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 ORCID iD [aut, cre], Sofia Kirke Forslund-Startceva ORCID iD [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: metadeconfoundR_1.0.2.zip, 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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