qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of gtfstools and RadialMR — release velocity, themes, recent moves, and the top alternatives to consider.
gtfstools stopped guarding its own object model and started accepting everyone else's.
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
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().
gtfstools reads, edits, filters and validates GTFS public transport feeds in R on a data.table backend. Since 1.3.0 it accepts GTFS objects produced by other packages such as gtfsio and tidytransit, converting them through an as_dt_gtfs() generic. Validation runs MobilityData's canonical validator, now supported through v6.0.0.
The package built out a wide function surface first — filters, geometry conversion, speed and duration calculations — then turned outward. Delegating validation to MobilityData's validator and accepting other packages' objects both trade self-sufficiency for a position inside the wider GTFS ecosystem. Deprecations are handled slowly, with old behaviour left as the default for a release or more.
Expect continued validator version tracking and further completion of the deprecation cycle around filter_by_stop_id()'s full_trips behaviour.
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().
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.
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.
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 gtfstools or RadialMR.
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 gtfstools alternatives → · See all RadialMR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. gtfstools 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gtfstools 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.
Top gtfstools alternatives in Analytics are ranked by recent ship velocity. Browse the "gtfstools alternatives" section above for the current picks, or visit /alternatives/gtfstools-r for the full list with editorial commentary on each.
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.