STACAS
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A side-by-side editorial comparison of regfusionr and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
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.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
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.
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.
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.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
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 sdsfun.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A univariate density estimator that added zero-inflated data and reopened its C++ API to do it.
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.
A Star Trek data package that became a Memory Alpha web client and has been patching scrapers ever since.
See all regfusionr alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.