Bioinformatics approaches to associate single nucleotide polymorphisms with human diseases according to their pathway related context

Official URL: http://192.168.1.20/record=b1478192 (Table of Contents)

Genome-wide association studies (GWASs) with millions of single nucleotide polymorphisms (SNPs) are popular strategies to reveal the genetic basis of human complex diseases. Despite many successes of GWASs, it is well recognized that new analytical approaches have to be integrated to achieve their full potential. In this thesis, starting with a list of SNPs, found to be associated with disease in GWAS, we have developed a novel methodology to devise functionally important pathways through the identification of SNP targeted genes within these pathways. Our methodology is based on functionalization of important SNPs to identify effected genes and disease related pathways. We have tested our methodology on rheumatoid arthritis, epilepsy, intracranial aneurysm and Behçet’s disease datasets. With the whole-genome sequencing on the horizon, we show that the full potential of GWASs can be achieved by integrating prior knowledge from functional properties of a SNP and pathwayoriented analysis via protein-protein interaction networks.