tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of serofoi and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
serofoi grew a serosurvey simulator alongside the force-of-infection models it was built to fit.
serofoi estimates the force of infection from serological survey data using Bayesian serocatalytic models fitted through Stan. Beyond fitting it now simulates serosurveys — specifying a model and a survey design and generating the data such a survey would produce. The most recent release is visualisation and naming work.
Tplyr made clinical summary tables explain where every number came from.
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
serofoi estimates the force of infection from serological survey data using Bayesian serocatalytic models fitted through Stan. Beyond fitting it now simulates serosurveys — specifying a model and a survey design and generating the data such a survey would produce. The most recent release is visualisation and naming work.
The package moved from fitting-only to a fit-and-simulate pair. 0.1.0 added simulation from time- or age-varying force-of-infection trends and simplified the fitted object down to a Stan fit; 1.0.2 broadened simulation into full serosurvey generation with its own vignette. 1.0.3 then spent its effort on naming consistency and plotting options, which is what a package does once its scope is set.
With simulation and fitting both in place, the natural next step is tooling that closes the loop between them — recovery checks or study-design guidance built on simulated surveys.
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
Post-1.0 work has been about completing the metadata story and filling gaps in layer composition rather than adding table types — metadata for missing subjects, add_anti_join(), missing-subject rows, data limiting, and fixes to nested count layers where an inner value appears under several outer groups. Releases cluster tightly after a major version, then go quiet, and the window ends with a patch issued days after the release it corrects.
Further releases will most likely continue closing traceability and nested-layer edge cases rather than introducing new layer types, following the pattern of both post-1.0 feature releases.
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 serofoi or Tplyr.
A tables-listings-graphs package that reached CRAN and then went quiet.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all serofoi alternatives → · See all Tplyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. serofoi and Tplyr 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. serofoi and Tplyr 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 serofoi alternatives in Analytics are ranked by recent ship velocity. Browse the "serofoi alternatives" section above for the current picks, or visit /alternatives/serofoi for the full list with editorial commentary on each.
Top Tplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "Tplyr alternatives" section above for the current picks, or visit /alternatives/tplyr for the full list with editorial commentary on each.