qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of ggmagnify and TwoSampleMR — 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.
The flagship Mendelian randomization package is auditing its own estimators, one bootstrap at a time.
TwoSampleMR is the MRC-IEU package for two-sample Mendelian randomization against OpenGWAS. Its 2026 releases are a sustained correctness review rather than feature work: 0.7.9 fixed bootstrap standard errors in mr_mode() and mr_rucker_bootstrap() that had been inflated since v0.6.30, and repaired two Rucker functions that were returning malformed objects. Point estimates were not affected by the bootstrap bug.
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.
TwoSampleMR is the MRC-IEU package for two-sample Mendelian randomization against OpenGWAS. Its 2026 releases are a sustained correctness review rather than feature work: 0.7.9 fixed bootstrap standard errors in mr_mode() and mr_rucker_bootstrap() that had been inflated since v0.6.30, and repaired two Rucker functions that were returning malformed objects. Point estimates were not affected by the bootstrap bug.
The pattern across these releases is a package being read line by line — a copy-paste weight vector in ldsc_rg(), chunking that produced zero splits for short SNP lists, penalisation recycled across the wrong SNPs, dead code paths removed, and regression tests added behind each fix. Alongside it runs a mechanical modernization pass: seq_len() for loop indices, tidyr in place of reshape2, current ggplot2 idioms, and the OpenGWAS URL migration. Feature work is limited to forest plot presentation.
Expect the audit to continue through the remaining bootstrap and jackknife routines, with releases staying in the 0.7.x patch range and each fix arriving with its own regression test.
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 TwoSampleMR.
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 TwoSampleMR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ggmagnify and TwoSampleMR 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. ggmagnify and TwoSampleMR 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 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 TwoSampleMR alternatives in Analytics are ranked by recent ship velocity. Browse the "TwoSampleMR alternatives" section above for the current picks, or visit /alternatives/twosamplemr for the full list with editorial commentary on each.