Package: metadeconfoundR 1.0.2

Till Birkner

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.

Authors:Till Birkner [aut, cre], Sofia Kirke Forslund-Startceva [ctb]

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Bug tracker:https://github.com/tillbirkner/metadeconfoundr/issues

On CRAN:

3 exports 14 stars 1.94 score 64 dependencies 8 scripts 792 downloads

Last updated 3 months agofrom:14a2a67d35. Checks:OK: 7. Indexed: yes.

Exports:BuildHeatmapImportLongPriorMetaDeconfound

Dependencies:backportsbootcallrcheckmateclicodetoolscolorspacedescdetectseparationdoParallelfansifarverforeachformatRfsfutile.loggerfutile.optionsggplot2gluegtableisobanditeratorslabelinglambda.rlatticelifecyclelme4lmtestlpSolveAPImagrittrMASSMatrixmgcvminqamunsellnlmenloptrpillarpkgbuildpkgconfigpkgloadplyrprocessxpsR6RColorBrewerRcppRcppEigenregistryreshape2rlangROIROI.plugin.lpsolverprojrootscalesslamstringistringrtibbleutf8vctrsviridisLitewithrzoo