since has been maintenance and plotting ergonomics. Each release since 1.1 touches one function and returns something callers previously had to reconstruct, which reads as a package settling into a stable API and responding to individual user requests rather than pursuing new scope. The 13-month gap between 1.1.2 and 1.1.4 puts it firmly in low-cadence maintenance.
Expect continued point releases that expose internals from the plotting functions or refresh the bundled GO release, not new analysis capability. The entries give no signal of a planned 1.2.
mice is the reference implementation of multiple imputation by chained equations, and the default answer to missing data in R. The releases here follow a consistent shape: one or two substantive additions per version, most contributed by outside authors, plus fixes to methods that have been in the package for years. The current 3.19.0 adds predict_mi(), which pools predictions across imputations under Rubin's rules and can return prediction intervals.
Two things are happening. The imputation method catalogue keeps widening — lasso variants, multivariate PMM, categorical PMM via canonical correlation — while the pooling side is being extended past its original purpose, first to synthetic data, now to predictions on held-out sets. That second thread points at predictive modelling workflows rather than the inferential ones mice was built for. Meanwhile the maintainers keep finding consequential old bugs: the augment() ordered-factor defect in 3.18.0 had been silently degrading ordinal imputations for years.
predict_mi() is framed around evaluating predictive performance on test sets, and the ignore argument added in 3.12.0 already exists to hold out rows from the imputation model. Expect the next work to join those up into a fuller train/test story for imputed data, since the pieces are now in place but not yet connected.
Other Infra & APIs 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 goat or mice.
The protist reference database keeps widening past the rRNA gene it was built on.
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
Conservation planning absorbs the literature's target-setting rules as code.
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
An ecosystem model starts tracking carbon isotopes and land-use change.
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Infra & APIs. goat and mice 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. goat and mice 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 Infra & APIs products to evaluate alongside.
Top goat alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "goat alternatives" section above for the current picks, or visit /alternatives/goat for the full list with editorial commentary on each.
Top mice alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "mice alternatives" section above for the current picks, or visit /alternatives/mice for the full list with editorial commentary on each.