Peak quantification in surface‐enhanced laser desorption/ionization by using mixture models

Surface‐enhanced laser desorption/ionization (SELDI) time of flight (TOF) is a mass spectrometry technology for measuring the composition of a sampled protein mixture. A mass spectrum contains peaks corresponding to proteins in the sample. The peak areas are proportional to the measured concentrations of the corresponding proteins. Quantifying peak areas is difficult for existing methods because peak shapes are not constant across a spectrum and because peaks often overlap. We present a new method for quantifying peak areas. Our method decomposes a spectrum into peaks and a baseline using so‐called statistical finite mixture models. We illustrate our method in detail on 8 samples from culture media of adipose tissue and globally on 64 samples from serum to compare our method to the standard Ciphergen method. Both methods give similar estimates for singleton peaks, but not for overlapping peaks. The Ciphergen method overestimates the heights of such peaks while our method still gives appropriate estimates. Peak quantification is an important step in pre‐processing SELDI‐TOF data and improvements therein will pay off in the later biomarker discovery phase.

[1]  大房 健 基礎講座 電気泳動(Electrophoresis) , 2005 .

[2]  Geoffrey J. McLachlan,et al.  Mixture models : inference and applications to clustering , 1989 .

[3]  J. Whitin,et al.  Improving feature detection and analysis of surface‐enhanced laser desorption/ionization‐time of flight mass spectra , 2005, Proteomics.

[4]  D. Balding,et al.  Handbook of statistical genetics , 2004 .

[5]  S. Weinberger,et al.  Recent advancements in surface‐enhanced laser desorption/ionization‐time of flight‐mass spectrometry , 2000, Electrophoresis.

[6]  R. Koppmann,et al.  A new mathematical procedure to evaluate peaks in complex chromatograms. , 2005, Journal of chromatography. A.

[7]  D L Massart,et al.  Automatic program for peak detection and deconvolution of multi-overlapped chromatographic signals part I: peak detection. , 2005, Journal of chromatography. A.

[8]  C. Fischer Handbook of statistical genetics: , 2002, Human Genetics.

[9]  P. Scherer,et al.  Printed in U.S.A. Copyright © 2003 by The Endocrine Society doi: 10.1210/en.2003-0580 Minireview: The Adipocyte—At the Crossroads of Energy Homeostasis, Inflammation, and Atherosclerosis , 2022 .

[10]  Jeffrey S. Morris,et al.  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 , 2005, Proteomics.

[11]  R. Bischoff,et al.  Methodological advances in the discovery of protein and peptide disease markers. , 2004, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[12]  E. Fung,et al.  ProteinChip clinical proteomics: computational challenges and solutions. , 2002, BioTechniques.

[13]  E. Petricoin,et al.  SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer. , 2004, Current opinion in biotechnology.

[14]  X Yu,et al.  J.Chromatogr., B: Anal. Technol. Biomed. Life Sci. , 2004 .

[15]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .