quantro

This is the development version of quantro; for the stable release version, see quantro.

A test for when to use quantile normalization


Bioconductor version: Development (3.21)

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] (ORCID: ), Rafael Irizarry [aut] (ORCID: )

Maintainer: Stephanie Hicks <shicks19 at jhu.edu>

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

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("quantro")

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

Documentation

Reference Manual PDF

Details

biocViews Microarray, MultipleComparison, Normalization, Preprocessing, Sequencing, Software
Version 1.41.0
In Bioconductor since BioC 3.0 (R-3.1) (10 years)
License GPL-3
Depends R (>= 4.0)
Imports Biobase, minfi, doParallel, foreach, iterators, ggplot2, methods, RColorBrewer
System Requirements
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Suggests rmarkdown, knitr, RUnit, BiocGenerics, BiocStyle
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Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/quantro
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/quantro
Package Short Url https://bioconductor.org/packages/quantro/
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