pr2database
The protist reference database keeps widening past the rRNA gene it was built on.
Comparison · Infra & APIs
mice vs slendr
A side-by-side editorial comparison of mice and slendr — release velocity, themes, recent moves, and the top alternatives to consider.
mice vs slendr: at a glance
What is mice?
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.
What is slendr?
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().
mice vs slendr: editorial side-by-side
mice
0.0INFRA · APIS
mice can finally predict, not just estimate, from multiply imputed data.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
slendr
0.0INFRA · APIS
Population-genetic simulation in R, opened up to selection and finally easier to install.
◆ Current state
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().
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to mice and slendr
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 mice or slendr.
ggalign
Composable aligned layouts, rebuilt on S7 while ggplot2 4.0 lands underneath.
prioritizr
Conservation planning absorbs the literature's target-setting rules as code.
jSDM
Joint species distribution models in Gibbs-sampled C++, quiet since 2023.
rsofun
An ecosystem model starts tracking carbon isotopes and land-use change.
usmap
Ten years in, US mapping splits its data out and finally adds Puerto Rico.
Recent activity from mice and slendr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoslendrEphemeral uv Python environments remove the setup step
- 7mo agoslendrgene_flow() separates migration rate from ancestry proportion
- 8mo agomicemice 3.19.0 ⚡
- 9mo agoslendrshiny made optional; SLiM 5.1 and Python 3.13 required
- 1y agoslendrconda activation reverted to a slower but reliable path
- 1y agoslendrBackends raised to SLiM 5.0, tskit 0.6.4 and msprime 1.3.4
- 1y agomicemice 3.18.0
- 1y agoslendrNon-neutral models arrive; slim() interface simplified ⚡
- 1y agomicemice 3.17.0
- 3y agomicemice 3.16.0
- 3y agomicemice 3.15.0
- 4y agomicemice 3.14.0
Frequently asked questions
What is the difference between mice and slendr?
They serve adjacent needs but don't currently overlap on shipped themes. mice 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.
Is mice better than slendr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mice 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.
What are the best alternatives to mice?
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.
What are the best alternatives to slendr?
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.