qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of gtfstools and hstats — 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.
hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.
hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.
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.
hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.
The structural work — the hstats_matrix object, quantile approximation, revised plotting — landed in 1.0.0 just outside this window, and nothing since has changed the package's shape. What continues is model-coverage plumbing: mlr3 classification modes, ranger survival behind a survival argument, and factor predictions added in 1.1.0 then removed again in 1.2.0. The most recent releases are compatibility-driven, tracking ggplot2 rather than the interaction statistics.
Expect the next release to be another dependency-compatibility pass or a new model backend working out of the box, rather than new interaction statistics.
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 hstats.
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 hstats alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. gtfstools and hstats 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 hstats 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 hstats alternatives in Analytics are ranked by recent ship velocity. Browse the "hstats alternatives" section above for the current picks, or visit /alternatives/hstats for the full list with editorial commentary on each.