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ggmagnify vs mrbayes

A side-by-side editorial comparison of ggmagnify and mrbayes — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

ggmagnify vs mrbayes: at a glance

Featureggmagnifymrbayes
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, inset-plots, r-packagemendelian-randomization, bayesian-inference, stan, jags
Last editorial update1h ago7h ago
WebsiteVisit →Visit →

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.

Read the full ggmagnify trajectory →

What is mrbayes?

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

Read the full mrbayes trajectory →

ggmagnify vs mrbayes: editorial side-by-side

G
ggmagnify
ANALYTICS
0.0

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.

M
mrbayes
ANALYTICS
0.0

mrbayes spent 2026 auditing its own Bayesian MR estimators for coding errors.

◆ Current state

mrbayes wraps Stan and JAGS implementations of Bayesian Mendelian randomization estimators — IVW, MR-Egger, radial Egger, and their multivariable forms. Most of the visible history is packaging work: dependency trimming, conditional examples so the package installs where JAGS will not compile, a maintainer handover. The 0.5.3 release in July 2026 breaks that pattern with a dense list of fixes inside the model code itself.

◆ Where it's heading

The package has moved from packaging upkeep into a correctness-audit phase. 0.5.3 fixes a hardcoded three-exposure loop in MVMR-Egger reporting, a broken joint-prior branch, a sigma parameterization error in radial Egger, and several prior specifications — the profile of a maintainer reading their own model files closely rather than responding to bug reports. Platform work continues underneath: an R 4.3.0 floor inherited through a transitive dependency chain, and segfault fixes on macOS ARM.

◆ Prediction

Expect further audit-driven patches to the remaining rjags and Stan model files rather than new estimators; the fixes in 0.5.3 cluster in the Egger variants, which suggests that is where the reading is still in progress.

Alternatives to ggmagnify and mrbayes

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 mrbayes.

See all ggmagnify alternatives → · See all mrbayes alternatives →

Recent activity from ggmagnify and mrbayes

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agomrbayesEstimator audit fixes MVMR-Egger loops and radial Egger sigma
  2. 1y agomrbayesMVMR rjags example gated on rjags being installed
  3. 1y agomrbayesExamples and tests skip when rstan or rjags is missing
  4. 1y agomrbayespkgdown site updated
  5. 1y agomrbayesHelper command added for installing JAGS
  6. 1y agomrbayesDependency surface trimmed; maintainer handover
  7. 2y agoggmagnifyFixes inset theme override on supplied plots
  8. 2y agoggmagnifyAdds fill between projection lines
  9. 2y agoggmagnifyAdds corner radius for target and inset

Frequently asked questions

What is the difference between ggmagnify and mrbayes?

Both compete on the same themes — r-package — within Analytics. ggmagnify and mrbayes 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 mrbayes?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggmagnify and mrbayes 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 mrbayes?

Top mrbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "mrbayes alternatives" section above for the current picks, or visit /alternatives/mrbayes for the full list with editorial commentary on each.