Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform

Abstract

Mass spectrometry is being used to find disease-related patterns in mixtures of proteins derived from biological fluids. Questions have been raised about the reproducibility and reliability of peak quantifications using this technology. We collected nipple aspirate fluid from breast cancer patients and healthy women, pooled them into a quality control sample, and produced 24 replicate SELDI spectra. We developed a novel algorithm to process the spectra, denoising with the undecimated discrete wavelet transform (UDWT), and evaluated it for consistency and reproducibility. UDWT efficiently decomposes spectra into noise and signal. The noise is consistent and uncorrelated. Baseline correction produces isolated peak clusters separated by flat regions. Our method reproducibly detects more peaks than the method implemented in Ciphergen software. After normalization and log transformation, the mean coefficient of variation of peak heights is 10.6%. Our method to process spectra provides improvements over existing methods. Denoising using the UDWT appears to be an important step toward obtaining results that are more accurate. It improves the reproducibility of quantifications and supplies tools for investigation of the variations in the technology more carefully. Further study will be required, because we do not have a gold standard providing an objective assessment of which peaks are present in the samples.

A strategy for the prior processing of high‐resolution mass spectral data obtained from high‐dimensional combined fractional diagonal chromatography

“…After applying the algorithm to the bovine cytochrome C and COFRADIC data sets, we could conclude that the removal of the normal error term ε in (1) by undecimated continuous wavelet transform [11] has only a minor effect on the intensity of the peptide peaks. The baseline correction is fast and yields results comparable to, e.g., LOWESS.…”

“…Nevertheless, during the low-level processing (light gray labels in Fig. 1), the additive noise is removed from the mass spectrum by using the undecimated discrete wavelet transform proposed by Baggerly et al [11] The baseline is removed to improve the reproducibility. To decrease the complexity of a mass spectrum, the data are reduced without loss of relevant information, i.e., the information about the isotopic distribution is retained.…”

Signal Processing Methods for Capillary Electrophoresis

“…Wavelet denoising strategies were also used (Ceballos et al 2008) on pattern recognition in CE. Similar wavelet based denoising strategies to those cited above have also been applied to liquid chromatography data (Barclay and Bonner 1997;Shao et al 2004), Raman spectroscopy (Hu et al 2007), mass spectrometry data (Barclay and Bonner 1997;Coombes et al 2005), as well as numerous other areas of research (Jagtiani et al 2008;Komsta 2009). The DWT is sufficient in many scenarios when removing high and low frequency noise from signals.…”

Workflow and Methods of High-Content Time-Lapse Analysis for Quantifying Intracellular Calcium Signals

“…In the extracted calcium signals, noisy signals will most likely be induced by the bias of segmentation, displacement correction, and intensity normalization. To suppress these noisy signals, the undecimated discrete wavelet transform (UDWT) (Coombes et al 2005) is employed. Figure 6 provides an example of extracted calcium signals.…”