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Comparison · Analytics

cTMed vs qtl2

A side-by-side editorial comparison of cTMed and qtl2 — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

cTMed vs qtl2: at a glance

FeaturecTMedqtl2
SectorAnalyticsAnalytics
Velocity score2.52.5
Sparks · 30d00
Top themesmediation-analysis, continuous-time-models, r-package, statistical-methodsqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago48m ago
WebsiteVisit →Visit →

What is cTMed?

Continuous-time mediation effects get standardized centrality, six years into steady patch work

cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.

Read the full cTMed trajectory →

What is qtl2?

The standard QTL mapping package in R opened its genome scan to user-supplied likelihood models.

qtl2 is the R toolkit for QTL mapping in experimental crosses, covering genotype probability calculation, genome scans with and without polygenic effects, permutation testing, SNP association, and the plotting that goes with them. The last year of work has pushed hard in two directions: tooling for high-throughput expression and protein QTL studies, and a generalisation of the scan engine itself so the log-likelihood being maximised can be supplied by the user. Note that the release history reached this feed out of order, so feed position is not a reliable guide to which release came first.

Read the full qtl2 trajectory →

cTMed vs qtl2: editorial side-by-side

C
cTMed
ANALYTICS
2.5

Continuous-time mediation effects get standardized centrality, six years into steady patch work

◆ Current state

cTMed computes direct, indirect and total effects for continuous-time mediation models, with delta-method, Monte Carlo and bootstrap variants of each. Development is a long run of patch releases from the jeksterslab account, roughly every two months, each adding a function or two. The latest adds standardized centrality measures and allows a diagonal sigma across ten standardized estimators.

◆ Where it's heading

The package is filling out a matrix rather than changing shape: for each effect type there is a delta-method, a Monte Carlo and a bootstrap path, and each release closes another cell. The 2025 releases were largely externally forced — an Armadillo 15.0.x transition at CRAN, a citation addition after the Psychological Methods paper landed — which suggests the statistical core has been settled since the 1.0.6 standardization revision.

◆ Prediction

The diagonal-sigma option has now reached the standardized estimators; extending it to the remaining unstandardized variants is the obvious next cell to fill.

Q
qtl2
ANALYTICS
2.5

The standard QTL mapping package in R opened its genome scan to user-supplied likelihood models.

◆ Current state

qtl2 is the R toolkit for QTL mapping in experimental crosses, covering genotype probability calculation, genome scans with and without polygenic effects, permutation testing, SNP association, and the plotting that goes with them. The last year of work has pushed hard in two directions: tooling for high-throughput expression and protein QTL studies, and a generalisation of the scan engine itself so the log-likelihood being maximised can be supplied by the user. Note that the release history reached this feed out of order, so feed position is not a reliable guide to which release came first.

◆ Where it's heading

The eQTL and pQTL direction is the clearest thread — cis-trans plots, hotspot counting over a sliding window, multi-trait scan heat maps, and genome-wide genotype plots all arrived together, which is the toolkit an experiment with thousands of traits needs rather than one with a handful. Running underneath it is a steady generalisation of the core: a scan function that accepts an arbitrary likelihood, permutations that work with alternative scan functions, full variance-covariance output from single-position fits. Performance and parallelism get attention each cycle, including a more considerate default that leaves one core free. The rest is the ordinary maintenance of a long-lived package — renames to avoid tidyverse collisions, compiler warnings, and correctness fixes on specific cross types.

◆ Prediction

With scan1gen and permutation support for alternative scan functions in place, the natural next step is more model types built on that hook rather than more special-cased scan functions; the entries do not indicate which models are planned.

Alternatives to cTMed and qtl2

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 cTMed or qtl2.

See all cTMed alternatives → · See all qtl2 alternatives →

Recent activity from cTMed and qtl2

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

  1. 27d agocTMedStandardized centrality measures and diagonal-sigma support
  2. 27d agoqtl2chr_lengths() extended to cross2 objects
  3. 1mo agoqtl2A genome scan that takes your own likelihood function
  4. 2mo agoqtl2Hotspot counting and cis-trans plots for eQTL studies
  5. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  6. 6mo agocTMedMinor method edits
  7. 10mo agocTMedPackage citation added for the Psychological Methods paper
  8. 10mo agocTMedArmadillo 15.0.x compatibility for CRAN
  9. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  10. 1y agoqtl2CSV readers renamed to avoid the readr collision
  11. 1y agocTMedStandardization reworked around the steady-state covariance matrix
  12. 1y agocTMedBootstrap centrality estimators and MCPhiSigma()

Frequently asked questions

What is the difference between cTMed and qtl2?

Both compete on the same themes — r-package — within Analytics. cTMed and qtl2 are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 cTMed better than qtl2?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cTMed and qtl2 are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 cTMed?

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

What are the best alternatives to qtl2?

Top qtl2 alternatives in Analytics are ranked by recent ship velocity. Browse the "qtl2 alternatives" section above for the current picks, or visit /alternatives/qtl2 for the full list with editorial commentary on each.