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Comparison · Analytics
reliaplotr vs UCell
A side-by-side editorial comparison of reliaplotr and UCell — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
reliaplotr vs UCell: at a glance
What is reliaplotr?
The Weibull plotting package renamed itself, then handed its charts to AI assistants.
ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.
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.
reliaplotr vs UCell: editorial side-by-side
reliaplotr
0.0ANALYTICS
The Weibull plotting package renamed itself, then handed its charts to AI assistants.
◆ Current state
ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.
◆ Where it's heading
The package has been following its analysis siblings function for function: as accelerated life testing and repairable systems modelling landed in the wider suite, the matching plot types appeared here, and when the growth-analysis package shipped an MCP server, this one followed two weeks later. The tidy extractors point the same way — a plotting package that can also return parameter estimates, goodness-of-fit metrics, and confidence bounds as tidy frames is one designed to be consumed programmatically, by a pipeline or an assistant, not only read on screen. Overlaying multiple model fits on a single plot has been a recurring request answered across several releases.
◆ Prediction
Expect the tidy extractor and MCP tool surfaces to keep expanding together, since each new plot type in the suite now implies both a chart and a machine-readable version of what it shows.
UCell
0.0ANALYTICS
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 reliaplotr 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 reliaplotr or UCell.
dynwrap
A dormant trajectory-inference wrapper wakes up for maintenance only
tEDM
The temporal half of the stscl EDM pair, tracking its spatial sibling
spEDM
Spatial causal discovery in R, one exposed method per release
sccore
Shared plumbing for the Kharchenko single-cell stack, updated once a year
rdataone
The R client for DataONE ships slow, correctness-focused maintenance
See all reliaplotr alternatives → · See all UCell alternatives →
Recent activity from reliaplotr and UCell
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoreliaplotrTidy model extractors plus five plotting tools over MCP ⚡
- 2mo agoreliaplotrNHPP plots switch to the mean cumulative function
- 3mo agoUCellTracks Bioconductor 3.23 and points to a Python port
- 4mo agoreliaplotrAccelerated life testing and repairable systems plots added
- 8mo agoreliaplotrDuane plots gain confidence bounds
- 9mo agoUCellUCell version 2.14
- 9mo agoreliaplotrReliaPlotR v0.4.1
- 10mo agoreliaplotrRenamed from WeibullR.plotly to ReliaPlotR
- 2y agoUCellUCell version 2.8
- 2y agoUCellUCell version 2.6
- 3y agoUCellUCell version 2.4
- 3y agoUCellUCell version 2.2
Frequently asked questions
What is the difference between reliaplotr and UCell?
Both compete on the same themes — r-package — within Analytics. reliaplotr 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 reliaplotr better than UCell?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. reliaplotr 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 reliaplotr?
Top reliaplotr alternatives in Analytics are ranked by recent ship velocity. Browse the "reliaplotr alternatives" section above for the current picks, or visit /alternatives/reliaplotr 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.