simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
effectplots vs STACAS
A side-by-side editorial comparison of effectplots and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
effectplots vs STACAS: at a glance
What is effectplots?
A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
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.
effectplots vs STACAS: editorial side-by-side
effectplots
0.0ANALYTICS
A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.
◆ Current state
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
◆ Where it's heading
After 0.2.0 the work turns to the awkward cases - missing values on the x axis, explicit and empty factor levels, discrete grid detection. The package is also widening past a single modelling ecosystem: h2o support and tidymodels examples arrived with 0.2.0, and fcut() was exported as a fast replacement for cut(). Release notes are issue-numbered throughout, so the roadmap is effectively the issue tracker.
◆ Prediction
Expect continued default tuning around collapse_m and discrete_m plus more model-backend coverage; the cadence points to another batch of issue fixes rather than a new plot type.
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 effectplots 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 effectplots 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 effectplots alternatives → · See all STACAS alternatives →
Recent activity from effectplots and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
- 1y agoeffectplotsRare categories collapse into an 'other' level
- 1y agoeffectplotsMissing x values now plotted for numeric features
- 1y agoeffectplotsNumeric core rewritten after an in-place data corruption fix ⚡
- 1y agoeffectplotsInitial CRAN release
- 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 ⚡
- 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
Frequently asked questions
What is the difference between effectplots and STACAS?
Both compete on the same themes — r-package — within Analytics. effectplots 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 effectplots better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. effectplots 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 effectplots?
Top effectplots alternatives in Analytics are ranked by recent ship velocity. Browse the "effectplots alternatives" section above for the current picks, or visit /alternatives/effectplots 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.