Windowed mass selection method: a new data processing algorithm for liquidchromatography-mass spectrometry data

A number of preprocessing methods are tested on liquid chromatography-mass spectrometry (LC-MS) peptide map data, to determine the best and most effic ient way to improve the signal to noise ratio in the data, especially at lo w analyte concentrations. Three methods are investigated, including an algo rithm named "sequential paired covariance" (SPC), which was recently report ed. An improvement to this algorithm is also reported here. This new, impro ved method, named the "windowed mass selection method" (WMSM), is shown to effectively eliminate random noise that occurs in the data. This method is shown to be particularly useful in improving signal to noise ratios in both chromatographic and mass spectra for data acquired in peptide mapping of r ecombinant DNA derived proteins. (C) 1999 Elsevier Science B.V. All rights reserved.