Peak alignment using reduced set mapping

This paper presents an algorithm and method for peak alignment or spectral synchronization of first-order data with pronounced differences between baseline and signals of interest, e.g. data typically acquired by NMR, MS, GC, LC and CE. The method preserves the shapes of peaks, merely altering their positions on the x-axis of the data set. The method involves coarse discrimination between baseline and peaks, generation of a sparse vector or a list representing peak maximum positions, and analysis of the vector or list for shift parameters using breadth first search or dynamic programming. The method can align peaks up to the spectral resolution of the acquiring instrument without restrictions on the number of peaks that are to be shifted. Furthermore, the speed and moderate number of meta-parameters of the algorithm make the method suitable for on-line implementation. Real H-1 NMR and GC data are used to illustrate the method's performance. Copyright (C) 2004 John Wiley Sons, Ltd.