Forshed Jenny, Torgrip Ralf J O, Aberg K Magnus, Karlberg Bo, Lindberg Johan, Jacobsson Sven P
Department of Analytical Chemistry, Stockholm University, SE-10691, Stockholm, Sweden.
J Pharm Biomed Anal. 2005 Aug 10;38(5):824-32. doi: 10.1016/j.jpba.2005.01.042. Epub 2005 Apr 2.
This paper compares the performance of two recently developed algorithms and methods for peak alignment of first-order NMR data of complex biological samples. The NMR spectra of such samples exhibit variations in peak position and peak shape due to variations in the sample matrix and to instrumental instabilities. The first method comprises an alignment of spectral segments with linear interpolation and shift correction to accommodate correspondence between a target and a test spectrum by a beam search or genetic algorithm. The second method is based on peak picking and needle vector representation of the NMR data with subsequent breadth-first search to establish shift corrections between the target and the test spectrum. The two proposed peak alignment methods and their respective merits are discussed for a real metabonomics application. Both alignment methods have been shown to enhance the interpretability of the resulting multivariate models, thereby increasing the prospect of detecting and following the onset of subtle biological changes reflected in the NMR data.
本文比较了最近开发的两种用于复杂生物样品一阶核磁共振（NMR）数据峰对齐的算法和方法。由于样品基质的变化和仪器的不稳定性，此类样品的NMR谱在峰位置和峰形状上会表现出差异。第一种方法包括通过线性插值和移位校正对光谱段进行对齐，以通过束搜索或遗传算法来适应目标光谱与测试光谱之间的对应关系。第二种方法基于NMR数据的峰检测和针向量表示，随后进行广度优先搜索以建立目标光谱与测试光谱之间的移位校正。针对实际的代谢组学应用，讨论了所提出的两种峰对齐方法及其各自的优点。两种对齐方法均已证明可增强所得多变量模型的可解释性，从而增加检测和追踪NMR数据中反映的细微生物变化起始情况的可能性。
