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Alpsnmr: an r package for signal processing of fully untargeted nmr-based metabolomics
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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.
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MADRID GAMBÍN, Francisco javier, OLLER MORENO, Sergio, FERNÁNDEZ ROMERO, Luis, BARTOVA, Simona, GINER, Maria pilar, JOYCE, Christopher, FERRARO, Francesco, MONTOLIU, Ivan, MOCO, Sofia, MARCO COLÁS, Santiago. Alpsnmr: an r package for signal processing of fully untargeted nmr-based metabolomics. _Bioinformatics_. 2020. Vol. 36, núm. 9, pàgs. 2943-2945. [consulta: 20 de gener de 2026]. ISSN: 1367-4803. [Disponible a: https://hdl.handle.net/2445/180153]