Peak alignment of NMR signals by means of a genetic algorithm Original Research Article

Nuclear magnetic resonance (NMR) analysis of complex samples, such as biofluid samples is accompanied by variations in peak position and peak shape not directly related to the sample. This is due to variations in the background matrix of the sample and to instrumental instabilities. These variations complicate and limit the interpretation and analysis of NMR data by multivariate methods. Alignment of the NMR signals may circumvent these limitations and is an important preprocessing step prior to multivariate analysis. Previous aligning methods reduce the spectral resolution, are very computer-intensive for this kind of data (65k data points in one spectrum), or rely on peak detection. The method presented in this work requires neither data reduction nor preprocessing, e.g. peak detection. The alignment is achieved by taking each segment of the spectrum individually, shifting it sidewise, and linearly interpolating it to stretch or shrink until the best correlation with a corresponding reference spectrum segment is obtained. The segments are automatically picked out with a routine, which avoids cutting in a peak, and the optimization process is accomplished by means of a genetic algorithm (GA). The peak alignment routine is applied to NMR metabonomic data.