qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of quantities and TAF — release velocity, themes, recent moves, and the top alternatives to consider.
The glue package that makes R carry units and uncertainty through the same calculation.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
TAF keeps turning ICES stock assessments into reproducible, dependency-pinned projects.
TAF is the R tooling behind the ICES Transparent Assessment Framework, which standardizes how fish stock assessments are laid out, sourced and rerun. The 4.3.0 release is the largest in years, adding roughly ten functions covering dependency installation and analysis, software version checks, directory inspection and README drafting. The package has carried zero non-base dependencies since 4.0.0, and the new work is careful not to break that.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.
Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.
TAF is the R tooling behind the ICES Transparent Assessment Framework, which standardizes how fish stock assessments are laid out, sourced and rerun. The 4.3.0 release is the largest in years, adding roughly ten functions covering dependency installation and analysis, software version checks, directory inspection and README drafting. The package has carried zero non-base dependencies since 4.0.0, and the new work is careful not to break that.
The arc runs from analysis runner to project toolkit. Early 3.x releases built out the bootstrap and metadata machinery; 4.0.0 renamed the package and stripped every external dependency; 4.2.0 cleaned up vocabulary that confused users. 4.3.0 turns outward to the people running assessments — install.deps(), pdeps() and check.software() address reproducing someone else's environment, while draft.readme(), taf.example() and dir.tree() address understanding an unfamiliar project.
Expect the follow-up work to harden the new dependency functions rather than add more surface, since 4.3.1 arrived immediately to fix wide2long() compatibility with older R and that batch of ten functions has had little field exposure.
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 quantities or TAF.
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 quantities alternatives → · See all TAF alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. quantities and TAF 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. quantities and TAF 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 quantities alternatives in Analytics are ranked by recent ship velocity. Browse the "quantities alternatives" section above for the current picks, or visit /alternatives/quantities for the full list with editorial commentary on each.
Top TAF alternatives in Analytics are ranked by recent ship velocity. Browse the "TAF alternatives" section above for the current picks, or visit /alternatives/taf-r for the full list with editorial commentary on each.