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A mass spectrometry imaging toolbox for statistical analysis

Bioconductor version: Release (3.19)

Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.

Author: Kylie Ariel Bemis [aut, cre]

Maintainer: Kylie Ariel Bemis <k.bemis at>

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


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:

1. Cardinal 3: User guide for mass spectrometry imaging analysis HTML R Script
2. Cardinal 3: Statistical methods for mass spectrometry imaging HTML R Script
Reference Manual PDF


biocViews Classification, Clustering, ImagingMassSpectrometry, ImmunoOncology, Infrastructure, Lipidomics, MassSpectrometry, Normalization, Proteomics, Regression, Software
Version 3.6.4
In Bioconductor since BioC 3.1 (R-3.2) (9.5 years)
License Artistic-2.0
Depends R (>= 4.3), ProtGenerics, BiocGenerics, BiocParallel, S4Vectors(>= 0.27.3), methods, stats, stats4
Imports CardinalIO, Biobase, EBImage, graphics, grDevices, irlba, Matrix, matter(>= 2.6.2), nlme, parallel, utils
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Follow Installation instructions to use this package in your R session.

Source Package Cardinal_3.6.4.tar.gz
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macOS Binary (x86_64) Cardinal_3.6.4.tgz
macOS Binary (arm64) Cardinal_3.6.4.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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