Please use this identifier to cite or link to this item:
https://hdl.handle.net/2445/180153| Title: | Alpsnmr: an r package for signal processing of fully untargeted nmr-based metabolomics |
| Author: | 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 |
| Keywords: | Metabòlits Ressonància magnètica nuclear Programari Metabolites Nuclear magnetic resonance Computer software |
| Issue Date: | 13-Jan-2020 |
| Publisher: | Oxford University Press |
| Abstract: | 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. |
| Note: | Versió postprint del document publicat a: https://doi.org/10.1093/bioinformatics/btaa022 |
| It is part of: | Bioinformatics, 2020, vol. 36, num. 9, p. 2943-2945 |
| URI: | https://hdl.handle.net/2445/180153 |
| Related resource: | https://doi.org/10.1093/bioinformatics/btaa022 |
| ISSN: | 1367-4803 |
| Appears in Collections: | Articles publicats en revistes (Enginyeria Electrònica i Biomèdica) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 699828.pdf | 1.02 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
