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Random Rotation Methods for High Dimensional Data with Batch Structure

Bioconductor version: Release (3.19)

A collection of methods for performing random rotations on high-dimensional, normally distributed data (e.g. microarray or RNA-seq data) with batch structure. The random rotation approach allows exact testing of dependent test statistics with linear models following arbitrary batch effect correction methods.

Author: Peter Hettegger [aut, cre]

Maintainer: Peter Hettegger <p.hettegger at>

Citation (from within R, enter citation("randRotation")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Random Rotation Package Introduction PDF R Script
Reference Manual PDF


biocViews BatchEffect, BiomedicalInformatics, DifferentialExpression, GeneExpression, Genetics, MicroRNAArray, Microarray, Normalization, Preprocessing, RNASeq, Sequencing, Software, StatisticalMethod
Version 1.16.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL-3
Imports methods, graphics, utils, stats, Rdpack (>= 0.7)
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Suggests knitr, BiocParallel, lme4, nlme, rmarkdown, BiocStyle, testthat (>= 2.1.0), limma, sva
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Follow Installation instructions to use this package in your R session.

Source Package randRotation_1.16.0.tar.gz
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macOS Binary (x86_64) randRotation_1.16.0.tgz
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