qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of tern.mmrm and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
An MMRM tabulation package that has published nothing since its 2024 CRAN releases.
tern.mmrm wraps mixed models for repeated measures into the tern tabulation and plotting layer used by teal clinical modules. The visible history ends with three CRAN releases in mid-to-late 2024; before that the feed carries only automated version bumps from 2022, three of which have just been backfilled into the record. The most recent substantive change adds axis limit arguments to the LS-means plot.
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
tern.mmrm wraps mixed models for repeated measures into the tern tabulation and plotting layer used by teal clinical modules. The visible history ends with three CRAN releases in mid-to-late 2024; before that the feed carries only automated version bumps from 2022, three of which have just been backfilled into the record. The most recent substantive change adds axis limit arguments to the LS-means plot.
Content per release is thin and largely organisational: a maintainer change, replacing scda with random.cdisc.data in vignettes, and adapting to new {mmrm} versions. The package appears to be in maintenance, tracking its upstream dependency rather than developing independently. The 2022 entries now visible are release-automation commits, not releases in any meaningful sense.
Nothing here signals new functionality; the realistic next event is another compatibility release when {mmrm} or {rtables} changes underneath it.
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.
The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.
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 tern.mmrm or tidypolars.
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
The R client for AusTraits spends its releases chasing the dataset it reads.
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
A fossil-record simulator that quietly grew a trait-evolution engine.
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all tern.mmrm alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tern.mmrm and tidypolars 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. tern.mmrm and tidypolars 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 tern.mmrm alternatives in Analytics are ranked by recent ship velocity. Browse the "tern.mmrm alternatives" section above for the current picks, or visit /alternatives/tern-mmrm for the full list with editorial commentary on each.
Top tidypolars alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypolars alternatives" section above for the current picks, or visit /alternatives/tidypolars for the full list with editorial commentary on each.