qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
ggmagnify vs RadialMR
A side-by-side editorial comparison of ggmagnify and RadialMR — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggmagnify vs RadialMR: at a glance
What is ggmagnify?
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.
What is RadialMR?
RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
ggmagnify vs RadialMR: editorial side-by-side
ggmagnify
0.0ANALYTICS
A single-purpose ggplot2 inset tool, refining the same three arguments.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.
RadialMR
0.0ANALYTICS
RadialMR's 2026 release corrects degrees of freedom that had been wrong since documentation.
◆ Current state
RadialMR implements radial-plot formulations of IVW and MR-Egger Mendelian randomization, with outlier detection and interactive plotting. The recent history is thin on features and increasingly focused on the arithmetic: 1.2.4 in July 2026 fixes the degrees of freedom returned by egger_radial() to the documented n-2, corrects the heterogeneity p-value that inherited the same error, and repairs a negated lower bound in the random-effects bootstrap standard error search interval in ivw_radial().
◆ Where it's heading
This is a package being read closely by its maintainer rather than extended. The 1.2.x line pairs statistical corrections with defensive hardening — an rmr_format class check so unformatted input fails with a clear message, and plotly_radial() dispatching on object class instead of counting list elements. Both are the kind of change made while auditing, not while building.
◆ Prediction
Expect the audit to continue into the remaining estimator internals and print methods rather than new radial variants; the entries show no feature work queued.
Alternatives to ggmagnify and RadialMR
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 RadialMR.
constants
The R package for CODATA constants rebuilt its symbol table on NIST's naming so future updates stop being hand work.
austraits
The R client for AusTraits spends its releases chasing the dataset it reads.
ggdemetra
A ggplot2 layer for seasonal adjustment output, filling in one plot type at a time.
fossilsim
A fossil-record simulator that quietly grew a trait-evolution engine.
tern.rbmi
Reference-based multiple imputation tables, shipping only what CRAN checks demand.
See all ggmagnify alternatives → · See all RadialMR alternatives →
Recent activity from ggmagnify and RadialMR
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoRadialMRegger_radial() degrees of freedom corrected to n-2
- 3mo agoRadialMRroxygen2 bumped; package-level helpfile added
- 4mo agoRadialMRUnspecified codebase optimizations
- 1y agoRadialMRggplot2 v4 warning removed from plot_radial()
- 2y agoggmagnifyFixes inset theme override on supplied plots
- 2y agoggmagnifyAdds fill between projection lines
- 2y agoggmagnifyAdds corner radius for target and inset
Frequently asked questions
What is the difference between ggmagnify and RadialMR?
Both compete on the same themes — r-package — within Analytics. ggmagnify and RadialMR 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.
Is ggmagnify better than RadialMR?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggmagnify and RadialMR 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.
What are the best alternatives to ggmagnify?
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.
What are the best alternatives to RadialMR?
Top RadialMR alternatives in Analytics are ranked by recent ship velocity. Browse the "RadialMR alternatives" section above for the current picks, or visit /alternatives/radialmr for the full list with editorial commentary on each.