simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of STACAS and treasury — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A thin Treasury rates wrapper has stopped adding endpoints and started making its tables self-describing.
treasury wraps the US Treasury's published rate feeds — bill rates, par yields, forward rates, long-term extrapolated rates, and the HQM and breakeven inflation curves — into one set of R functions. Since 0.3.0 every function returns a data.table, and 0.5.0 added optional on-disk response caching with a one-day default. The most recent release is about data fidelity rather than reach: identifying columns, correct maturity labels, and locale-safe date parsing.
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.
treasury wraps the US Treasury's published rate feeds — bill rates, par yields, forward rates, long-term extrapolated rates, and the HQM and breakeven inflation curves — into one set of R functions. Since 0.3.0 every function returns a data.table, and 0.5.0 added optional on-disk response caching with a one-day default. The most recent release is about data fidelity rather than reach: identifying columns, correct maturity labels, and locale-safe date parsing.
Endpoint coverage looks essentially complete, so the work has moved to the metadata a downstream analyst needs to join and audit results — cusip and maturity_date on bill quotes, the feed's updated_at stamp, and the extrapolation factor behind 2002-2006 long-term rate estimates. Error handling is tightening in the same direction: an out-of-range month now fails with a message instead of quietly returning nothing. That is the profile of a wrapper moving from coverage to correctness, where the remaining bugs are the subtle ones that only surface in other people's locales.
Expect further column-level enrichment and input validation on the endpoints already covered rather than new data sources, since the structural pieces — data.table returns and caching — are already in place.
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 STACAS or treasury.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all STACAS alternatives → · See all treasury alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. STACAS and treasury 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. STACAS and treasury 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.
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.
Top treasury alternatives in Analytics are ranked by recent ship velocity. Browse the "treasury alternatives" section above for the current picks, or visit /alternatives/treasury for the full list with editorial commentary on each.