spqn

Spatial quantile normalization


Bioconductor version: Release (3.20)

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>

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

Installation

To install this package, start R (version "4.4") 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")
spqn User's Guide HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews GraphAndNetwork, NetworkInference, Normalization, Software
Version 1.18.0
In Bioconductor since BioC 3.11 (R-4.0) (4.5 years)
License Artistic-2.0
Depends R (>= 4.0), ggplot2, ggridges, SummarizedExperiment, BiocGenerics
Imports graphics, stats, utils, matrixStats
System Requirements
URL https://github.com/hansenlab/spqn
Bug Reports https://github.com/hansenlab/spqn/issues
See More
Suggests BiocStyle, knitr, rmarkdown, tools, spqnData(>= 0.99.3), RUnit
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Package Archives

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

Source Package spqn_1.18.0.tar.gz
Windows Binary (x86_64) spqn_1.18.0.zip (64-bit only)
macOS Binary (x86_64) spqn_1.18.0.tgz
macOS Binary (arm64) spqn_1.18.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/spqn
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/spqn
Bioc Package Browser https://code.bioconductor.org/browse/spqn/
Package Short Url https://bioconductor.org/packages/spqn/
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