A16: Kernel Methods for the Association Analysis of Genes and Networks including Environmental Components of Complex Diseases
PhD student: Viola Tozzi
Supervisor: Prof. Dr. Heike Bickeböller
Genome-wide association studies (GWAS) have identified thousands of single nucleotide polymorphisms (SNPs) associated with complex diseases. Genome chips differ widely in size and coverage, not only between chips but also regarding the regions or networks of regions considered. We might look across the whole genome, pathways or genes, across networks and interactions. The goal of this thesis is to integrate gene- and pathway level information with information on non-genetic factors such as smoking in lung cancer or treatment when considering treatment response. The application for the statistical methods development in this project is lung cancer; others are hematopoietic stem cell transplantation or psychosis.