mice
mice can finally predict, not just estimate, from multiply imputed data.
A side-by-side editorial comparison of goat and slendr — 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.
Population-genetic simulation in R, opened up to selection and finally easier to install.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
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.
slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().
Since the 1.0.0 release added non-neutral simulation, the work has shifted from capability to friction. A large share of recent notes concerns Python environment handling, conda activation races on Windows, dependency pruning that made shiny optional, and argument names that misled users, as when gene_flow()'s rate argument turned out to mean total ancestry proportion rather than a rate. That is the profile of a package whose scientific surface is settled and whose remaining problems are the ones users actually hit.
Expect the uv-based environment path to move from fallback to default once it has proven itself, given the notes already describe an environment variable for making it so. The deprecated rate argument in gene_flow() is explicitly slated for removal in a future major release, which is the clearest signal here of what a 2.0 would contain.
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 slendr.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. goat and slendr 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 slendr 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 slendr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "slendr alternatives" section above for the current picks, or visit /alternatives/slendr for the full list with editorial commentary on each.