THESIS
2014
x, 47 pages : illustrations (some color) ; 30 cm
Abstract
Liquid chromatography-mass spectrometry (LC-MS) is a widely used technique in the
field of proteomics for biomarker discovery and protein identification. An LC-MS
experiment determines the components of a chemical mixture and the result can be
represented as a two-dimensional image, where the LC retention time and the mass-to-charge
ratio are the abscissa and the ordinate respectively, while the signal intensities
indicate the abundance of detected chemicals. In many LC-MS based applications,
it is often required to compare samples from different experiments, and thus multiple
LC-MS images. Since there is always a non-linear LC retention time shifting across
LC-MS images, alignment between images is needed prior to performing any analysis.
In this thesis, we introduce a multi-...[
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Liquid chromatography-mass spectrometry (LC-MS) is a widely used technique in the
field of proteomics for biomarker discovery and protein identification. An LC-MS
experiment determines the components of a chemical mixture and the result can be
represented as a two-dimensional image, where the LC retention time and the mass-to-charge
ratio are the abscissa and the ordinate respectively, while the signal intensities
indicate the abundance of detected chemicals. In many LC-MS based applications,
it is often required to compare samples from different experiments, and thus multiple
LC-MS images. Since there is always a non-linear LC retention time shifting across
LC-MS images, alignment between images is needed prior to performing any analysis.
In this thesis, we introduce a multi-resolution LC-MS image alignment scheme
for synchronizing LC-MS images. The multi-resolution scheme employs one of two
popular time alignment algorithms, Dynamic Time Warping (DTW) or Correlation
Optimized Warping (COW), as the optimization algorithm, while Kullback-Leibler
Distance (KLD) is used as the local similarity measure. We have validated the proposed
scheme using two real-world data sets, which include both high mass accuracy
and low mass accuracy LC-MS images. In addition, we have also compared the results
with an existing alignment algorithm, the Dynamic Time Warping-Component Detection Algorithm (DTW-CODA). The experiments show that the proposed scheme
outperforms DTW-CODA, and is a promising approach for aligning both high mass
accuracy and low mass accuracy LC-MS images.
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