qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of APCalign and quantities — release velocity, themes, recent moves, and the top alternatives to consider.
APCalign spent this year fixing the counts it had been quietly getting wrong
APCalign standardises Australian plant names against the APC and APNI taxonomic resources and derives state-level native/introduced status from them. The feed is GitHub releases tagged by resource download date rather than semantic version, so titles carry no information about content. The two 2026 releases are the only substantive ones in the window: infrataxa support in the diversity functions, then a fix for a grep that had been matching the wrong columns.
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.
APCalign standardises Australian plant names against the APC and APNI taxonomic resources and derives state-level native/introduced status from them. The feed is GitHub releases tagged by resource download date rather than semantic version, so titles carry no information about content. The two 2026 releases are the only substantive ones in the window: infrataxa support in the diversity functions, then a fix for a grep that had been matching the wrong columns.
Development is driven by users reporting that outputs do not match what they expect, and the fixes keep landing in the same two functions — create_species_state_origin_matrix() and native_anywhere_in_australia(). The infrataxa parameter and the reordered output columns came from user requests; the guard-ordering and grep fixes came from a filed issue. What is emerging is that the origin-matrix logic was written loosely and is now being tightened case by case, with tests and state diversity benchmarks added alongside.
Both recent releases touched the same pair of functions and the fixes were found by inspection rather than by tests failing, so more corrections in the native-status path are the likely next content — the benchmarks added in March are the mechanism that would surface them.
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.
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 APCalign or quantities.
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 APCalign alternatives → · See all quantities alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. APCalign is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. APCalign is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top APCalign alternatives in Analytics are ranked by recent ship velocity. Browse the "APCalign alternatives" section above for the current picks, or visit /alternatives/apcalign-r for the full list with editorial commentary on each.
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.