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Spatial quantile normalization

Bioconductor version: Release (3.19)

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>

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


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:

spqn User's Guide HTML R Script
Reference Manual PDF


biocViews GraphAndNetwork, NetworkInference, Normalization, Software
Version 1.16.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License Artistic-2.0
Depends R (>= 4.0), ggplot2, ggridges, SummarizedExperiment, BiocGenerics
Imports graphics, stats, utils, matrixStats
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Suggests BiocStyle, knitr, rmarkdown, tools, spqnData(>= 0.99.3), RUnit
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Follow Installation instructions to use this package in your R session.

Source Package spqn_1.16.0.tar.gz
Windows Binary
macOS Binary (x86_64) spqn_1.16.0.tgz
macOS Binary (arm64) spqn_1.16.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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Old Source Packages for BioC 3.19 Source Archive