svines
Stationary vine copulas for time series, released in lockstep with the rest of Nagler's vine stack.
A side-by-side editorial comparison of animovement and GeneNMF — release velocity, themes, recent moves, and the top alternatives to consider.
animovement stopped being a package and became a metapackage over seven focused ones.
animovement handles animal movement data — tracking output from pose-estimation and centroid trackers, cleaned into a standard form. Its 0.7.3 release, the first GitHub tag since November 2024, bundles the 0.5 through 0.7 development series and records a structural change: the codebase was split into aniframe, aniread, aniprocess, anicheck, animetric, anivis and anispace, which animovement now bundles and re-exports. The package has done this before at smaller scale, having renamed itself from trackballr in 0.2.0 to match a widened scope.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
GeneNMF applies non-negative matrix factorization to single-cell expression data to find gene programs, then consolidates programs recurring across samples into meta-programs. Version 0.6.0 replaced the consolidation method: instead of reducing each program to a gene set and taking a consensus, it retains full gene weight vectors and compares them by cosine similarity. Later releases have built reporting and control around that core — a metaprogram composition matrix showing which samples contributed, custom signature databases for enrichment testing, and the ability to drop meta-programs from results.
animovement handles animal movement data — tracking output from pose-estimation and centroid trackers, cleaned into a standard form. Its 0.7.3 release, the first GitHub tag since November 2024, bundles the 0.5 through 0.7 development series and records a structural change: the codebase was split into aniframe, aniread, aniprocess, anicheck, animetric, anivis and anispace, which animovement now bundles and re-exports. The package has done this before at smaller scale, having renamed itself from trackballr in 0.2.0 to match a widened scope.
Development has moved to the constituent packages, which release far more often than animovement itself — aniframe, aniread and aniprocess have each shipped multiple times in 2026 while animovement tagged once. That makes animovement a stable install surface rather than where the work happens, and the ani_df data class plus the frame-rate to sampling-rate terminology change are the contracts holding the suite together. Optional dependencies are handled through animovement_install_suggested() against r-universe and Bioconductor mirrors.
With the split done and the constituent packages iterating independently, animovement releases are likely to become periodic roll-ups of the suite rather than carriers of new functionality.
GeneNMF applies non-negative matrix factorization to single-cell expression data to find gene programs, then consolidates programs recurring across samples into meta-programs. Version 0.6.0 replaced the consolidation method: instead of reducing each program to a gene set and taking a consensus, it retains full gene weight vectors and compares them by cosine similarity. Later releases have built reporting and control around that core — a metaprogram composition matrix showing which samples contributed, custom signature databases for enrichment testing, and the ability to drop meta-programs from results.
The package is moving from producing meta-programs to letting users interrogate and constrain how they were formed. Composition matrices, the drop function and downsampled similarity heatmaps all serve inspection rather than derivation. The parameters added alongside the 0.6.0 rewrite — specificity weighting, cumulative weight thresholds, confidence defined as the fraction of programs containing a gene — turn what were fixed internal choices into stated, tunable ones.
Recent releases have been fixes and compatibility work rather than method changes, so the core approach appears settled. The dependency on an RcppML version not on CRAN is the loose end most likely to force the next release.
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 animovement or GeneNMF.
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.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
A Fortran-backed Delaporte distribution package where every release is compiler and CRAN weather.
Queuing theory packaged for NHS waiting-list managers, one year into a community-built first release.
See all animovement alternatives → · See all GeneNMF alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. animovement and GeneNMF 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. animovement and GeneNMF 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 animovement alternatives in Analytics are ranked by recent ship velocity. Browse the "animovement alternatives" section above for the current picks, or visit /alternatives/animovement for the full list with editorial commentary on each.
Top GeneNMF alternatives in Analytics are ranked by recent ship velocity. Browse the "GeneNMF alternatives" section above for the current picks, or visit /alternatives/genenmf for the full list with editorial commentary on each.