qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
Comparison · Analytics
ggmagnify vs lineup2
A side-by-side editorial comparison of ggmagnify and lineup2 — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
ggmagnify vs lineup2: 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 lineup2?
lineup2 ships once every few years, and 2026's release is a logo and a core-count tweak.
lineup2 provides distance-based tools for detecting sample mix-ups between related datasets — comparing rows and columns of two matrices to find swapped or mislabeled samples. Its visible history is four releases spread across six years, and the capability surface has barely moved since plot_sample() and the propdiff distance arrived in 0.4. Version 0.8 in July 2026 adds a package logo and redefines cores=0 to mean all-but-one core.
ggmagnify vs lineup2: 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.
lineup2
0.0ANALYTICS
lineup2 ships once every few years, and 2026's release is a logo and a core-count tweak.
◆ Current state
lineup2 provides distance-based tools for detecting sample mix-ups between related datasets — comparing rows and columns of two matrices to find swapped or mislabeled samples. Its visible history is four releases spread across six years, and the capability surface has barely moved since plot_sample() and the propdiff distance arrived in 0.4. Version 0.8 in July 2026 adds a package logo and redefines cores=0 to mean all-but-one core.
◆ Where it's heading
This is a finished, single-purpose package in maintenance. The substantive changes across the whole window are plotting conveniences and one parallelism default; nothing in the entries points at new distance measures, new input formats, or expanded scope. The release cadence — five years between 0.6 and 0.8 — reads as a tool the author considers done.
◆ Prediction
Further releases are likely to stay small: a plotting option, a parallelism detail, or a check-farm fix. The entries give no signal of planned feature work.
Alternatives to ggmagnify and lineup2
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 lineup2.
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 lineup2 alternatives →
Recent activity from ggmagnify and lineup2
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agolineup2cores=0 now leaves one core free
- 2y agoggmagnifyFixes inset theme override on supplied plots
- 2y agoggmagnifyAdds fill between projection lines
- 2y agoggmagnifyAdds corner radius for target and inset
- 5y agolineup2plot_sample() gains xlim and ylim control
- 5y agolineup2plot_sample() and the propdiff distance added
- 5y agolineup2Package description revised for CRAN resubmission
Frequently asked questions
What is the difference between ggmagnify and lineup2?
Both compete on the same themes — r-package — within Analytics. ggmagnify and lineup2 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 lineup2?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggmagnify and lineup2 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 lineup2?
Top lineup2 alternatives in Analytics are ranked by recent ship velocity. Browse the "lineup2 alternatives" section above for the current picks, or visit /alternatives/lineup2-r for the full list with editorial commentary on each.