simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of glydraw and STACAS — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.
STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.
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.
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.
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.
STACAS integrates single-cell RNA-seq datasets by finding and weighting anchors between them, with rPCA-distance-based downweighting and an optional semi-supervised mode that uses cell type labels to discard inconsistent anchors. IntegrateData.STACAS() performs the integration natively rather than handing off, and StandardizeGeneSymbols() normalises gene naming across datasets before anchors are computed.
The method work concentrated in version 2.0 and has been stable since; everything after is Seurat compatibility and operational robustness. Versions 2.1.1 through 2.3.0 track Seurat v5 assays, v3-to-v5 conversion, multi-layer objects and SCT normalisation, with the genuinely useful additions — a reference seed dataset, max.seed.datasets for large-scale integration, min.sample.size — arriving as side effects of that work. The package is from the same lab as GeneNMF, and its release rhythm follows the single-cell ecosystem's upstream churn rather than an internal roadmap.
Expect the next release to follow further Seurat object-model changes, which have driven the last three. Nothing in the entries indicates new anchor-scoring or correction methodology in progress.
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 glydraw or STACAS.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all glydraw alternatives → · See all STACAS alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
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.
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.
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.
Top STACAS alternatives in Analytics are ranked by recent ship velocity. Browse the "STACAS alternatives" section above for the current picks, or visit /alternatives/stacas for the full list with editorial commentary on each.