Ludwig Christian
Department of Metabolism and Systems Sciences, School of Medical Sciences, College of Medicine and Health, University of Birmingham, Birmingham B15 2TT, UK.
Metabolites. 2025 Jan 14;15(1):48. doi: 10.3390/metabo15010048.
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. 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-H, C HSQC NMR data. The qtmetabolabpy package contains routines related to the graphical user interface. 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.
核磁共振波谱法是一种用于研究代谢的强大技术，可用于代谢组学研究，也可通过追踪稳定同位素富集的代谢前体来进行研究。MetaboLabPy（版本0.9.66）是一个免费的开源软件包，用于处理一维和二维核磁共振波谱。该软件实现了一个完整的核磁共振数据预处理工作流程，以准备一系列用于多变量统计数据分析的一维核磁共振波谱。这包括选择用于自动相位校正、分段对齐、光谱缩放、方差稳定化、导出到各种软件平台以及分析代谢追踪数据的算法。该软件有一个集成的帮助系统，其中的教程展示了标准工作流程并解释了MetaboLabPy的功能。该软件用Python实现，并使用了许多Python工具箱，如numpy、scipy、pandas等。该软件以三个不同的包实现：metabolabpy、qtmetabolabpy和metabolabpytools。metabolabpy包包含处理核磁共振数据的类以及处理和预处理一维核磁共振数据并对二维氢碳异核单量子相干核磁共振数据进行多重峰分析所需的所有数值例程。qtmetabolabpy包包含与图形用户界面相关的例程。PySide6用于生成一个现代且用户友好的图形用户界面。metabolabpytools包包含并非仅特定于处理核磁共振数据的例程，例如，从核磁共振多重峰和气相色谱 - 质谱数据的组合中推导同位素异构体分布的例程。目前正在开发针对后者的深度学习方法。可通过Python包索引或GitHub获取MetaboLabPy。
