nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
forecasting vs UCell
A side-by-side editorial comparison of forecasting and UCell — release velocity, themes, recent moves, and the top alternatives to consider.
forecasting vs UCell: at a glance
What is forecasting?
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
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.
forecasting vs UCell: editorial side-by-side
forecasting
0.0ANALYTICS
HIDDA.forecasting is a book chapter's reproducibility artifact, not a package under development.
◆ Current state
HIDDA.forecasting accompanies a book chapter on forecasting infectious disease counts; its vignettes reproduce the results presented there using arima, prophet, glarma, hhh4contacts and scoringRules. The 1.0.0 release states this outright — it is the version used for the chapter, pinned to CRAN package versions as of July 2018. Every release since has been a vignette rebuild against newer R and dependency versions.
◆ Where it's heading
The release pattern is maintenance on an eight-year cadence dictated entirely by the surrounding ecosystem: 1.1.1 rebuilt under R 4.0.4, 1.1.2 under R 4.3.2, 1.1.3 under R 4.6.1, each reporting whether the numbers moved. They mostly have not — the recurring note is minor numerical differences confined to the prophet forecasts in vignette('CHILI_prophet'). The only substantive change in the visible history is 1.1.0's methodological tidy-up of the scoring comparisons.
◆ Prediction
Nothing in these entries points to new functionality; the next release is most likely another vignette rebuild whenever a dependency change or a CRAN check failure forces one.
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 forecasting 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 forecasting or UCell.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
robma
RoBMA 4.0 tears out its own constructor surface and rebuilds on one class hierarchy
See all forecasting alternatives → · See all UCell alternatives →
Recent activity from forecasting and UCell
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoforecastingVignettes rebuilt under R 4.6.1
- 3mo agoUCellTracks Bioconductor 3.23 and points to a Python port
- 9mo agoUCellUCell version 2.14
- 2y agoUCellUCell version 2.8
- 2y agoforecastingVignettes rebuilt under R 4.3.2
- 2y agoUCellUCell version 2.6
- 3y agoUCellUCell version 2.4
- 3y agoUCellUCell version 2.2
- 5y agoforecastingVignettes rebuilt under R 4.0.4
- 7y agoforecastingStandard PIT and discretized log-normal scoring
- 7y agoforecastingThe version used for the book chapter, with pinned dependencies
Frequently asked questions
What is the difference between forecasting and UCell?
They serve adjacent needs but don't currently overlap on shipped themes. forecasting 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 forecasting better than UCell?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. forecasting 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 forecasting?
Top forecasting alternatives in Analytics are ranked by recent ship velocity. Browse the "forecasting alternatives" section above for the current picks, or visit /alternatives/forecasting 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.