HydroPortailStats
France's national flood statistics, ported out of Fortran and into R.
Comparison · Infra & APIs
driveR vs ggdist
A side-by-side editorial comparison of driveR and ggdist — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
driveR vs ggdist: at a glance
What is driveR?
A cancer driver prioritization package that ships rarely and mostly to stay installable
driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.
What is ggdist?
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
driveR vs ggdist: editorial side-by-side
driveR
0.0INFRA · APIS
A cancer driver prioritization package that ships rarely and mostly to stay installable
◆ Current state
driveR prioritizes cancer driver genes from somatic variant and copy number data, combining coding impact scores, noncoding impact, copy number alteration scores and hotspot annotations into a multi-task learning classification model. Version 0.5.0 added gene-level SCNA data frames as an accepted input to create_features_df(), with an example table shipped alongside, widening the entry point beyond the segment-level format. The same release moved org.Hs.eg.db and both hg19 and hg38 TxDb annotation packages from Imports to Suggests under new CRAN policy, with dependent functions now raising an error when they are absent rather than silently degrading.
◆ Where it's heading
Releases are infrequent and split cleanly between capability and correction. GRCh38 support arrived in 0.4.0 and cancer-type-specific thresholds were refreshed in 0.3.0, while the 0.2.x pair fixed scoring errors serious enough to require retraining: a column name mismatch meant the SCNA score was not being computed at all, and MCR table coordinates needed converting from hg18 to hg19. Both times the bundled classification model and thresholds were rebuilt as a consequence. Since 0.4.0 the changes have been input handling and packaging rather than method.
◆ Prediction
The move of the annotation databases to Suggests suggests a leaner install is the current priority; the entries give no indication of planned model or scoring changes.
ggdist
0.0INFRA · APIS
The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.
◆ Current state
ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.
◆ Where it's heading
Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.
◆ Prediction
Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.
Alternatives to driveR and ggdist
Other Infra & APIs 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 driveR or ggdist.
bsvarSIGNs
Sign, zero and narrative restrictions brought into the bsvars ecosystem.
estimatr
Fast design-based estimators for experiments, coasting on CRAN patches.
ipaddress
IP address vectors for R that hit 1.0 and then went quiet.
ltertools
A column-key toolkit for stitching decades of ecological field data into one table.
finnts
Microsoft's automated forecasting framework, still mostly a one-maintainer effort.
See all driveR alternatives → · See all ggdist alternatives →
Recent activity from driveR and ggdist
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 7mo agodriveRGene-level copy number input accepted, annotation packages made optional
- 1y agoggdistPer-geometry thickness subscales and settable defaults
- 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator ⚡
- 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
- 3y agodriveRCRAN documentation error fixed
- 3y agoggdistBounded density becomes the default; existing charts change ⚡
- 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
- 4y agodriveRGRCh38 genome build supported
- 4y agoggdistComputed variables shared across sub-geometries
- 4y agodriveRCancer-type-specific thresholds updated
- 5y agodriveRMCR coordinates converted to hg19 and the model retrained
- 5y agodriveRCopy number score was never being computed, model rebuilt
Frequently asked questions
What is the difference between driveR and ggdist?
Both compete on the same themes — r-package — within Infra & APIs. driveR and ggdist 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 driveR better than ggdist?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. driveR and ggdist 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 Infra & APIs products to evaluate alongside.
What are the best alternatives to driveR?
Top driveR alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "driveR alternatives" section above for the current picks, or visit /alternatives/driver for the full list with editorial commentary on each.
What are the best alternatives to ggdist?
Top ggdist alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggdist alternatives" section above for the current picks, or visit /alternatives/ggdist for the full list with editorial commentary on each.