EvoPhylo
EvoPhylo added BEAST2 alongside MrBayes, then went quiet for two years.
Comparison · Analytics
distributional vs qtl
A side-by-side editorial comparison of distributional and qtl — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
distributional vs qtl: at a glance
What is distributional?
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
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.
distributional vs qtl: editorial side-by-side
distributional
0.0ANALYTICS
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
◆ Current state
The R package providing vectorised distribution objects — the substrate that forecasting and anomaly tooling in the same ecosystem builds on. Cadence has picked up sharply, with four releases in the six months to June 2026 against roughly one a year before that. Two kinds of work alternate: adding distribution families (Dirichlet, Horseshoe, Laplace, multivariate t, g-and-k, the extreme-value pair) and deepening what can be computed generically across all of them.
◆ Where it's heading
The generic-computation thread is the one that matters and it has been building steadily: a Monte Carlo default method for cdf(), has_symmetry() to let algorithms specialise, hdr() moving to exact results for symmetric distributions and 4096 quantiles elsewhere, open-versus-closed support intervals. Version 0.8.0 is where that thread arrives somewhere — arithmetic on arbitrary distributions, with closed forms used when they exist and numerical convolution when they do not. The package is positioning itself as a computational layer rather than a catalogue, which is consistent with how weird and the forecasting packages consume it.
◆ Prediction
Expect the numerical machinery behind dist_convolved() to be reused for other operators, and more generics like has_symmetry() that let downstream algorithms take exact paths when a distribution supports them.
qtl
0.0ANALYTICS
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 distributional 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 distributional or qtl.
treespace
treespace ships once every year or two, and only when CRAN or a user forces it.
Rpath
Rpath 1.1.0 learns to read Ecopath's own files, easing migration off the desktop tool.
TAF
TAF keeps turning ICES stock assessments into reproducible, dependency-pinned projects.
parallelDist
parallelDist is in pure preservation mode — one build fix every few years.
cairo
Cairo finally catches R's graphics engine, all the way to GE API 16.
See all distributional alternatives → · See all qtl alternatives →
Recent activity from distributional and qtl
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
- 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators ⚡
- 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
- 5mo agodistributionalDirichlet and Horseshoe distributions added
- 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
- 8mo agoqtlRemove R_ext/PrtUtil.h include flagged by CRAN
- 8mo agoqtlClearer cim() error when multiple phenotypes are passed
- 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
- 1y agoqtlC memory calls migrated to R_Calloc/R_Realloc/R_Free
- 2y agoqtlFix Rprintf call and remaining compiler warnings
- 2y agoqtlFix summary.scanone() thresholds and csvs phenotype reading
- 3y agoqtlFix addint()/addcovarint() with X chromosome QTL and missing phenotypes
Frequently asked questions
What is the difference between distributional and qtl?
Both compete on the same themes — r-package — within Analytics. distributional 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 distributional better than qtl?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributional 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 distributional?
Top distributional alternatives in Analytics are ranked by recent ship velocity. Browse the "distributional alternatives" section above for the current picks, or visit /alternatives/distributional-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.