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TitleAn R package for the integrated analysis of metabolomics and spectral data
Author(s)Costa, Christopher
Maraschin, Marcelo
Rocha, Miguel
Nuclear Magnetic Resonance
Mass Spectrometry
Infrared spectroscopy
Statistical data analysis
Machine learning
Infrared and UV-visible spectroscopy
Issue dateJun-2016
JournalComputer Methods and Programs in Biomedicine
CitationCosta, Christopher; Maraschin, Marcelo; Rocha, Miguel, An R package for the integrated analysis of metabolomics and spectral data. Computer Methods and Programs in Biomedicine, 129, 117-124, 2016.
Abstract(s)Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as Nuclear Magnetic Resonance, Gas or Liquid Chromatography, Mass Spectrometry, Infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which 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, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines.
Publisher version
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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