A Bayesian Model Averaging Approach to the Quantification of Overlapping Peptides in an MALDI-TOF Mass Spectrum

Qi, Zhu; Kasim, Adetayo; Dirk, Valkenborg; Tomasz, Burzykowski

doi:10.1155/2011/928391

A Bayesian Model Averaging Approach to the Quantification of Overlapping Peptides in an MALDI-TOF Mass Spectrum

Qi, Zhu; Kasim, Adetayo; Dirk, Valkenborg; Tomasz, Burzykowski

Authors

Zhu Qi

Adetayo Kasim

Valkenborg Dirk

Burzykowski Tomasz

Abstract

In a high-resolution MALDI-TOF mass spectrum, a peptide produces multiple peaks, corresponding to the isotopic variants of the molecules. An overlap occurs when two peptides appear in the vicinity of the mass coordinate, resulting in the difficulty of quantifying the relative abundance and the exact masses of these peptides. To address the problem, two factors need to be considered: (1) the variability pertaining to the abundances of the isotopic variants (2) extra information content needed to supplement the information contained in data. We propose a Bayesian model for the incorporation of prior information. Such information exists, for example, for the distribution of the masses of peptides and the abundances of the isotopic variants. The model we develop allows for the correct estimation of the parameters of interest. The validity of the modeling approach is verified by a real-life case study from a controlled mass spectrometry experiment and by a simulation study.

Citation

Qi, Z., Kasim, A., Dirk, V., & Tomasz, B. (2011). A Bayesian Model Averaging Approach to the Quantification of Overlapping Peptides in an MALDI-TOF Mass Spectrum. International Journal of Proteomics, 2011, Article 928391. https://doi.org/10.1155/2011/928391

Journal Article Type	Article
Publication Date	Jan 1, 2011
Deposit Date	Nov 23, 2011
Publicly Available Date	Jun 6, 2012
Journal	International Journal of Proteomics
Print ISSN	2090-2166
Electronic ISSN	2090-2174
Publisher	Hindawi
Peer Reviewed	Peer Reviewed
Volume	2011
Article Number	928391
DOI	https://doi.org/10.1155/2011/928391

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Copyright Statement
Copyright © 2011 Qi Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.