Dynamic adaptive binning: an improved quantification technique for NMR spectroscopic data
Dynamic adaptive binning: an improved quantification technique for NMR spectroscopic data
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DOI：
10.1007/s11306-010-0242-7
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发表时间：
2011-06-01
期刊：
影响因子：
3.6
通讯作者：
Raymer, Michael L.
中科院分区：
文献类型：
--
作者：
Anderson, Paul E.;Mahle, Deirdre A.;Raymer, Michael L.
代谢组学研究的核磁共振（NMR）实验结果的解释需要密集的信号处理和多变量数据分析技术。该过程的关键步骤是光谱特征的量化，通常通过将NMR光谱划分为数百个积分区域或箱来完成。bining试图最小化由样品pH值、离子强度和成分引起的峰位置变化的影响，同时降低多元统计分析的维数。本文提出了一种改进的新型光谱量化技术——动态自适应分束。使用这种技术，通过使用动态规划策略优化目标函数来确定bin边界。目标函数根据每个桶的峰值数量来度量桶配置的质量。与传统的均匀分束和其他自适应分束技术相比，该技术有了显著的改进。这种改进是通过综合验证集来量化的，通过分析算法的能力来创建不包含多个峰值的箱，并最大化从峰值到箱边界的距离。验证集是通过表征实验核磁共振波谱数据中的显著分布而开发的。此外，动态自适应分形应用于基于H-1核磁共振的大鼠尿液代谢物监测实验，以经验证明改进的光谱定量。
The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. A key step in this process is the quantification of spectral features, which is commonly accomplished by dividing an NMR spectrum into several hundred integral regions or bins. Binning attempts to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition, while reducing the dimensionality for multivariate statistical analyses. Herein we develop an improved novel spectral quantification technique, dynamic adaptive binning. With this technique, bin boundaries are determined by optimizing an objective function using a dynamic programming strategy. The objective function measures the quality of a bin configuration based on the number of peaks per bin. This technique shows a significant improvement over both traditional uniform binning and other adaptive binning techniques. This improvement is quantified via synthetic validation sets by analyzing an algorithm's ability to create bins that do not contain more than a single peak and that maximize the distance from peak to bin boundary. The validation sets are developed by characterizing the salient distributions in experimental NMR spectroscopic data. Further, dynamic adaptive binning is applied to a H-1 NMR-based experiment to monitor rat urinary metabolites to empirically demonstrate improved spectral quantification.