Gaussian mixture decomposition in the analysis of MALDI‐TOF spectra

Abstract

The article presents a method of protein matrix-assisted laser desorption and ionization-time of flight (TOF) spectra analysis. The method performs peaks detection. Spectra are analysed with Gaussian mixture decomposition. The results obtained are used for peaks identification purposes. The concept of the method is that a single peak is represented by one Gaussian distribution. The expectation-maximization algorithm and maximum likelihood rule are used for spectra processing. The analysis can be done for a set of spectra with use of the mean spectrum, or it may be performed for a single spectrum at a time. The number of mixture-model components is estimated by the Bayesian information criterion. Before the main analysis, a few pre-processing steps need to be done. Spectra should be subjected to calibration, normalization, denoising, baseline correction, etc. The aim of the work is to identify peptides in the analysed sample on the basis of the parameters of the mixture model and to find differences between spectra in the analysed set.

Inactivation of the particulate methane monooxygenase (pMMO) in Methylococcus capsulatus (Bath) by acetylene

“…The Gaussian mixture decomposition of MALDI-TOF MS spectra is a widely used approach to dissect overlapping signals [21][22][23]. The fitting was first performed on the mass peak of the PmoC subunit derived from the untreated sample (control) in order to establish the criteria for the best fitting model, namely, the minimum number of Gaussians required to obtain optimal statistics.…”

Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry

“…Parameters of the signal y n , min max n n n ≤ ≤ , (6)-(7) corresponding either to a splitter-segment or to a segment are k k w sα = , k µ and k σ , k=1,2,…K. EM recursions assume the following form (similar to standard EM iterations for mixtures) [18,22,26] (…”

“…Applications of mixture modeling to proteomic MS spectra were researched in [18][19][20][21][22][23][24] by analyzing proteomic actual mass spectra, or their fragments, and by conducting experiments involving fitting mixture models to data. A computational model and some exemplary results were presented in [22]. In [19] Kempka and coauthors studied a model based on the biophysical mechanisms of forming peaks in the MALDI ToF MS spectrum, with two Gaussian components corresponding to two sets of ions formed during the peptide ionization stage.…”

“…A potentially useful approach to computational processing of proteomic MS spectra is modeling spectral signals by mixtures of component functions. Some results in this area were published in [18][19][20][21][22][23][24]. A natural choice for the component functions are Gaussian distribution functions.…”

Time-frequency analysis for cancer detection using proteomic MS-spectra

“…In order to achieve This work was supported in part by BIOTEC postdoc grant. high specificity and sensitivity, they often comprise different techniques for normalization, baseline removal, kernel smoothing, noise estimation, peak alignment, and eventually pattern recognition, e.g., [4][5][6][7]. This motivates a simpler algorithm which can reduce or shorten these steps while maintaining the detection/classification performance.…”