JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of PEIMAN2 and tidyplots — release velocity, themes, recent moves, and the top alternatives to consider.
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
PEIMAN2 does enrichment analysis over post-translational modifications, testing whether a protein list is enriched for particular PTMs against UniProt-derived annotations, with translation functions bridging to mass spectrometry workflows. Its answers are only as current as its bundled database, and until June that database could only be refreshed by releasing a new package version. Version 1.1.0 changes that.
tidyplots keeps rebuilding its own foundations rather than layering around them.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
PEIMAN2 does enrichment analysis over post-translational modifications, testing whether a protein list is enriched for particular PTMs against UniProt-derived annotations, with translation functions bridging to mass spectrometry workflows. Its answers are only as current as its bundled database, and until June that database could only be refreshed by releasing a new package version. Version 1.1.0 changes that.
The package has been moving from a fixed snapshot toward versioned, user-selectable data. Earlier releases updated the bundled database in place — 1.0.0 shipped the March 2025 version and said little else — which meant the annotation vintage was whatever the package version implied. Now update_peiman_database() downloads and caches external database files and UniProt PTM lists, enrichment workflows take a database_version argument, and the mass-spec translators take a ptmlist_version, so an analysis can pin a dated database rather than a package release. The CRAN-safe default is preserved deliberately: loading, examples and checks still use the bundled internal data and need no network.
Version pinning is now expressible but the release notes do not describe how a chosen version is recorded in output, so surfacing the active database version in results is the natural companion. The database and the UniProt PTM list are versioned separately, which leaves room for a combined manifest.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
The package is converging on ggplot2 rather than abstracting away from it: split_plot() now uses facet_wrap and facet_grid, as_tidyplot() was hard-deprecated on the grounds that converting a ggplot was never a good idea, and releases are timed against upstream ggplot2 versions. The other constant is the statistics surface, which has grown from basic error bars to paired and selected comparisons. Breaking changes are announced plainly and frequently, consistent with a package using 0.x to fix its shape before committing.
The patchwork removal is described as something that will eventually break dependent code, so the near-term work is likely completing that migration and settling the split_plot() parameters introduced alongside it. A 1.0 would signal the breaking-change cadence is ending, and nothing here indicates that yet.
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 PEIMAN2 or tidyplots.
Recurrent-event modelling settles, with mean_no() promoted to stable.
Nonparametric change point detection swaps p-values for importance scores.
A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.
Wavelet trend estimation tightens the defaults it shipped with.
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
mice can finally predict, not just estimate, from multiply imputed data.
See all PEIMAN2 alternatives → · See all tidyplots alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. PEIMAN2 and tidyplots 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. PEIMAN2 and tidyplots 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.
Top PEIMAN2 alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "PEIMAN2 alternatives" section above for the current picks, or visit /alternatives/peiman2 for the full list with editorial commentary on each.
Top tidyplots alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyplots alternatives" section above for the current picks, or visit /alternatives/tidyplots for the full list with editorial commentary on each.