incident.io
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A side-by-side editorial comparison of ddml and onemap — release velocity, themes, recent moves, and the top alternatives to consider.
Double machine learning in R keeps adding estimands and the inference to go with them.
ddml implements double and debiased machine learning estimators, with a stacking layer so the nuisance functions can be fit by an ensemble rather than a single learner. The estimand list has grown from partially linear models to average treatment effects, treatment effects on the treated, and local average treatment effects, and 0.3.0 added one-way clustered inference. The most recent release is maintenance: xgboost syntax, glmnet binomial predictions, weights in the flexible partially linear IV estimator.
A genetic-mapping mainstay that now points new users toward MAPpoly at load time
OneMap constructs genetic linkage maps for experimental crosses, and its 3.x line turned it into a hub in a wider mapping toolchain: export functions for VIEWpoly and QTLpoly, summary and interactive ordering functions adapted from MAPpoly, and retention of reference and alternative allele information from imported VCFs. The most recent release, 3.2.0 in January 2025, adds an announcement about MAPpoly to the README and the package load message, fixes a subscript-out-of-bounds warning in rf_2pts and refreshes vignettes and tests.
ddml implements double and debiased machine learning estimators, with a stacking layer so the nuisance functions can be fit by an ensemble rather than a single learner. The estimand list has grown from partially linear models to average treatment effects, treatment effects on the treated, and local average treatment effects, and 0.3.0 added one-way clustered inference. The most recent release is maintenance: xgboost syntax, glmnet binomial predictions, weights in the flexible partially linear IV estimator.
Two lines of work run in parallel. One extends what can be estimated, the other makes the estimates trustworthy under real data conditions, and the second is where the recent effort has gone: clustered standard errors, propensity score trimming, higher default fold counts, corrected ATE and LATE scores. Raising sample_folds and cv_folds to ten is a small change with a clear intent, trading compute for stability.
Clustered inference arrived one-way; two-way and multi-way clustering are the obvious continuation. The stacking layer is also accumulating edge-case handling, so expect more work on degenerate ensemble weights.
OneMap constructs genetic linkage maps for experimental crosses, and its 3.x line turned it into a hub in a wider mapping toolchain: export functions for VIEWpoly and QTLpoly, summary and interactive ordering functions adapted from MAPpoly, and retention of reference and alternative allele information from imported VCFs. The most recent release, 3.2.0 in January 2025, adds an announcement about MAPpoly to the README and the package load message, fixes a subscript-out-of-bounds warning in rf_2pts and refreshes vignettes and tests.
Versions 3.0.0 and 3.1.0 were driven by a benchmarking preprint on genotyping-by-sequencing best practice, and their content follows directly: marker filtering from two-point estimates, memory reduction after filtering, and optimisation of find_bins and map_avoid_unlinked. What has happened since is signposting rather than capability — a package that spent two releases integrating with MAPpoly now tells users about it every time it loads. The pre-3.0 tags are backfilled, with versions 2.3 through 2.7 sharing a single August 2021 timestamp, so their order carries no information.
The load-message announcement suggests attention is flowing toward the MAPpoly side of the toolchain; expect maintenance and compatibility releases here rather than new mapping algorithms.
Other Infra & APIs 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 ddml or onemap.
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Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. ddml and onemap are shipping at a similar cadence (velocity 0.0 vs 0.0, 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. ddml and onemap are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top ddml alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ddml alternatives" section above for the current picks, or visit /alternatives/ddml for the full list with editorial commentary on each.
Top onemap alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "onemap alternatives" section above for the current picks, or visit /alternatives/onemap for the full list with editorial commentary on each.