A test for when to use quantile normalization

Bioconductor version: Release (3.19)

A data-driven test for the assumptions of quantile normalization using raw data such as objects that inherit eSets (e.g. ExpressionSet, MethylSet). Group level information about each sample (such as Tumor / Normal status) must also be provided because the test assesses if there are global differences in the distributions between the user-defined groups.

Author: Stephanie Hicks [aut, cre] , Rafael Irizarry [aut]

Maintainer: Stephanie Hicks <shicks19 at jhu.edu>

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


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The quantro user's guide HTML R Script
Reference Manual PDF


biocViews Microarray, MultipleComparison, Normalization, Preprocessing, Sequencing, Software
Version 1.38.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 years)
License GPL-3
Depends R (>= 4.0)
Imports Biobase, minfi, doParallel, foreach, iterators, ggplot2, methods, RColorBrewer
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Suggests rmarkdown, knitr, RUnit, BiocGenerics, BiocStyle
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Source Package quantro_1.38.0.tar.gz
Windows Binary quantro_1.38.0.zip
macOS Binary (x86_64) quantro_1.38.0.tgz
macOS Binary (arm64) quantro_1.38.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/quantro
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/quantro
Bioc Package Browser https://code.bioconductor.org/browse/quantro/
Package Short Url https://bioconductor.org/packages/quantro/
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