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qtl2 vs semmcci

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

Shared themes:r-package

qtl2 vs semmcci: at a glance

Featureqtl2semmcci
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesqtl-mapping, statistical-genetics, bioinformatics, r-packagestructural-equation-modeling, monte-carlo, confidence-intervals, r-package
Last editorial update1h ago2h ago
WebsiteVisit →Visit →

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 →

What is semmcci?

Monte Carlo confidence intervals for SEM, now mostly reacting to upstream deprecations

semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.

Read the full semmcci trajectory →

qtl2 vs semmcci: editorial side-by-side

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.

S
semmcci
ANALYTICS
0.0

Monte Carlo confidence intervals for SEM, now mostly reacting to upstream deprecations

◆ Current state

semmcci generates Monte Carlo confidence intervals for structural equation model parameters, working alongside lavaan. Its four-year release history is a run of patch versions from the jeksterslab account, each adding a function or adjusting method detail. The recent ones are quieter still: the latest addresses a lavaan::getCov() deprecation in tests, and the one before it is described only as minor method edits.

◆ Where it's heading

The functional build-out finished some time ago. MCGeneric() in 1.1.3 and Func()/MCFunc() in 1.1.4 opened the package to user-defined functions of parameters, which is the natural end point for a Monte Carlo interval tool — once arbitrary functions are supported, there is little left to add. Since then releases have tracked lavaan's changes rather than semmcci's own direction, and the gap between them has stretched from months to over a year.

◆ Prediction

Expect the next release to be triggered by another lavaan deprecation rather than by new capability.

Alternatives to qtl2 and semmcci

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 qtl2 or semmcci.

See all qtl2 alternatives → · See all semmcci alternatives →

Recent activity from qtl2 and semmcci

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

  1. 27d agoqtl2chr_lengths() extended to cross2 objects
  2. 1mo agoqtl2A genome scan that takes your own likelihood function
  3. 2mo agosemmccilavaan getCov() deprecation handled in tests
  4. 2mo agoqtl2Hotspot counting and cis-trans plots for eQTL studies
  5. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  6. 10mo agosemmcciMinor method edits
  7. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  8. 1y agoqtl2CSV readers renamed to avoid the readr collision
  9. 2y agosemmcciUser-defined parameter functions via Func() and MCFunc()
  10. 2y agosemmcciMCGeneric() opens up arbitrary parameter targets
  11. 3y agosemmcciMultiple-imputation support via MCMI()
  12. 3y agosemmcciData generation internals refactored

Frequently asked questions

What is the difference between qtl2 and semmcci?

Both compete on the same themes — r-package — within Analytics. qtl2 is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 qtl2 better than semmcci?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. qtl2 is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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 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.

What are the best alternatives to semmcci?

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