ggtrace
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
A side-by-side editorial comparison of singlercapture and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
singleRcapture reached 1.0.0 with no release notes at all — the arc has to be read backwards.
A package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
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 package for single-source capture-recapture population size estimation: zero-truncated Poisson, geometric and negative binomial regression, Chao and Zelterman mixture models, analytic and bootstrap variance estimation, all behind estimatePopsize(). The 0.2.x line professionalised it — an offset argument, parallel bootstrap and dfbeta, faster semiparametric sampling, a singleRStaticCountData subclass explicitly created so a companion package could fit models from countreg and VGAM, then interaction-term and anova fixes. The 1.0.0 release carries nothing but a link to the compare view.
The direction visible in 0.2.x is outward: refactoring for maintainability, extending to models fitted elsewhere via a subclass, adding a JSS-paper vignette, and pushing coverage towards 90%. That is a package preparing to be cited and extended rather than one still finding its methods. The 1.0.0 tag presumably marks the end of that stabilisation, but the entry itself gives no evidence either way.
Not readable from this feed — the 1.0.0 notes are empty, so whether the major version marks an API freeze or a breaking change cannot be determined from the entries shown.
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.
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 singlercapture or STACAS.
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.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
See all singlercapture alternatives → · See all STACAS alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. singlercapture 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. singlercapture 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.
Top singlercapture alternatives in Analytics are ranked by recent ship velocity. Browse the "singlercapture alternatives" section above for the current picks, or visit /alternatives/singlercapture for the full list with editorial commentary on each.
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.