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segregatr vs tulpa

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

segregatr vs tulpa: at a glance

Featuresegregatrtulpa
SectorAnalyticsAnalytics
Velocity score0.07.5
Sparks · 30d02
Top themesstatistical-genetics, pedigree-analysis, variant-classification, pedsuitebayesian-inference, cran-release, r-packages, spatial-modeling
Last editorial update3d ago11h ago
WebsiteVisit →Visit →

What is segregatr?

A segregation-analysis tool that keeps widening which pedigrees it can actually handle.

segregatr computes full-likelihood Bayes factors for variant segregation in families, built on pedtools and part of the wider pedsuite ecosystem. Its releases are infrequent but each one lifts a structural restriction: loops, recessive and X-linked models, liability classes, and most recently a proband-free variant of the score. The companion shinyseg app gives the same machinery a clinical front end.

Read the full segregatr trajectory →

What is tulpa?

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

Read the full tulpa trajectory →

segregatr vs tulpa: editorial side-by-side

S
segregatr
ANALYTICS
0.0

A segregation-analysis tool that keeps widening which pedigrees it can actually handle.

◆ Current state

segregatr computes full-likelihood Bayes factors for variant segregation in families, built on pedtools and part of the wider pedsuite ecosystem. Its releases are infrequent but each one lifts a structural restriction: loops, recessive and X-linked models, liability classes, and most recently a proband-free variant of the score. The companion shinyseg app gives the same machinery a clinical front end.

◆ Where it's heading

The through-line is coverage of awkward real-world pedigrees rather than new statistics. Loops were handled for the core score in 0.3.0 and then extended to liability classes in 0.4.0, so the same structural capability is being pushed through the codebase feature by feature. The 2025 release moves in a different direction, relaxing the requirement for a designated proband. Development is slow and steady, roughly annual, and tracks its pedtools dependency closely.

◆ Prediction

Expect the next release to continue relaxing modelling constraints — the pattern of retrofitting each new capability across loops, liability classes and inheritance models is unfinished — rather than expanding beyond segregation scoring.

T
tulpa
ANALYTICS
7.5

The 0.0.x train stops at CRAN: tulpa's engine ships to the ecosystem it already anchors.

◆ Current state

tulpa is the C++/R Bayesian spatial inference engine sitting under gcol33's family of ecological occupancy packages, tagging 0.0.x releases several times a week. 0.1.0 is its first CRAN release, and the notes state outright that the engine surface is unchanged from 0.0.198 — the work is packaging discipline: local T bindings rebound to n_t/n_times, OpenMP teams capped under R CMD check, the pkgdown deploy narrowed, an aspell dictionary added. The window behind it splits between the S3 generics conversion and numerical-correctness work in the nested-Laplace grid.

◆ Where it's heading

Two moves in nine days point at the same destination: the generics conversion made tulpa extensible by downstream packages, and CRAN admission makes it installable by them. The current cadence — several tags a week, some existing only to record a measurement that produced no code change — does not survive CRAN's submission overhead, so the release rhythm has to slow whether or not the project intends it. The correctness work still clusters on the joint nested-Laplace driver, and 0.1.0 extends the same diagnostics habit with .NL_AXIS_SD_REASONS, a closed vocabulary for an outer axis whose grid does not contain its own posterior mode.

◆ Prediction

Expect tulpaObs to follow tulpa onto CRAN, since it is the consumer whose registrations the engine has spent this window unblocking, and expect the version line to move in larger, less frequent steps now that each one carries a submission.

Alternatives to segregatr and tulpa

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 segregatr or tulpa.

See all segregatr alternatives → · See all tulpa alternatives →

Recent activity from segregatr and tulpa

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

  1. 21h agotulpaFirst CRAN release: engine surface unchanged from 0.0.198
  2. 4d agotulpatulpa_re_aghq() exposes the mode/theta cross-Hessian
  3. 8d agotulpaDense batched joint path could silently drop a grid cell
  4. 8d agotulpaCalibration and goodness-of-fit entry points become S3 generics
  5. 9d agotulpaCUDA backend had two definitions; link order decided if it ran
  6. 9d agotulpaHyperparameter bounds now flag when they leave the node range
  7. 11mo agosegregatrProband-free variant of the FLB score
  8. 2y agosegregatrLiability classes now work in looped pedigrees
  9. 3y agosegregatrsegregatr 0.3.0

Frequently asked questions

What is the difference between segregatr and tulpa?

They serve adjacent needs but don't currently overlap on shipped themes. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is segregatr better than tulpa?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tulpa is currently shipping more aggressively (velocity 7.5 vs 0.0), with 2 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to segregatr?

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

What are the best alternatives to tulpa?

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