vim
Six dormant years end with a correctness audit across VIM's entire imputation surface
A side-by-side editorial comparison of fitVARMxID and qtl2 — release velocity, themes, recent moves, and the top alternatives to consider.
A VAR-model fitting package acquiring the standard R methods it launched without
fitVARMxID fits vector autoregressive models via OpenMx identification, and is one of several packages maintained by the jeksterslab account. Its recent releases are small and additive: confint() and plot() methods, a save function, and before that a documentation pass. The feed also carries automated build commits that are pure CI artifacts.
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.
fitVARMxID fits vector autoregressive models via OpenMx identification, and is one of several packages maintained by the jeksterslab account. Its recent releases are small and additive: confint() and plot() methods, a save function, and before that a documentation pass. The feed also carries automated build commits that are pure CI artifacts.
This is a package settling into R conventions rather than growing capability. Adding confint() and plot() is the standard-methods work most modeling packages do once the estimation core is stable — it signals the author considers the fitting side done. Cadence is roughly quarterly and the changes get smaller each time.
Further method coverage — summary(), predict(), or coef() — is the likely next step, since confint() and plot() are usually the first two of that set rather than the last.
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.
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.
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.
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 fitVARMxID or qtl2.
Six dormant years end with a correctness audit across VIM's entire imputation surface
A dormant table-formatting package woken by a 20-PR correctness and coverage sweep
The write half of the Antares R toolchain, hitting 1.0 by tracking the simulator rather than stabilizing
The R reader for Antares Simulator studies, pinned to whatever the simulator ships next
The out-of-memory backend for R/qtl2, feature-complete since 2020 and now purely on upkeep
A single-purpose mouse map interpolator that solved its problem in 2023 and has coasted since
See all fitVARMxID alternatives → · See all qtl2 alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. fitVARMxID 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fitVARMxID 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.
Top fitVARMxID alternatives in Analytics are ranked by recent ship velocity. Browse the "fitVARMxID alternatives" section above for the current picks, or visit /alternatives/fitvarmxid for the full list with editorial commentary on each.
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.