ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A side-by-side editorial comparison of b3gbi and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
b3gbi pulled confidence intervals out of its indicator workflow and handed them to dubicube.
b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.
b3gbi computes biodiversity indicators from GBIF occurrence cubes for the B-Cubed project, and sits at 0.9.4 in a JOSS review run-up. The 0.9 release decoupled uncertainty from indicator calculation: confidence intervals are no longer produced inline but added afterward with add_ci(), backed by whole-cube bootstrapping from the sibling dubicube package. Everything since has been grid-parsing and compatibility repair around that split.
Two forces are shaping releases. Internally, the uncertainty split produced an indicator-specific rule book — species-level indicators bootstrap the whole cube, raw counts resample within year, evenness gets a logit transform — and that rule book is where the statistical thinking now lives. Externally, GBIF's taxonomic backbone migration to the Catalogue of Life forced string taxon keys through process_cube() and the plotting paths, while recurring EEA and MGRS grid-code fixes mark coordinate parsing as the least settled area.
The 0.9.4 notes are entirely JOSS review items — contributors, examples, tracked datasets — so the next release is most likely a JOSS-accepted 1.0 rather than new indicator work.
STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.
The method work concentrated in version 2.0 and has been stable since; everything after is Seurat compatibility and operational robustness. Versions 2.1.1 through 2.3.0 track Seurat v5 assays, v3-to-v5 conversion, multi-layer objects and SCT normalisation, with the genuinely useful additions — a reference seed dataset, max.seed.datasets for large-scale integration, min.sample.size — arriving as side effects of that work. The package is from the same lab as GeneNMF, and its release rhythm follows the single-cell ecosystem's upstream churn rather than an internal roadmap.
Expect the next release to follow further Seurat object-model changes, which have driven the last three. Nothing in the entries indicates new anchor-scoring or correction methodology in progress.
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 b3gbi or STACAS.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all b3gbi alternatives → · See all STACAS alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. b3gbi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. 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. b3gbi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top b3gbi alternatives in Analytics are ranked by recent ship velocity. Browse the "b3gbi alternatives" section above for the current picks, or visit /alternatives/b3gbi for the full list with editorial commentary on each.
Top STACAS alternatives in Analytics are ranked by recent ship velocity. Browse the "STACAS alternatives" section above for the current picks, or visit /alternatives/stacas for the full list with editorial commentary on each.