simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
ggquiver vs STACAS
A side-by-side editorial comparison of ggquiver and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
ggquiver vs STACAS: at a glance
What is ggquiver?
ggquiver returned after four years to make arrows respect ggplot's own scales.
A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.
What is STACAS?
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.
ggquiver vs STACAS: editorial side-by-side
ggquiver
0.0ANALYTICS
ggquiver returned after four years to make arrows respect ggplot's own scales.
◆ Current state
A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.
◆ Where it's heading
The consistent theme across both eras is deferring to ggplot2 rather than drawing on top of it: coordinate systems first, then scale transformations, then arrow styling handed to grid. Development is episodic — years pass, then a release that closes the gap between what the geom does and what a user expects from any other layer. The changelog is entirely correctness and integration work; there is no sign of the package growing new plot types.
◆ Prediction
The entries only support a narrow read: further releases will likely keep closing ggplot2 integration gaps as they are reported, but the four-year gap means cadence is not predictable from this feed.
STACAS
0.0ANALYTICS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to ggquiver and STACAS
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 ggquiver or STACAS.
lavaanExtra
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
ibis.iSDM
A raster-to-terra migration is the only readable change in a feed of merge notes.
anyflights
A nycflights13 generator whose recent work is all about the data being right.
vinereg
Conditional density and log-likelihood fill out a vine copula regression package.
stringx
A drop-in string API for base R, kept alive by upstream check failures.
See all ggquiver alternatives → · See all STACAS alternatives →
Recent activity from ggquiver and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agoggquiverArrows respect scale transformations and grid arrow styling
- 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
- 2y agoSTACASscale.data option for extreme batch effects; gene name conversion table
- 3y agoSTACASReference seeding, gene symbol standardisation, large-scale integration path
- 4y agoSTACASSemi-supervised integration and rPCA anchor downweighting ⚡
- 4y agoggquiverArrow scaling and centered-arrow angle fixes
- 4y agoggquiverFix for resized vectors via vecsize
- 4y agoggquiverNon-Cartesian coordinates and ggmap backgrounds supported
- 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
Frequently asked questions
What is the difference between ggquiver and STACAS?
They serve adjacent needs but don't currently overlap on shipped themes. ggquiver and STACAS 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.
Is ggquiver better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggquiver and STACAS 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.
What are the best alternatives to ggquiver?
Top ggquiver alternatives in Analytics are ranked by recent ship velocity. Browse the "ggquiver alternatives" section above for the current picks, or visit /alternatives/ggquiver for the full list with editorial commentary on each.
What are the best alternatives to STACAS?
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.