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Comparison · Analytics

gghighlight vs STACAS

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

Shared themes:r-package

gghighlight vs STACAS: at a glance

FeaturegghighlightSTACAS
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualisation, ggplot-extension, upstream-compatsingle-cell, batch-correction, data-integration, seurat
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is gghighlight?

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

Read the full gghighlight trajectory →

What is STACAS?

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.

Read the full STACAS trajectory →

gghighlight vs STACAS: editorial side-by-side

G
gghighlight
ANALYTICS
0.0

A single-purpose ggplot2 extension that has spent six years tracking ggplot2 instead of growing.

◆ Current state

gghighlight adds one verb to ggplot2: highlight the series matching a predicate and grey out the rest, with unhighlighted_params controlling how the shadowed layer renders and calculate_per_facet deciding whether the predicate evaluates within facets. The API settled at 0.2.0; the 0.5.0 release supports ggplot2 v4.0 including its ink and paper theme elements, and finally deletes gghighlight_point() and gghighlight_line().

◆ Where it's heading

Two threads run through the history. One is a slow deprecation, from soft-deprecating the geom-specific functions at 0.1.0, to defunct at 0.3.0, to removed at 0.5.0 — a five-year removal cycle. The other is compatibility work: purrr 1.0.0, dplyr's across() deprecation, ggplot2 3.4.0, then 4.0. Genuine feature additions are rare and small, with line_label_type at 0.4.0 the last one. Note that 0.3.2's notes restate 0.3.1's n() item, so adjacent tags here overlap rather than each describing distinct work.

◆ Prediction

The next release most likely absorbs further ggplot2 4.x changes, given that is what triggered the last three. Nothing in the entries points to a new highlighting capability.

S
STACAS
ANALYTICS
0.0

Single-cell batch correction that learned to use cell labels, then spent three releases chasing Seurat.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to gghighlight and STACAS

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 gghighlight or STACAS.

See all gghighlight alternatives → · See all STACAS alternatives →

Recent activity from gghighlight and STACAS

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

  1. 1y agogghighlightggplot2 v4.0 support; geom-specific functions removed
  2. 1y agoSTACASMulti-layer objects and Seurat v3-to-v5 conversion handled
  3. 2y agoSTACASscale.data option for extreme batch effects; gene name conversion table
  4. 2y agogghighlightTest expectations updated for upcoming ggplot2
  5. 3y agoSTACASReference seeding, gene symbol standardisation, large-scale integration path
  6. 3y agogghighlightline_label_type adds geomtextpath and second-axis labelling
  7. 4y agoSTACASSemi-supervised integration and rPCA anchor downweighting
  8. 4y agogghighlightDeprecated dplyr::across() usage removed
  9. 5y agogghighlightExplicit NULL in unhighlighted_params preserved; aesthetic name clash fixed
  10. 5y agoSTACASSeurat 4.0.0 compatibility and SCTransform support
  11. 5y agogghighlightDiscrete-scale labels and n() predicates

Frequently asked questions

What is the difference between gghighlight and STACAS?

Both compete on the same themes — r-package — within Analytics. gghighlight and STACAS 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.

Is gghighlight better than STACAS?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gghighlight and STACAS 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 Analytics products to evaluate alongside.

What are the best alternatives to gghighlight?

Top gghighlight alternatives in Analytics are ranked by recent ship velocity. Browse the "gghighlight alternatives" section above for the current picks, or visit /alternatives/gghighlight for the full list with editorial commentary on each.

What are the best alternatives to STACAS?

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.