simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
Comparison · Analytics
qtl2convert vs STACAS
A side-by-side editorial comparison of qtl2convert and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
qtl2convert vs STACAS: at a glance
What is qtl2convert?
A conversion utility in pure maintenance mode, tracking R-devel breakage release by release
qtl2convert is the format-shim of the R/qtl2 ecosystem: it moves genotype probabilities and genetic maps between DOQTL, R/qtl and R/qtl2 representations. The last three releases contain no new conversion functions at all — 0.32 fixed a C string comparison flagged by CRAN, 0.34 restored attribute-clearing that R-devel 4.7 changed underneath the package, and 0.36 adjusted parallel core defaults plus a test tweak. The functional surface has been stable since 0.26 added cross2_ril_to_genril().
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.
qtl2convert vs STACAS: editorial side-by-side
qtl2convert
0.0ANALYTICS
A conversion utility in pure maintenance mode, tracking R-devel breakage release by release
◆ Current state
qtl2convert is the format-shim of the R/qtl2 ecosystem: it moves genotype probabilities and genetic maps between DOQTL, R/qtl and R/qtl2 representations. The last three releases contain no new conversion functions at all — 0.32 fixed a C string comparison flagged by CRAN, 0.34 restored attribute-clearing that R-devel 4.7 changed underneath the package, and 0.36 adjusted parallel core defaults plus a test tweak. The functional surface has been stable since 0.26 added cross2_ril_to_genril().
◆ Where it's heading
This is a package whose release cadence is driven by its dependencies, not its roadmap. Two of the last three releases exist purely because upstream R or CRAN's check suite moved; the maintainer responds within weeks and ships. The cores=0 change in 0.36 is the only user-visible behavior shift in over a year, and it landed simultaneously in sibling package qtl2fst — this is a maintainer-wide convention change, not a qtl2convert decision.
◆ Prediction
Expect the next release to be triggered by another R-devel or CRAN check change rather than a feature request, following the same pattern as 0.32 and 0.34.
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 qtl2convert 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 qtl2convert or STACAS.
lavaanExtra
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
ibis.iSDM
A raster-to-terra migration is the only readable change in a feed of merge notes.
anyflights
A nycflights13 generator whose recent work is all about the data being right.
vinereg
Conditional density and log-likelihood fill out a vine copula regression package.
stringx
A drop-in string API for base R, kept alive by upstream check failures.
See all qtl2convert alternatives → · See all STACAS alternatives →
Recent activity from qtl2convert and STACAS
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoqtl2convertcores=0 now leaves one core free instead of taking all
- 2mo agoqtl2convertAttribute-clearing fix for R-devel 4.7
- 3mo agoqtl2convertC string comparison fix in encode_geno()
- 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
- 2y agoqtl2convertBug fix in probs_doqtl_to_qtl2()
- 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 agoqtl2convertMaintenance release for a NEWS.md typo
- 4y agoqtl2convertAdds cross2_ril_to_genril() for RIL cross conversion
- 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
Frequently asked questions
What is the difference between qtl2convert and STACAS?
Both compete on the same themes — r-package — within Analytics. qtl2convert 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 qtl2convert better than STACAS?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qtl2convert 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 qtl2convert?
Top qtl2convert alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2convert alternatives" section above for the current picks, or visit /alternatives/qtl2convert 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.