RAMClustR: Mass Spectrometry Metabolomics Feature Clustering and Interpretation

A feature clustering algorithm for non-targeted mass spectrometric metabolomics data. This method is compatible with gas and liquid chromatography coupled mass spectrometry, including indiscriminant tandem mass spectrometry <doi:10.1021/ac501530d> data.

Version: 1.2.3
Depends: R (≥ 3.5.0)
Imports: dynamicTreeCut, fastcluster, ff, InterpretMSSpectrum, BiocManager, httr, jsonlite, preprocessCore, e1071, gplots, pcaMethods, stringr, xml2, utils, webchem, stringi, RCurl, ggplot2, readxl
Suggests: knitr, rmarkdown, xcms, testthat, MSnbase
Published: 2022-03-30
Author: Corey D. Broeckling, Fayyaz Afsar, Steffan Neumann, Asa Ben-Hur, Jessica Prenni.
Maintainer: "Broeckling,Corey" <Corey.Broeckling at ColoState.EDU>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/cbroeckl/RAMClustR
NeedsCompilation: no
Materials: README ChangeLog
CRAN checks: RAMClustR results


Reference manual: RAMClustR.pdf
Vignettes: RAMClustR: post-XCMS Feature Clustering


Package source: RAMClustR_1.2.3.tar.gz
Windows binaries: r-devel: RAMClustR_1.2.3.zip, r-release: RAMClustR_1.2.3.zip, r-oldrel: RAMClustR_1.2.3.zip
macOS binaries: r-release (arm64): RAMClustR_1.2.2.tgz, r-release (x86_64): RAMClustR_1.2.3.tgz, r-oldrel: not available
Old sources: RAMClustR archive


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