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Improvments and evaluation of data processing in LC-MS metabolomics: for application in in vitro systems pharmacology
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Biology Education Centre.
2017 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The resistance of established medicines is rapidly increasing while the rate of

discovery of new drugs and treatments have not increases during the last decades

(Spiro et al. 2008). Systems pharmacology can be used to find new combinations or

concentrations of established drugs to find new treatments faster (Borisy et al. 2003).

A recent study aimed to use high resolution Liquid chromatography–mass

spectrometry (LC-MS) for in vitro systems pharmacology, but encountered problems

with unwanted variability and batch effects(Herman et al. 2017). This thesis builds on

this work by improving the pipeline and comparing alternative methods and evaluating

used methods. The evaluation of methods indicated that the data quality was often

not improved substantially by complex methods and pipelines. Instead simpler

methods such as binning for feature extraction performed best. In-fact many of the

preprocessing method commonly used proved to have negative or neglect-able effects

on resulting data quality. Finally the recently introduced Optimal Orthonormal System

for Discriminant Analysis (OOS-DA) for batch removal was found to be a good

alternative to the more complex Combat method.

Place, publisher, year, edition, pages
2017.
Series
UPTEC X ; 17 028
National Category
Analytical Chemistry Bioinformatics and Systems Biology Pharmacology and Toxicology
Identifiers
URN: urn:nbn:se:uu:diva-329971OAI: oai:DiVA.org:uu-329971DiVA, id: diva2:1143969
Educational program
Molecular Biotechnology Engineering Programme
Supervisors
Examiners
Available from: 2017-09-25 Created: 2017-09-24 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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