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Proceedings Paper

Detecting trace components in liquid chromatography/mass spectrometry data sets with two-dimensional wavelets
Author(s): Duane C. Compton; Robert R. Snapp
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Paper Abstract

TWiGS (two-dimensional wavelet transform with generalized cross validation and soft thresholding) is a novel algorithm for denoising liquid chromatography-mass spectrometry (LC-MS) data for use in "shot-gun" proteomics. Proteomics, the study of all proteins in an organism, is an emerging field that has already proven successful for drug and disease discovery in humans. There are a number of constraints that limit the effectiveness of liquid chromatography-mass spectrometry (LC-MS) for shot-gun proteomics, where the chemical signals are typically weak, and data sets are computationally large. Most algorithms suffer greatly from a researcher driven bias, making the results irreproducible and unusable by other laboratories. We thus introduce a new algorithm, TWiGS, that removes electrical (additive white) and chemical noise from LC-MS data sets. TWiGS is developed to be a true two-dimensional algorithm, which operates in the time-frequency domain, and minimizes the amount of researcher bias. It is based on the traditional discrete wavelet transform (DWT), which allows for fast and reproducible analysis. The separable two-dimensional DWT decomposition is paired with generalized cross validation and soft thresholding. The Haar, Coiflet-6, Daubechie-4 and the number of decomposition levels are determined based on observed experimental results. Using a synthetic LC-MS data model, TWiGS accurately retains key characteristics of the peaks in both the time and m/z domain, and can detect peaks from noise of the same intensity. TWiGS is applied to angiotensin I and II samples run on a LC-ESI-TOF-MS (liquid-chromatography-electrospray-ionization) to demonstrate its utility for the detection of low-lying peaks obscured by noise.

Paper Details

Date Published: 2 October 2007
PDF: 12 pages
Proc. SPIE 6763, Wavelet Applications in Industrial Processing V, 67630P (2 October 2007); doi: 10.1117/12.732910
Show Author Affiliations
Duane C. Compton, The Univ. of Vermont (United States)
Robert R. Snapp, The Univ. of Vermont (United States)

Published in SPIE Proceedings Vol. 6763:
Wavelet Applications in Industrial Processing V
Frédéric Truchetet; Olivier Laligant, Editor(s)

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