uncertR: Bootstrap Prediction Uncertainty and Its Biological Drivers in Gene-Expression Models

Fits bootstrap ensembles of penalized regression models on bulk gene-expression data, derives per-sample uncertainty scores from out-of-bag predictions, and tests whether technical covariates explain that uncertainty. The bootstrap method is described by Efron and Tibshirani (1993, ISBN:9780412042317), and elastic-net regression follows Friedman, Hastie, and Tibshirani (2010) <doi:10.18637/jss.v033.i01>. The optional immunedeconv package, used for immune-cell deconvolution, is available from GitHub <https://github.com/omnideconv/immunedeconv>.

Version:	0.1.3
Depends:	R (≥ 4.2.0)
Imports:	glmnet, future.apply, splines, stats, graphics
Suggests:	testthat (≥ 3.0.0), SummarizedExperiment, knitr, rmarkdown, immunedeconv
Published:	2026-11-03
DOI:	10.32614/CRAN.package.uncertR (may not be active yet)
Author:	Tanay Belapurkar [aut, cre]
Maintainer:	Tanay Belapurkar <btanay041 at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
CRAN checks:	uncertR results

Documentation:

Reference manual:	uncertR.html , uncertR.pdf
Vignettes:	Getting started with uncertR (source)

Downloads:

Package source:	uncertR_0.1.3.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): uncertR_0.1.3.tgz, r-oldrel (x86_64): uncertR_0.1.3.tgz

Linking:

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