Integrative methods for the analysis of genome wide association studies
Abstract/Contents
- Abstract
- Genome Wide Association Studies (GWAS) have identified over 4,500 common variants in the human genome that are statistically associated with diseases and other phenotypical traits. Most identified associations, however, only have a small effect on disease risk, and their relevance in a clinical setting remains the subject of extensive debate. In this thesis I present three integrative analysis directions that extend on GWAS by developing new methods, by using genotyping data to ask new questions, and by integrating additional types of data to generate functional hypotheses about the biological processes underlying associations. First, I introduce a new classifier-based methodology that identifies similarities in the genetic architecture of diseases. This method can successfully identify both known and novel relationships between common diseases. Second, I show how control individuals from a GWAS can be used to detect genetic differences between the pseudoautosomal regions of chromosomes X and Y in the general population. Finally, I present an approach that integrates experimental data generated by the ENCODE consortium in order to identify functional Single Nucleotide Polymorphisms (SNPs). These functional SNPs are associated with a phenotype, either directly or through linkage disequilibrium, and overlap a functional region of the genome such as a transcribed region or a transcription factor binding site. Up to 80% of all associations previously reported in a GWAS can be mapped to a functional SNP.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Schaub, Marc Andreas |
|---|---|
| Associated with | Stanford University, Computer Science Department |
| Primary advisor | Batzoglou, Serafim |
| Thesis advisor | Batzoglou, Serafim |
| Thesis advisor | Butte, Atul J |
| Thesis advisor | Dill, David L |
| Advisor | Butte, Atul J |
| Advisor | Dill, David L |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Marc A. Schaub. |
|---|---|
| Note | Submitted to the Department of Computer Science. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2012. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2012 by Marc Andreas Schaub
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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