qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of ggmagnify and hdnom — 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.
hdnom is in pure custodial mode, absorbing glmnet's changes so its users don't have to
hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.
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.
hdnom builds nomograms and validation/calibration workflows for high-dimensional Cox survival models on top of glmnet, ncvreg and penalized. The package's own interface has been stable since the 6.0.0 refactor in 2019; every release since has been maintenance. The recent run is entirely about surviving glmnet's evolution — a lambda-selection rule argument, then a cox.ties argument pinning the old tie handling.
The releases track two upstream pressures with no feature work of its own. glmnet is the larger one: its 4.1-9 change to how Cox cross-validation errors are normalized made lambda.1se select null models far more often, forcing hdnom to expose a rule argument and switch its examples to lambda.min. R-devel is the other, producing a steady trickle of strict-headers, deprecated-symbol and check-note fixes. The pattern is consistent — absorb the upstream change, default to whatever preserves existing behaviour, let users opt into the new one.
The cox.ties default is explicitly pinned to "breslow" to silence glmnet's migration warning, which is a deferral rather than a decision; expect a future release to flip that default to "efron" once glmnet completes the transition.
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 hdnom.
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 hdnom alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. hdnom 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. hdnom 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 hdnom alternatives in Analytics are ranked by recent ship velocity. Browse the "hdnom alternatives" section above for the current picks, or visit /alternatives/hdnom for the full list with editorial commentary on each.