University of Groningen
Development of bioinformatic tools and application of novel statistical methods in
genome-wide analysis
van der Most, Peter Johannes
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Publication date: 2017
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van der Most, P. J. (2017). Development of bioinformatic tools and application of novel statistical methods in genome-wide analysis. University of Groningen.
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1. Genome-wide association studies have generally used brute force instead of sophisticated statistical methods (this thesis).
2. Survival analysis methods can be applied in genome-wide analyses, allowing for better modelling of censored data (chapters 4 and 8, this thesis).
3. Good quality control after a genome- or epigenome-wide association study is essential to catch errors that could bias the results (chapters 2 and 3, this thesis). 4. The common SNP heritability is a more useful reference of how much heritability a
genome-wide association study can detect than heritability derived from family- or twin studies (chapter 5, this thesis).
5. Low-resolution genotyping arrays limit the value of larger genome reference panels for imputation (this thesis).
6. In the short term the most cost-effective solution to the problem of missing heritability remains the use of a more detailed reference genome for imputation combined with a larger sample size for analysis (this thesis).
7. Genetic risks scores are not yet accurate/comprehensive enough to be used for personalized genetic risk prediction of complex traits (chapter 5, this thesis). 8. A major challenge for genetic epidemiology is extracting meaning out of the
enormous amount of data that is already collected (this thesis).
9. The missing heritability problem precludes the application of genetic epidemiological fi ndings in clinical settings (this thesis).
10. A task will always take more time than the plan foresaw. This occurs even if the plan took into account the aforementioned phenomenon (Murphy’s law of planning). 11. Plans are worthless, but planning is everything (Dwight D. Eisenhower).
