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Comparison · Analytics
regfusionr vs STACAS
A side-by-side editorial comparison of regfusionr and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
regfusionr vs STACAS: at a glance
What is regfusionr?
Registration fusion mapping goes bidirectional, and a vertex-indexing bug that silently returned wrong coordinates is fixed
regfusionr maps coordinates between volumetric brain templates (MNI152, Colin27) and the fsaverage surface. After four dormant years it returned in July 2026 with a release that fixes a coordinate-indexing bug, unblocks a previously disabled function, and completes the template-by-method matrix so all four combinations answer point queries. It also breaks compatibility by switching to the standard FREESURFER_HOME environment variable.
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.
regfusionr vs STACAS: editorial side-by-side
regfusionr
3.8ANALYTICS
Registration fusion mapping goes bidirectional, and a vertex-indexing bug that silently returned wrong coordinates is fixed
◆ Current state
regfusionr maps coordinates between volumetric brain templates (MNI152, Colin27) and the fsaverage surface. After four dormant years it returned in July 2026 with a release that fixes a coordinate-indexing bug, unblocks a previously disabled function, and completes the template-by-method matrix so all four combinations answer point queries. It also breaks compatibility by switching to the standard FREESURFER_HOME environment variable.
◆ Where it's heading
The package moved from a partial implementation to a complete one in a single release. Before this, vol_coords_to_fsaverage returned coordinates indexed by query position rather than by vertex index — results that looked plausible and were wrong — and fsaverage_to_vol was guarded behind a stop(). Both are now resolved, and the new Colin27 and MNI152 convenience functions make the mapping bidirectional. The sibling package haze shipped a maintenance release 56 minutes later, marking this as a coordinated sweep across the maintainer's neuroimaging stack.
◆ Prediction
With the four template-by-method combinations closed and the coordinate bug fixed, the next release is more likely to be CRAN-adjacent packaging or documentation than new mapping capability.
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 regfusionr 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 regfusionr or STACAS.
kde1d
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
gghighlight
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
rtrek
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
eiaapi
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all regfusionr alternatives → · See all STACAS alternatives →
Recent activity from regfusionr and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agoregfusionrVersion 0.3.0 -- vol_to_fsaverage, many convenience functions and fixes ⚡
- 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 agoregfusionrv0.2.0 -- surface to volume data projection
- 4y agoregfusionrv0.1.0: Initial release
- 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
Frequently asked questions
What is the difference between regfusionr and STACAS?
Both compete on the same themes — r-package — within Analytics. regfusionr is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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.
Is regfusionr better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. regfusionr is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 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.
What are the best alternatives to regfusionr?
Top regfusionr alternatives in Analytics are ranked by recent ship velocity. Browse the "regfusionr alternatives" section above for the current picks, or visit /alternatives/regfusionr 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.