← Back to home
Comparison · Analytics

distributional vs qqman

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

distributional vs qqman: at a glance

Featuredistributionalqqman
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, probability-distributions, distribution-arithmetic, numerical-methodsgwas, genomics, manhattan-plot, visualization
Last editorial update7h ago1h ago
WebsiteVisit →Visit →

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.

Read the full distributional trajectory →

What is qqman?

The Manhattan-plot package for GWAS results, finished and dormant since 2017.

qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.

Read the full qqman trajectory →

distributional vs qqman: editorial side-by-side

D0.0

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.

Q
qqman
ANALYTICS
0.0

The Manhattan-plot package for GWAS results, finished and dormant since 2017.

◆ Current state

qqman does two things: manhattan() and qq() plots for genome-wide association study results. Its six visible releases run from 2014 to a single 2017 packaging fix, and the last release with any user-facing change shipped in 2015. The archive is non-monotonic — a 0.0.0 tag published after 0.1.1 archives the pre-package standalone script — so version order and publication order disagree.

◆ Where it's heading

The real development window was 2014 to 2015. The 0.1.2 release did the substantive work, replacing the assumption that SNPs are evenly distributed across chromosomes and handing users control of axis limits, labels and log transformation; 0.1.3 then added annotation by p-value threshold and top-SNP-per-chromosome. After that the package stops. Notably, the archival 0.0.0 entry records that the original script had confidence intervals on QQ plots and richer highlighting than the released package ever regained.

◆ Prediction

With one packaging fix in the last decade, these entries support no prediction of further releases. The package reads as complete for its narrow purpose rather than abandoned mid-arc.

Alternatives to distributional and qqman

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 qqman.

See all distributional alternatives → · See all qqman alternatives →

Recent activity from distributional and qqman

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

  1. 1mo agodistributionalConditional S3 registration so the package loads on R before 4.3
  2. 1mo agodistributionalDistribution arithmetic: FFT convolution behind the + and - operators
  3. 2mo agodistributionalVectorised p in quantile() for inflated distributions; open brackets on infinite bounds
  4. 5mo agodistributionalDirichlet and Horseshoe distributions added
  5. 7mo agodistributionalhas_symmetry() generic, exact HDRs for symmetric distributions
  6. 1y agodistributionalMonte Carlo cdf() default method; g-and-k, g-and-h and extreme-value families
  7. 9y agoqqmanREADME image path fix for pandoc
  8. 11y agoqqmanAnnotate SNPs by p-value threshold or per-chromosome top hit
  9. 11y agoqqmanChromosome ticks stop assuming even SNP spacing; axis control opens up
  10. 12y agoqqmanArchival tag for the pre-package standalone script
  11. 12y agoqqmanVignette touch-up
  12. 12y agoqqmanZenodo archival tag, no code change

Frequently asked questions

What is the difference between distributional and qqman?

They serve adjacent needs but don't currently overlap on shipped themes. distributional and qqman 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 qqman?

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

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