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MSclassifR: Automated Classification of Mass Spectra

Functions to classify mass spectra in known categories, and to determine discriminant mass-over-charge values. It includes easy-to-use functions for pre-processing mass spectra, functions to determine discriminant mass-over-charge values (m/z) from a library of mass spectra corresponding to different categories, and functions to predict the category (species, phenotypes, etc.) associated to a mass spectrum from a list of selected mass-over-charge values. Three vignettes illustrating how to use the functions of this package from real data sets are also available online to help users: <https://agodmer.github.io/MSclassifR_examples/Vignettes/Vignettemsclassifr_Ecrobiav3.html>, <https://agodmer.github.io/MSclassifR_examples/Vignettes/Vignettemsclassifr_Klebsiellav3.html> and <https://agodmer.github.io/MSclassifR_examples/Vignettes/Vignettemsclassifr_DAv3.html>.

Version: 0.3.3
Depends: R (≥ 4.0), cp4p, caret, statmod, MALDIquant, MALDIrppa
Imports: e1071, MALDIquantForeign, mixOmics, reshape2, ggplot2, nnet, dplyr, fuzzyjoin, VSURF, metap, xgboost, glmnet, performanceEstimation, mltools, mclust, UBL, stats, limma, car, vita, randomForest
Suggests: knitr, rmarkdown
Published: 2023-08-09
DOI: 10.32614/CRAN.package.MSclassifR
Author: Alexandre Godmer [aut, cre], Quentin Giai Gianetto [aut], Karen Druart [aut]
Maintainer: Alexandre Godmer <alexandre.godmer at aphp.fr>
License: GPL (≥ 3)
URL: https://github.com/agodmer/MSclassifR_examples
NeedsCompilation: yes
CRAN checks: MSclassifR results

Documentation:

Reference manual: MSclassifR.pdf

Downloads:

Package source: MSclassifR_0.3.3.tar.gz
Windows binaries: r-devel: MSclassifR_0.3.3.zip, r-release: MSclassifR_0.3.3.zip, r-oldrel: MSclassifR_0.3.3.zip
macOS binaries: r-release (arm64): MSclassifR_0.3.3.tgz, r-oldrel (arm64): MSclassifR_0.3.3.tgz, r-release (x86_64): MSclassifR_0.3.3.tgz, r-oldrel (x86_64): MSclassifR_0.3.3.tgz
Old sources: MSclassifR archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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