metadeconfoundR: Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional Data

Using non-parametric tests, naive associations between omics features and metadata in cross-sectional data-sets are detected. In a second step, confounding effects between metadata associated to the same omics feature are detected and labeled using nested post-hoc model comparison tests, as first described in Forslund, Chakaroun, Zimmermann-Kogadeeva, et al. (2021) <doi:10.1038/s41586-021-04177-9>. The generated output can be graphically summarized using the built-in plotting function.

Version:	1.0.2
Depends:	R (≥ 3.5.0), detectseparation
Imports:	lmtest, foreach, parallel, doParallel, stats, futile.logger, lme4, ggplot2, reshape2, methods, rlang
Suggests:	pander, knitr, gridExtra, kableExtra
Published:	2024-06-25
DOI:	10.32614/CRAN.package.metadeconfoundR
Author:	Till Birkner [aut, cre], Sofia Kirke Forslund-Startceva [ctb]
Maintainer:	Till Birkner <metadeconf at till-birkner.de>
BugReports:	https://github.com/TillBirkner/metadeconfoundR/issues
License:	GPL-2
URL:	https://github.com/TillBirkner/metadeconfoundR
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	metadeconfoundR results

Documentation:

Reference manual:	metadeconfoundR.pdf
Vignettes:	Introduction to metadeconfoundR

Downloads:

Package source:	metadeconfoundR_1.0.2.tar.gz
Windows binaries:	r-devel: metadeconfoundR_1.0.2.zip, r-release: not available, r-oldrel: metadeconfoundR_1.0.2.zip
macOS binaries:	r-release (arm64): metadeconfoundR_1.0.2.tgz, r-oldrel (arm64): metadeconfoundR_1.0.2.tgz, r-release (x86_64): metadeconfoundR_1.0.2.tgz, r-oldrel (x86_64): metadeconfoundR_1.0.2.tgz

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