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Application of Wavelet Transform to the MS-based Proteomics Data Preprocessing

Mass spectrometry (MS) has become one of the major detection technologies for high-throughput proteomics. The preprocessing of mass spectra is crucial for its subsequent analysis like biomarker discovery or protein identification. Wavelet transform is gradually becoming an important methodology in the MS data preprocessing. This paper reviews the application of wavelet transforms in quality control, smoothing and peak detection of MS data preprocessing. It also proposes an improved Discrete Wavelet Transform (DWT) smoothing algorithm, which utilizes the cross-level DWT coefficients information during smoothing. Most of the algorithms described in this paper are included or will be included in the Bioconductor MassSpecWavelet package.