qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of ggmagnify and vellum — release velocity, themes, recent moves, and the top alternatives to consider.
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.
vellum's bugs are now found by using it, not testing it — the downstream grammar is doing the QA.
The rendering engine shipped nine releases in the two weeks around the end of July, six of them on a single day. Almost every entry is a correctness fix in a capability that worked when drawn and failed when measured, or worked in isolation and failed in composition. The release notes are unusually forensic: each one states the mechanism, the observable symptom, and why the fix mirrors the draw path rather than reimplementing it.
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.
The rendering engine shipped nine releases in the two weeks around the end of July, six of them on a single day. Almost every entry is a correctness fix in a capability that worked when drawn and failed when measured, or worked in isolation and failed in composition. The release notes are unusually forensic: each one states the mechanism, the observable symptom, and why the fix mirrors the draw path rather than reimplementing it.
The pivotal detail is stated outright in 0.6.3 — the first bug in the series found by using the engine from vellumplot rather than testing it in isolation. Every release since names the downstream as the source: the contrast rule's false positives, the lint rules that fired on all five sample plots, the keyed roundrect batch. A rendering engine with a real grammar built on top of it is now getting the integration coverage that unit tests structurally cannot provide, and the fixes are converging on one theme: the measurement path and the draw path must not drift.
Expect the release rate to fall as the vellumplot integration surface is exhausted, with remaining work concentrated in the lint rule set now that it is meant to gate builds rather than just inform.
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 ggmagnify or vellum.
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 ggmagnify alternatives → · See all vellum alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. vellum is currently shipping more aggressively (velocity 5.0 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. vellum is currently shipping more aggressively (velocity 5.0 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 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.
Top vellum alternatives in Analytics are ranked by recent ship velocity. Browse the "vellum alternatives" section above for the current picks, or visit /alternatives/vellum-r for the full list with editorial commentary on each.