An objective comparison of pre-processing methods for enhancement of liquid chromatography–mass spectrometry data

Four data pre-processing methods have been applied with different settings to data sets obtained from the analysis of a pharmaceutical drug and its degradation products by liquid chromatography–mass spectrometry (LC–MS). The methods compared were the frequently used component detection algorithm (CODA) and three kinds of digital filters—matched filtration (MF), Gaussian second derivative (GSD) and Savitzky–Golay. The aim was to evaluate the performance and robustness of these methods for extracted ion chromatogram (XIC), total ion chromatogram (TIC) and base peak chromatogram (BPC) in the presence of different types of noise. In accordance with theory, the best improvements in signal-to-noise ratio (S/N) of the XICs were obtained with MF under the ideal case with random white noise. However, when highly coloured noise was present, it was found that no improvements in XIC S/N could be obtained with any of the pre-processing methods studied. GSD and CODA did, however, improve the S/N for both TIC and BPC. GSD and CODA also significantly reduced the background in the spectral domain, thereby facilitating the interpretation of the mass spectra. Another advantage associated with CODA and to some extent also with GSD is their data reduction ability.