OHPL
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
A side-by-side editorial comparison of APCalign and MVMR — 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.
MVMR spent 2026 discovering its own estimators had been returning the wrong numbers
MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.
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.
MVMR implements multivariable Mendelian randomization — conditional instrument strength, pleiotropy tests and heterogeneity-robust effect estimation from GWAS summary data. The package has been releasing steadily through 2026, and the substantive releases are all corrections rather than features. Two core routines were found to be computing the wrong quantity outright: qhet_mvmr() built weights from the minimised objective value instead of the minimiser, and strhet_mvmr() never minimised the Q-statistic at all.
This is a sustained audit, not a maintenance drift. Each release since February has fixed a specific analytical defect — omitted intercepts in the exposure-on-genotype regressions, a division by zero when a gencov list held exactly two variants, covariance matrices computed wrongly for matrix inputs, a spurious covariance warning — and several explicitly warn that reported values will differ from previous versions. The strhet_mvmr() rewrite to iteratively reweighted least squares also removes a combinatorial grid that could exhaust memory past three exposures, so the function is now usable as well as correct.
The corrections have been walking through the package function by function, and the ones with published fixes so far are the heterogeneity and covariance routines; the remaining untouched estimators are the natural next stop if the audit continues at this pace.
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 MVMR.
A 2017 chemometrics method frozen in place, visited only when CRAN changes its documentation rules.
A fast dplyr stand-in that keeps finding new places to skip work entirely.
Belgium's invasive-species indicator toolkit is in steady refinement, one plotting edge case at a time.
The ICES stock assessment client took upload away in 2024 and spent two years giving it back.
A discrete global grid generator grew cell traversal and became a usable spatial index.
Community ecology's standard toolkit is retiring the functions a generation of scripts was built on.
See all APCalign alternatives → · See all MVMR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r — within Analytics. 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 MVMR alternatives in Analytics are ranked by recent ship velocity. Browse the "MVMR alternatives" section above for the current picks, or visit /alternatives/mvmr for the full list with editorial commentary on each.