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

Spatial quantile normalization

Bioconductor version: Development (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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


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 1.17.0
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_1.17.0.tar.gz
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macOS Binary (x86_64) spqn_1.17.0.tgz
macOS Binary (arm64) spqn_1.17.0.tgz
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Source Repository (Developer Access) git clone
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