spqn

DOI: 10.18129/B9.bioc.spqn    

Spatial quantile normalization

Bioconductor version: Release (3.14)

The spqn package implements spatial quantile normalization (SpQN). This method was developed to remove a mean-correlation relationship in correlation matrices built from gene expression data. It can serve as pre-processing step prior to a co-expression analysis.

Author: Yi Wang [cre, aut], Kasper Daniel Hansen [aut]

Maintainer: Yi Wang <yiwangthu5 at gmail.com>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("spqn")

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

Documentation

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

browseVignettes("spqn")

 

HTML	R Script	spqn User's Guide
PDF		Reference Manual
Text		NEWS

Details

biocViews	GraphAndNetwork, NetworkInference, Normalization, Software
Version	1.6.0
In Bioconductor since	BioC 3.11 (R-4.0) (2 years)
License	Artistic-2.0
Depends	R (>= 4.0), ggplot2, ggridges, SummarizedExperiment, BiocGenerics
Imports	graphics, stats, utils, matrixStats
LinkingTo
Suggests	BiocStyle, knitr, rmarkdown, tools, spqnData(>= 0.99.3), RUnit
SystemRequirements
Enhances
URL	https://github.com/hansenlab/spqn
BugReports	https://github.com/hansenlab/spqn/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	spqn_1.6.0.tar.gz
Windows Binary	spqn_1.6.0.zip
macOS 10.13 (High Sierra)	spqn_1.6.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/spqn
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/spqn
Package Short Url	https://bioconductor.org/packages/spqn/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.14	Source Archive