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Comparison · Analytics
qtl2fst vs STACAS
A side-by-side editorial comparison of qtl2fst and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
qtl2fst vs STACAS: at a glance
What is qtl2fst?
The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
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.
qtl2fst vs STACAS: editorial side-by-side
qtl2fst
0.0ANALYTICS
The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep
◆ Current state
qtl2fst backs R/qtl2 genotype probabilities with on-disk fst files so large crosses don't have to fit in RAM. Its defining release was 0.22 in 2020, which added calc_genoprob_fst() and genoprob_to_alleleprob_fst() to fuse calculation and storage in one step. The five releases since are documentation links, directory-creation robustness, a Windows example fix, and — in 0.32 — a change to how cores=0 is interpreted.
◆ Where it's heading
The package has settled into the role of a stable satellite of R/qtl2: it tracks the parent package's conventions rather than setting its own. The cores=0 change in 0.32 arrived alongside the identical change in qtl2convert, so the parallel-computing default is being standardized across the maintainer's packages at once. Release intervals have stretched from months to years.
◆ Prediction
Further releases will most likely mirror changes originating in R/qtl2 or CRAN checks, in the same follow-the-parent pattern as 0.24 and 0.32.
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 qtl2fst 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 qtl2fst 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 qtl2fst alternatives → · See all STACAS alternatives →
Recent activity from qtl2fst and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoqtl2fstcores=0 now leaves one core free instead of taking all
- 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
- 1y agoqtl2fstWindows fix for the replace_path() example
- 2y agoqtl2fstDocumentation link fix
- 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 agoqtl2fstCreates missing directories instead of erroring out
- 5y agoqtl2fstTest coverage for qtl2 functions against fst-backed probabilities
- 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
- 6y agoqtl2fstDocumentation and metadata cleanup for CRAN
Frequently asked questions
What is the difference between qtl2fst and STACAS?
Both compete on the same themes — r-package — within Analytics. qtl2fst 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.
Is qtl2fst better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qtl2fst 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.
What are the best alternatives to qtl2fst?
Top qtl2fst alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2fst alternatives" section above for the current picks, or visit /alternatives/qtl2fst 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.