JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of tidyplots and valr — release velocity, themes, recent moves, and the top alternatives to consider.
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.
valr's interval verbs now read genomic files in place instead of demanding a loaded tibble.
valr reimplements bedtools-style genome interval arithmetic as tidyverse verbs backed by C++. Its long project has been closing the behavioural gap with bedtools — the book-ended interval semantics finally match in 0.10.0, three releases after the deprecation began. The July release also ends the assumption that intervals must be in memory: bed_map(), bed_intersect(), bed_subtract(), bed_coverage() and bed_window() accept a bigWig or bigBed path or URL where an interval table used to go.
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.
valr reimplements bedtools-style genome interval arithmetic as tidyverse verbs backed by C++. Its long project has been closing the behavioural gap with bedtools — the book-ended interval semantics finally match in 0.10.0, three releases after the deprecation began. The July release also ends the assumption that intervals must be in memory: bed_map(), bed_intersect(), bed_subtract(), bed_coverage() and bed_window() accept a bigWig or bigBed path or URL where an interval table used to go.
Two arcs converge here. One is compatibility: min_overlap arrived with a deprecation warning in 0.9.0 and its default flipped from 0 to 1 in 0.10.0, so book-ended intervals are excluded by default as bedtools does, with the internal calculations in bed_closest() and friends deliberately left counting them. The other is the file-backed path, which grew out of the cpp11bigwig dependency adopted in 0.8.3 for read_bigwig() and re-exported in 0.9.0 — reading a file became querying one. Underneath, the C++ base keeps getting lighter: Rcpp swapped for cpp11, rlang cut to a single function, per-group memory copies removed from three verbs.
Only five verbs take a file argument today and bed_closest(), bed_glyph() and the statistical verbs do not, so extending the file-backed path across the rest of the API is the obvious follow-up. The deprecated tibble re-exports and the now-defunct n_fields argument suggest continued removal of the compatibility layer in the next minor release.
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 tidyplots or valr.
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 tidyplots alternatives → · See all valr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. tidyplots and valr 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. tidyplots and valr 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 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.
Top valr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "valr alternatives" section above for the current picks, or visit /alternatives/valr for the full list with editorial commentary on each.