qqman
The Manhattan-plot package for GWAS results, finished and dormant since 2017.
A side-by-side editorial comparison of omopsketch and quantities — release velocity, themes, recent moves, and the top alternatives to consider.
Health-data characterisation tooling maturing through steady issue-by-issue tightening.
OmopSketch summarises and characterises OMOP Common Data Model databases — clinical records, observation periods, concept counts and missing data. Recent releases have tightened the semantics of those summaries: only records within observation are counted, study ranges are trimmed consistently, and a collect() was removed so more of the work stays in the database. Development is dominated by a single contributor working through numbered issues.
The glue package that makes R carry units and uncertainty through the same calculation.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
OmopSketch summarises and characterises OMOP Common Data Model databases — clinical records, observation periods, concept counts and missing data. Recent releases have tightened the semantics of those summaries: only records within observation are counted, study ranges are trimmed consistently, and a collect() was removed so more of the work stays in the database. Development is dominated by a single contributor working through numbered issues.
The package is moving from producing summaries toward producing defensible ones. Interval-based arguments replaced the narrower year argument, table output gained a datatable option, and the vignette now demonstrates a full characterisation feeding a Shiny app. The pattern is refinement of existing summarise* functions rather than new analytic surface.
Expect continued tightening of the summarise* family and its table output options; with only three releases visible, the cadence itself is hard to read.
quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.
The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.
Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.
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 omopsketch or quantities.
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 omopsketch alternatives → · See all quantities alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. omopsketch and quantities 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. omopsketch and quantities 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 omopsketch alternatives in Analytics are ranked by recent ship velocity. Browse the "omopsketch alternatives" section above for the current picks, or visit /alternatives/omopsketch for the full list with editorial commentary on each.
Top quantities alternatives in Analytics are ranked by recent ship velocity. Browse the "quantities alternatives" section above for the current picks, or visit /alternatives/quantities for the full list with editorial commentary on each.