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collapse vs qtl

A side-by-side editorial comparison of collapse and qtl — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

collapse vs qtl: at a glance

Featurecollapseqtl
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsgenetics, qtl-mapping, statistical-genomics, r-package
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

What is qtl?

R/qtl is in pure custodial mode: every recent release answers a compiler, not a user

R/qtl is the long-established R package for QTL mapping in experimental crosses, covering interval mapping, composite interval mapping, multiple-QTL model fitting and the associated cross data formats. Nothing in the recent release history adds capability. Version 1.74 removes an include that started warning on CRAN, 1.72 improves an error message in cim(), and 1.70 migrates the C code from Calloc/Realloc/Free to their R_-prefixed equivalents for R-devel.

Read the full qtl trajectory →

collapse vs qtl: editorial side-by-side

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

Q
qtl
ANALYTICS
0.0

R/qtl is in pure custodial mode: every recent release answers a compiler, not a user

◆ Current state

R/qtl is the long-established R package for QTL mapping in experimental crosses, covering interval mapping, composite interval mapping, multiple-QTL model fitting and the associated cross data formats. Nothing in the recent release history adds capability. Version 1.74 removes an include that started warning on CRAN, 1.72 improves an error message in cim(), and 1.70 migrates the C code from Calloc/Realloc/Free to their R_-prefixed equivalents for R-devel.

◆ Where it's heading

The package is being maintained, not developed. The work divides cleanly into keeping the compiled code building against successive R and toolchain versions, and fixing narrow bugs reported through the issue tracker. The C-level migrations in particular are compliance with R's tightening of its C interface rather than anything chosen. Users should read the stability as maturity: the analysis surface has been fixed for years and the maintainer is keeping it installable.

◆ Prediction

R has continued to restrict its non-API C entry points, and this package has already made two such migrations, so further compile-time compliance work is the most likely content of the next release.

Alternatives to collapse and qtl

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 collapse or qtl.

See all collapse alternatives → · See all qtl alternatives →

Recent activity from collapse and qtl

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  2. 7mo agocollapseNegative zero now hashes equal to zero across the package
  3. 8mo agoqtlRemove R_ext/PrtUtil.h include flagged by CRAN
  4. 8mo agoqtlClearer cim() error when multiple phenotypes are passed
  5. 8mo agocollapsecollap() no longer double-aggregates external weights
  6. 9mo agocollapseCustom unlist() preserves attributes
  7. 0y agocollapseAssorted bug fixes
  8. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  9. 1y agoqtlC memory calls migrated to R_Calloc/R_Realloc/R_Free
  10. 2y agoqtlFix Rprintf call and remaining compiler warnings
  11. 2y agoqtlFix summary.scanone() thresholds and csvs phenotype reading
  12. 3y agoqtlFix addint()/addcovarint() with X chromosome QTL and missing phenotypes

Frequently asked questions

What is the difference between collapse and qtl?

Both compete on the same themes — r-package — within Analytics. collapse and qtl 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 collapse better than qtl?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. collapse and qtl 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 collapse?

Top collapse alternatives in Analytics are ranked by recent ship velocity. Browse the "collapse alternatives" section above for the current picks, or visit /alternatives/collapse-r for the full list with editorial commentary on each.

What are the best alternatives to qtl?

Top qtl alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl alternatives" section above for the current picks, or visit /alternatives/qtl-r for the full list with editorial commentary on each.