PepsNMR for 1H NMR metabolomic data pre-processing
PepsNMR for 1H NMR metabolomic data pre-processing
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DOI：
10.1016/j.aca.2018.02.067
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发表时间：
2018-08-17
影响因子：
6.2
通讯作者：
Govaerts, Bernadette
中科院分区：
文献类型：
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作者：
Martin, Manon;Legat, Benoit;Govaerts, Bernadette
在生物样品的分析中，单独控制实验设计和数据采集程序不能确保具有最大信息恢复的良好条件的H-1 NMR谱用于数据分析。第三个主要因素影响结果的准确性和稳健性：数据预处理/预处理通常没有得到足够的关注，特别是在代谢组学研究中。通常的方法是使用分析仪器制造商提供的专有软件来执行整个预处理策略。这一广泛的做法有若干优点，例如具有图形设施的用户友好界面，但也有不可忽视的缺点：缺乏方法信息和自动化，依赖于人的主观选择，只有标准的处理可能性，缺乏评价预处理质量的客观质量标准。本文介绍了PepsNMR，以满足这些需求，R包专用于整个处理链之前，多元数据分析，包括，除其他工具，溶剂信号抑制，内部校准，相位，基线和错位校正，桶和归一化。方法方面进行了讨论，并与两个代谢组学案例研究的金标准程序包。PepsNMR对这些数据的使用显示了基于客观和定量质量标准的更好的信息恢复和预测能力。该软件包的其他关键资产是工作流程处理速度、可重复性、报告和灵活性、图形输出和记录例程。(c)2018 Elsevier B. V.版权所有。
In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned H-1 NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines. (c) 2018 Elsevier B.V. All rights reserved.