An Operator-Independent Approach to Mass Spectral Peak Identification and Integration

Abstract

A mathematical algorithm is presented that locates and calculates the area beneath peaks from real data using only reproducible mathematical operations and no user-selected parameters. It makes no assumptions about peak shape and requires no smoothing or preprocessing of the data. In fact, it is shown that for matrix-assisted laser desorption time-of-flight mass spectra noise exists at all frequency ranges making the smoothing of data without distortion of peak areas impossible. The algorithm is based on a time-series segmentation routine that reduces the data set to groups of three strategic points where each group defines the beginning, center, and ending of each peak located. The peak areas are found from the strategic points using a commonplace polygonal area calculation routine. Peaks with statistically insignificant height or area are then discarded. The performance of the algorithm is demonstrated on a polystyrene mass spectrum with varying degrees of noise added either mathematically or experimentally. An on-line implementation of the method, termed MassSpectator, for public use can be found at www.nist.gov/maldi.