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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.
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Package details |
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| Author | Till Birkner [aut, cre] (<https://orcid.org/0000-0003-2656-2821>), Sofia Kirke Forslund-Startceva [ctb] (<https://orcid.org/0000-0003-4285-6993>) |
| Maintainer | Till Birkner <metadeconf@till-birkner.de> |
| License | GPL-2 |
| Version | 1.0.2 |
| URL | https://github.com/TillBirkner/metadeconfoundR |
| Package repository | View on CRAN |
| Installation |
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