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glmbayes vs qtl2

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

Shared themes:r-package

glmbayes vs qtl2: at a glance

Featureglmbayesqtl2
SectorAnalyticsAnalytics
Velocity score6.32.5
Sparks · 30d10
Top themesbayesian-statistics, generalized-linear-models, opencl, r-packageqtl-mapping, statistical-genetics, bioinformatics, r-package
Last editorial update1h ago42m ago
WebsiteVisit →Visit →

What is glmbayes?

A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain

glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.

Read the full glmbayes 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 →

glmbayes vs qtl2: editorial side-by-side

G
glmbayes
ANALYTICS
6.3

A GPU-accelerated Bayesian GLM package buys its way into the standard R Bayesian toolchain

◆ Current state

glmbayes fits Bayesian generalized linear models with optional OpenCL acceleration. The last four months moved it from a package with its own vocabulary to one that answers the insight and bayestestR generics the rest of the R Bayesian ecosystem is built on, while pushing the OpenCL kernels out into a separate nmathopencl dependency that carries CRAN Windows binaries. It returned to CRAN in August after an archival over a configure policy issue.

◆ Where it's heading

The arc is about removing reasons not to use it. GPU support was previously blocked on Windows because the OpenCL kernels were vendored; splitting them into a CRAN package with binaries fixed that. The ecosystem work does the same thing for tooling — a glmb fit now responds to get_parameters, get_priors, simulate_prior and check_prior, so it drops into workflows built around easystats rather than requiring its own. The CRAN archival and the configure fixes that followed show how much of the effort goes into distribution rather than modelling.

◆ Prediction

get_priors() returning the full prior specification rather than a marginal table is the kind of detail that invites further bayestestR integration, and the diagnostic surface is the least built-out part of what has shipped so far.

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 glmbayes 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 glmbayes or qtl2.

See all glmbayes alternatives → · See all qtl2 alternatives →

Recent activity from glmbayes and qtl2

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

  1. 10d agoglmbayesBack on CRAN after a configure policy fix
  2. 22d agoglmbayesOpenCL split out to nmathopencl; insight and bayestestR integration
  3. 27d agoqtl2chr_lengths() extended to cross2 objects
  4. 1mo agoqtl2A genome scan that takes your own likelihood function
  5. 1mo agoglmbayesMulti-response models and conjugate GLM priors
  6. 2mo agoqtl2Hotspot counting and cis-trans plots for eQTL studies
  7. 3mo agoglmbayesOpenCL kernels restructured and a binomial GPU bug fixed
  8. 3mo agoglmbayesVersion bump for CRAN resubmission
  9. 3mo agoqtl2Confidence interval plotting, plus a documentation correction
  10. 1y agoglmbayesCRAN-ready beta with the core S3 interface
  11. 1y agoqtl2Finer-grained parallelism for kinship-based scans
  12. 1y agoqtl2CSV readers renamed to avoid the readr collision

Frequently asked questions

What is the difference between glmbayes and qtl2?

Both compete on the same themes — r-package — within Analytics. glmbayes is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 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 glmbayes better than qtl2?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. glmbayes is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 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 glmbayes?

Top glmbayes alternatives in Analytics are ranked by recent ship velocity. Browse the "glmbayes alternatives" section above for the current picks, or visit /alternatives/glmbayes 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.