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Investigation and interpretation of large mass spectrometry imaging datasets

Race, Alan M. (2016)
Ph.D. thesis, University of Birmingham.

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Abstract

Mass spectrometry imaging (MSI) enables two- and three-dimensional overviews of hundreds of unlabelled molecular species including drugs, metabolites, lipids and proteins in complex samples such as intact tissue. In this research, a new extensible software platform is presented, suitable for spectral preprocessing, multivariate analysis and visualisation of large MSI datasets from all major MSI vendors.
Principal component analysis (PCA) has been widely used in the unsupervised processing of MSI data. Standard implementations of PCA require the entire dataset to be stored in memory, necessitating a compromise between the number of pixels and the number of peaks to include. In this research a new method which has no limitation on the number of pixels is developed. Hierarchical composition of data has been shown as an efficient method of capturing the information present within images in other fields. An adaptation of these ideas to MSI data is described. The way in which imaging data are presented can have a significant impact on the perceived structure, especially when using false colour to display images. The research presented in this thesis has resulted in new recommendations for presentation of MS images. Finally, the software and algorithms presented were used to analyse MSI data from a traumatic brain injury model. Manual exploration and use of multivariate analysis methods such as PCA did not reveal any differences between the injured hemisphere of the brain and the control hemisphere, however the hierarchical composition algorithms identified multiple ion images which appear elevated in the injured hemisphere.

Type of Work:Ph.D. thesis.
Supervisor(s):Bunch, Josephine and Styles, Iain B
School/Faculty:Colleges (2008 onwards) > College of Engineering & Physical Sciences
Department:School of Chemistry
Additional Information:

Publications arising from thesis:

Alan M Race, Iain B Styles and Josephine Bunch. Inclusive sharing of mass spectrometry imaging data requires a converter for all. Journal of Proteomics, 75 (16), 5111-5112, 2012.
http://dx.doi.org/10.1016/j.jprot.2012.05.035

Alan M Race, Rory T Steven, Andrew D Palmer, Iain B Styles and Josephine Bunch. Memory efficient principal component analysis for the dimensionality reduction of large mass spectrometry imaging data sets. Analytical
Chemistry, 85 (15), 7146-7153, 2013.
http://dx.doi.org/10.1021/ac302528v

Alan M Race and Josephine Bunch. Optimisation of colour schemes to accurately display mass spectrometry imaging data based on human colour perception. Analytical and Bioanalytical Chemistry, 407 (8), 2047-2054, 2015.
http://dx.doi.org/10.1021/ac302528v

Subjects:QD Chemistry
Institution:University of Birmingham
ID Code:6718
This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder.
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