{"title":"MetaboLabPy-An Open-Source Software Package for Metabolomics NMR Data Processing and Metabolic Tracer Data Analysis.","authors":"Christian Ludwig","doi":"10.3390/metabo15010048","DOIUrl":null,"url":null,"abstract":"<p><p><b>Introduction:</b> NMR spectroscopy is a powerful technique for studying metabolism, either in metabolomics settings or through tracing with stable isotope-enriched metabolic precursors. MetaboLabPy (version 0.9.66) is a free and open-source software package used to process 1D- and 2D-NMR spectra. The software implements a complete workflow for NMR data pre-processing to prepare a series of 1D-NMR spectra for multi-variate statistical data analysis. This includes a choice of algorithms for automated phase correction, segmental alignment, spectral scaling, variance stabilisation, export to various software platforms, and analysis of metabolic tracing data. The software has an integrated help system with tutorials that demonstrate standard workflows and explain the capabilities of MetaboLabPy. <b>Materials and Methods:</b> The software is implemented in Python and uses numerous Python toolboxes, such as numpy, scipy, pandas, etc. The software is implemented in three different packages: metabolabpy, qtmetabolabpy, and metabolabpytools. The metabolabpy package contains classes to handle NMR data and all the numerical routines necessary to process and pre-process 1D NMR data and perform multiplet analysis on 2D-<sup>1</sup>H, <sup>13</sup>C HSQC NMR data. The qtmetabolabpy package contains routines related to the graphical user interface. <b>Results:</b> PySide6 is used to produce a modern and user-friendly graphical user interface. The metabolabpytools package contains routines which are not specific to just handling NMR data, for example, routines to derive isotopomer distributions from the combination of NMR multiplet and GC-MS data. A deep-learning approach for the latter is currently under development. MetaboLabPy is available via the Python Package Index or via GitHub.</p>","PeriodicalId":18496,"journal":{"name":"Metabolites","volume":"15 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11767891/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolites","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3390/metabo15010048","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: NMR spectroscopy is a powerful technique for studying metabolism, either in metabolomics settings or through tracing with stable isotope-enriched metabolic precursors. MetaboLabPy (version 0.9.66) is a free and open-source software package used to process 1D- and 2D-NMR spectra. The software implements a complete workflow for NMR data pre-processing to prepare a series of 1D-NMR spectra for multi-variate statistical data analysis. This includes a choice of algorithms for automated phase correction, segmental alignment, spectral scaling, variance stabilisation, export to various software platforms, and analysis of metabolic tracing data. The software has an integrated help system with tutorials that demonstrate standard workflows and explain the capabilities of MetaboLabPy. Materials and Methods: The software is implemented in Python and uses numerous Python toolboxes, such as numpy, scipy, pandas, etc. The software is implemented in three different packages: metabolabpy, qtmetabolabpy, and metabolabpytools. The metabolabpy package contains classes to handle NMR data and all the numerical routines necessary to process and pre-process 1D NMR data and perform multiplet analysis on 2D-1H, 13C HSQC NMR data. The qtmetabolabpy package contains routines related to the graphical user interface. Results: PySide6 is used to produce a modern and user-friendly graphical user interface. The metabolabpytools package contains routines which are not specific to just handling NMR data, for example, routines to derive isotopomer distributions from the combination of NMR multiplet and GC-MS data. A deep-learning approach for the latter is currently under development. MetaboLabPy is available via the Python Package Index or via GitHub.
MetabolitesBiochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
5.70
自引率
7.30%
发文量
1070
审稿时长
17.17 days
期刊介绍:
Metabolites (ISSN 2218-1989) is an international, peer-reviewed open access journal of metabolism and metabolomics. Metabolites publishes original research articles and review articles in all molecular aspects of metabolism relevant to the fields of metabolomics, metabolic biochemistry, computational and systems biology, biotechnology and medicine, with a particular focus on the biological roles of metabolites and small molecule biomarkers. Metabolites encourages scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on article length. Sufficient experimental details must be provided to enable the results to be accurately reproduced. Electronic material representing additional figures, materials and methods explanation, or supporting results and evidence can be submitted with the main manuscript as supplementary material.