simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
maths.genealogy vs STACAS
A side-by-side editorial comparison of maths.genealogy and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
maths.genealogy vs STACAS: at a glance
What is maths.genealogy?
A young Mathematics Genealogy client spending its first four releases satisfying CRAN.
maths.genealogy queries the Mathematics Genealogy Project over a WebSocket connection and renders academic advisor-student trees, with plot_grviz() as the visualisation entry point. The package reached CRAN in early 2025 and its functional surface has barely moved since — max_zoom() for deep trees at 0.1.1 is the only user-facing addition in the visible history.
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.
maths.genealogy vs STACAS: editorial side-by-side
maths.genealogy
0.0ANALYTICS
A young Mathematics Genealogy client spending its first four releases satisfying CRAN.
◆ Current state
maths.genealogy queries the Mathematics Genealogy Project over a WebSocket connection and renders academic advisor-student trees, with plot_grviz() as the visualisation entry point. The package reached CRAN in early 2025 and its functional surface has barely moved since — max_zoom() for deep trees at 0.1.1 is the only user-facing addition in the visible history.
◆ Where it's heading
Every release after the first is CRAN policy management. Three consecutive entries deal with the same underlying problem: examples that hit a live network resource and therefore fail unpredictably on check machines. The progression from wrapping them in \donttest{} to catching a stray case to rewriting all examples against published API-package guidance shows the maintainer converging on a pattern rather than adding features. That is the normal cost of shipping a network client to CRAN, and it appears to be settling.
◆ Prediction
With the examples problem resolved, the next release is the first plausible opportunity for feature work — likely on the plotting side, given max_zoom() was the sole non-compliance change so far. The entries do not name anything specific in progress.
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 maths.genealogy 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 maths.genealogy 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 maths.genealogy alternatives → · See all STACAS alternatives →
Recent activity from maths.genealogy and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1y agomaths.genealogyExamples rewritten to CRAN API-package guidance
- 1y agomaths.genealogyRemaining network-dependent example wrapped in donttest
- 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
- 1y agomaths.genealogyDESCRIPTION quoting and donttest example wrapping
- 1y agomaths.genealogyplot_grviz() gains max_zoom for deep trees
- 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 maths.genealogy and STACAS?
Both compete on the same themes — r-package — within Analytics. maths.genealogy 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 maths.genealogy better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. maths.genealogy 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 maths.genealogy?
Top maths.genealogy alternatives in Analytics are ranked by recent ship velocity. Browse the "maths.genealogy alternatives" section above for the current picks, or visit /alternatives/maths-genealogy 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.