DISSERTATION Model Selection Techniques for Locating Multiple Quantitative Trait Loci in Experimental Crosses

Preface Statistical developments have in many cases been driven by applications in science. While genetics was always an important area that encouraged statistical research, recent technological advances in this discipline pose ever new and challenging problems to statisticians. This thesis covers the application of model selection to QTL mapping, i.e. locating genes that influence a quantitative character of an organism. The existing statistical framework was taken as a starting point that has been adapted and modified to be applicable to QTL mapping. The requirements included good computational performance, robustness, consideration of prior information and treatment of incomplete data. The key results from my thesis are covered in three joint publications: A. (2007). Locating multiple interacting quantitative trait loci using rank-based model selection. Accepted in: Genetics 1 Acknowledgements I am grateful to my supervisor Andreas Futschik for introducing me to this fascinating area of research as well as for his constant guidance and stimulating advice. Andreas' statistical expertise and intuition as well as his focus on results had a great impact on the outcome of this thesis. Further, I want to thank Malgorzata Bog-dan for her enthusiastic participation in our joint work and for sharing her broad knowledge on the topic.