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ggstats vs UCell

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

Shared themes:r-package

ggstats vs UCell: at a glance

FeatureggstatsUCell
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, likert, regression-modelsr-package, single-cell, gene-signatures, bioconductor
Last editorial update40m ago1h ago
WebsiteVisit →Visit →

What is ggstats?

ggstats keeps widening what a coefficient or Likert plot can be

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

Read the full ggstats trajectory →

What is UCell?

A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next

UCell scores gene signatures in single-cell data using a rank-based metric that is robust to dataset composition. Its release history reads as a sequence of ecosystem accommodations: Bioconductor submission in 2.0, SmoothKNN() for k-nearest-neighbor smoothing of scores in 2.2, smoothing applied directly to expression slots in 2.4, Seurat v5 assay compatibility in 2.6, multi-layer Seurat v5 objects in 2.8, and a missing_genes parameter in 2.14 that lets callers impute or skip signature genes absent from the data. Version 2.16 tracks Bioconductor 3.23 and points at a new publication and a Python implementation, pyUCell.

Read the full UCell trajectory →

ggstats vs UCell: editorial side-by-side

G
ggstats
ANALYTICS
0.0

ggstats keeps widening what a coefficient or Likert plot can be

◆ Current state

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

◆ Where it's heading

Two long-running threads. The coefficient side has been consolidating — ggcoef_multinom() and ggcoef_multicomponents() soft-deprecated in favour of a unified ggcoef_model() with group_by, plus new ggcoef_dodged() and ggcoef_faceted() variants. The Likert side keeps expanding outward instead, absorbing survey objects, total columns and side-by-side layouts. Underneath both is a steady tax of ggplot2 and vctrs compatibility work, including tracking the geom_errorbarh() deprecation in ggplot2 4.0.0.

◆ Prediction

Expect gglikert_side() to lose its experimental status once its interface settles, and the deprecated multinomial entry points to be removed in a future release now that ggcoef_model() covers their cases.

U
UCell
ANALYTICS
0.0

A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next

◆ Current state

UCell scores gene signatures in single-cell data using a rank-based metric that is robust to dataset composition. Its release history reads as a sequence of ecosystem accommodations: Bioconductor submission in 2.0, SmoothKNN() for k-nearest-neighbor smoothing of scores in 2.2, smoothing applied directly to expression slots in 2.4, Seurat v5 assay compatibility in 2.6, multi-layer Seurat v5 objects in 2.8, and a missing_genes parameter in 2.14 that lets callers impute or skip signature genes absent from the data. Version 2.16 tracks Bioconductor 3.23 and points at a new publication and a Python implementation, pyUCell.

◆ Where it's heading

Two threads run through this. The scoring algorithm itself has barely changed — the rank-based core is stable, and 2.14's reformatting to gene indices rather than string matching is a speed change, not a method change. What does change constantly is object-format compatibility, which is the tax of living between Seurat and SingleCellExperiment. The pyUCell reference in 2.16 is the first sign of the method reaching beyond R, though these notes say nothing about its scope.

◆ Prediction

The cadence is locked to Bioconductor's twice-yearly release train, so the next version will most likely accompany Bioconductor 3.24 with whatever Seurat or SingleCellExperiment changes it brings.

Alternatives to ggstats and UCell

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 ggstats or UCell.

See all ggstats alternatives → · See all UCell alternatives →

Recent activity from ggstats and UCell

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

  1. 3mo agoUCellTracks Bioconductor 3.23 and points to a Python port
  2. 5mo agoggstatsgglikert_side() and total columns for Likert plots
  3. 7mo agoggstatsLikert functions accept survey objects
  4. 9mo agoUCellUCell version 2.14
  5. 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
  6. 1y agoggstatsggstats 0.10.0
  7. 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
  8. 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added
  9. 2y agoUCellUCell version 2.8
  10. 2y agoUCellUCell version 2.6
  11. 3y agoUCellUCell version 2.4
  12. 3y agoUCellUCell version 2.2

Frequently asked questions

What is the difference between ggstats and UCell?

Both compete on the same themes — r-package — within Analytics. ggstats and UCell 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 ggstats better than UCell?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstats and UCell 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 ggstats?

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

What are the best alternatives to UCell?

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