Omic data analysis for method development and unique insights into cancer, infectious and chronic diseases

Unbiased and high throughput measurements of different layers of molecular biology, collectively known as "omics", allow researchers to gather unprecedented amounts of data on their biological system of interest. In this thesis, I focus on evaluating a range of methodologies to improve our ability to analyse such datasets in order to extract useful knowledge. I make use of public datasets to develop a method for identification of genomic variants associated with disease. Furthermore, I use novel analytic approaches across three studies concerning cancer, infectious and chronic disease, and demonstrate the unique insights that can be gained from omic data