Enhance the Quality of Fourier Transform Mass Spectrometry Data Based on the Filter Diagonalization Method

Fourier transform mass spectrometry (FTMS) is capable of achieving very high resolution, which is widely used in molecular biological research. Data processing method, especially at the signal level, is crucial for improving the quality of the data. Compared to fast Fourier transform method (FFT), filter diagonalization method (FDM) can improve the resolution of the mass spectra and reduce the measured signal intensity error. In this work, the performance of FDM was investigated using the simulation data and experimental mass spectrometry data. Comparing to FFT, FDM was improved the resolution of the mass spectra by a factor of one order and reduced the measured signal error effectively in experimental mass spectrometry data. Meanwhile, this work also investigated the parameter optimization problem that could be a reference for the application of FDM.