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The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of arulesViz and ggmagnify — release velocity, themes, recent moves, and the top alternatives to consider.
arulesViz finished its move to ggplot2 and has been coasting on maintenance since.
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
A single-purpose ggplot2 inset tool, refining the same three arguments.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
The 2021 releases were a deliberate consolidation. 1.4-0 added ggplot2 engines and cut plotly_arules and the experimental iplots support out of the interface; 1.5.0 promoted ggplot2 to default and exposed the conversions to igraph and matrix so users could build their own views; 1.5-1 filled gaps in the graph and grouped-matrix methods. Since then the package tracks its dependencies rather than extending itself, which is a reasonable end state for a mature visualization layer.
Expect continued reactive releases keyed to ggplot2 and igraph deprecations, which have driven two of the last three updates. Nothing in these entries suggests new plot methods are planned.
ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.
Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.
Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.
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 arulesViz or ggmagnify.
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 arulesViz alternatives → · See all ggmagnify alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — ggplot2, r-package — within Analytics. arulesViz and ggmagnify 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. arulesViz and ggmagnify 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 arulesViz alternatives in Analytics are ranked by recent ship velocity. Browse the "arulesViz alternatives" section above for the current picks, or visit /alternatives/arulesviz-r for the full list with editorial commentary on each.
Top ggmagnify alternatives in Analytics are ranked by recent ship velocity. Browse the "ggmagnify alternatives" section above for the current picks, or visit /alternatives/ggmagnify for the full list with editorial commentary on each.