AlpsNMR: An R package for signal processing of fully untargeted NMR-based metabolomics

F. Madrid-Gambin, S. Oller-Moreno, L. Fernandez, L. Fernandez, S. Bartova, M.P. Giner, C. Joyce, F. Ferraro, I. Montoliu, S. Moco, S. Marco, S. Marco

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

© 2020 The Author(s). Published by Oxford University Press. All rights reserved.Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines.
Original languageEnglish
Pages (from-to)2943-2945
JournalBioinformatics
Volume36
Issue number9
DOIs
Publication statusPublished - 1 May 2020
Externally publishedYes

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