Metabolomics and Spectral Data Analysis and Mining

Provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, feature selection and pathway analysis. Case studies can be found on the website: <>. 'rcytoscapejs' is not present in a mainstream repository, but it can be obtained by typing 'devtools::install_github('cytoscape/r-cytoscape.js')' on the R command line.


Reference manual

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2.0.3 by Miguel Rocha, a year ago

Browse source code at

Authors: Christopher Costa <[email protected]> [aut] , Marcelo Maraschin <[email protected]> [aut] , Miguel Rocha <[email protected]> [aut, cre] , Sara Cardoso <[email protected]> [aut] , Telma Afonso <[email protected] [aut]> , C. Beleites [ctb] , Jie Hao [ctb] , Daniel Jacob [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports compare, hyperSpec, readJDX, baseline, rgl, Metrics, GGally, ggplot2, ellipse, ggdendro, caret, pls, pcaPP, RColorBrewer, grid, methods, qdap, MASS, scatterplot3d, xcms, MAIT, genefilter, impute, igraph, KEGGgraph, KEGGREST, reticulate, gdata, speaq, devtools

Suggests rcytoscapejs

System requirements: Python (>=3.5.2) and the following python modules: isatools, os, ftplib, glob, logging, pandas, tempfile, shutil, re, nmrglue.

See at CRAN