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metadeconfoundR  

Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional Data
View on CRAN: Click here


Download and install metadeconfoundR package within the R console
Install from CRAN:
install.packages("metadeconfoundR")

Install from Github:
library("remotes")
install_github("cran/metadeconfoundR")

Install by package version:
library("remotes")
install_version("metadeconfoundR", "1.0.2")



Attach the package and use:
library("metadeconfoundR")
Maintained by
Till Birkner
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-06-25
Latest Update: 2024-06-25
Description:
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.
How to cite:
Till Birkner (2024). metadeconfoundR: Covariate-Sensitive Analysis of Cross-Sectional High-Dimensional Data. R package version 1.0.2, https://cran.r-project.org/web/packages/metadeconfoundR. Accessed 12 Nov. 2024.
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