Abstract
In this thesis we present an overview of bioinformatics-based approaches for genomic association mapping, with emphasis on human quantitative traits and their contribution to complex diseases. We aim to provide a comprehensive walk-through of the classic steps of genomic association mapping illustrating the application and development of bioinformatics tools along the way. We start with a classic heritability study, continue with providing novel tools for genome-wide association studies (GWASs) of complex traits, and end with an integrated post-GWAS pipeline for translating GWAS findings of any human trait or disease to biological knowledge. Using this A-to-Z approach, we emphasize the importance of following the consecutive steps of genomic association mapping. To show how bioinformatics tools can facilitate and support analysis of high-throughput biological data, in Chapters 2, 3, 5, 6, and 7 we applied a number of already available tools, whereas in Chapters 3, 4, and 7 we developed novel bioinformatics tools supporting appropriate analysis of “big data” for genomic association mapping. Our in-house developed and extensively documented bioinformatics tools are freely available to the scientific community for further use. Furthermore, and as a running example of genomic association mapping of a typical human complex trait, we strictly adhered to serum levels of C-reactive protein (CRP). Using appropriate bioinformatics-based tools, either already available or our in-house developed ones, we succeeded to gain in knowledge of biological mechanisms controlling serum levels of CRP as well as its (causal) contribution to the pathophysiology of human diseases.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 23-Sept-2015 |
Place of Publication | [Groningen] |
Publisher | |
Print ISBNs | 978-90-367-8202-9 |
Electronic ISBNs | 978-90-367-8201-2 |
Publication status | Published - 2015 |