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Comparison · Analytics
brglm2 vs glydraw
A side-by-side editorial comparison of brglm2 and glydraw — release velocity, themes, recent moves, and the top alternatives to consider.
brglm2 vs glydraw: at a glance
What is brglm2?
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
What is glydraw?
SNFG glycan cartoons stopped being pictures and became ggplot2 geoms, guides and axis labels.
glydraw renders glycan structures as SNFG-standard cartoons, standalone or exported in bulk, and since 0.7.0 as native ggplot2 components: geom_glycan() for observations, geom_node_glycan() for ggraph networks, guide_glycan() for legends, and scale_x_glycan() and scale_y_glycan() for discrete axes. Appearance is configured through a single reusable style object rather than scattered arguments, a consolidation that 0.8.0 made breaking. The colour handling now expects a complete SNFG palette rather than sparse per-monosaccharide overrides.
brglm2 vs glydraw: editorial side-by-side
brglm2
0.0ANALYTICS
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
◆ Current state
brglm2 fits generalized linear models using mean and median bias reduction rather than plain maximum likelihood, which matters most when ML estimates are infinite or badly biased. The 0.7-0.9 line broadened coverage — negative binomial via brnb(), ordinal superiority measures, the expo() method for exponentiated parameters, add1()/drop1() so step() stops silently producing nonsense. Version 1.0.0 in August 2025 added mdyplFit(), estimating logistic regression by maximum Diaconis-Ylvisaker prior penalized likelihood with optional high-dimensional corrections. The two releases since have tuned that new path.
◆ Where it's heading
The package's older work assumed the classical regime where observations comfortably outnumber parameters. mdyplFit() and its hd_correction argument target the opposite case, and the follow-up releases are almost entirely about it — Pearson residuals on original responses, aliased parameter handling, the sloe() signal-strength estimator ignoring leverage-one observations. Meanwhile the older surface gets graceful-failure work: brglm_fit() now returns its latest estimates with warnings rather than aborting.
◆ Prediction
Given that 1.0.1 and 1.1.0 are both dominated by mdyplFit follow-ups while the classical path receives only robustness fixes, further work on high-dimensional corrections is the likeliest direction.
glydraw
6.3ANALYTICS
SNFG glycan cartoons stopped being pictures and became ggplot2 geoms, guides and axis labels.
◆ Current state
glydraw renders glycan structures as SNFG-standard cartoons, standalone or exported in bulk, and since 0.7.0 as native ggplot2 components: geom_glycan() for observations, geom_node_glycan() for ggraph networks, guide_glycan() for legends, and scale_x_glycan() and scale_y_glycan() for discrete axes. Appearance is configured through a single reusable style object rather than scattered arguments, a consolidation that 0.8.0 made breaking. The colour handling now expects a complete SNFG palette rather than sparse per-monosaccharide overrides.
◆ Where it's heading
The first half of this record is geometry correctness, fixing branch spacing, overlapping linkage annotations, core fucose collisions, triangle alignment and nested side-chain layout, because a cartoon that draws the wrong topology is worse than no cartoon. Once the drawing was trustworthy the package moved outward into ggplot2 and then inward again to consolidate its own API, dropping the glyexp dependency, removing positional argument support, and folding rendering options into style_glydraw(). Each of the last several releases has been explicitly breaking, which is a maintainer using a pre-1.0 window deliberately.
◆ Prediction
With the style object established and the ggplot2 surface in place, the remaining explicit arguments, show_linkage and orient, are the visible inconsistency and may follow the others into the style. Sibling packages adopt each change within days, as glyenzy did with the new orientation values, so expect the next breaking change to propagate the same way.
Alternatives to brglm2 and glydraw
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 brglm2 or glydraw.
gcube
gcube's recent releases are all packaging metadata, not simulation code
cubist
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats
ggstats keeps widening what a coefficient or Likert plot can be
ecodive
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
simStateSpace
State-space data simulation for R, filled in one function at a time
See all brglm2 alternatives → · See all glydraw alternatives →
Recent activity from brglm2 and glydraw
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agoglydrawRendering options consolidated into a single style object
- 23d agoglydrawGlycan cartoons become ggplot2 geoms, legends and axis labels ⚡
- 1mo agoglydrawNested side-chain layout preserves residue order and linkage labels
- 1mo agoglydrawFucose triangle geometry aligned to rectangle node bounds
- 1mo agoglydrawCustom colours, fucose orientation and export scaling; glyexp dependency dropped
- 1mo agoglydrawSwitches to SNFG standard colours
- 3mo agobrglm2brglm2 v1.1.0
- 8mo agobrglm2brglm2 v1.0.1
- 11mo agobrglm21.0.0 adds maximum DY-prior penalized likelihood for logistic regression ⚡
- 1y agobrglm2brglm2 v0.9.3
- 1y agobrglm2brglm2 v0.9.2
- 3y agobrglm2brglm2 v0.9.1
Frequently asked questions
What is the difference between brglm2 and glydraw?
They serve adjacent needs but don't currently overlap on shipped themes. glydraw is currently shipping more aggressively (velocity 6.3 vs 0.0), 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 brglm2 better than glydraw?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. glydraw is currently shipping more aggressively (velocity 6.3 vs 0.0), 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 brglm2?
Top brglm2 alternatives in Analytics are ranked by recent ship velocity. Browse the "brglm2 alternatives" section above for the current picks, or visit /alternatives/brglm2 for the full list with editorial commentary on each.
What are the best alternatives to glydraw?
Top glydraw alternatives in Analytics are ranked by recent ship velocity. Browse the "glydraw alternatives" section above for the current picks, or visit /alternatives/glydraw for the full list with editorial commentary on each.