Association Analysis for Big Data Related to Rheumatoid Arthritis

Genetics of autoimmune diseases represent a growing domain with surpassing biomarker results with rapid progress. Rheumatoid arthritis (RA) is an autoimmune disease which has a significant socio-economic impact. The exact cause of RA is unknown, but it is thought to have both a genetic and an environmental bases. This thesis is concerned with the methods of identifying the genetic biomarkers of RA. Most of the researchers in the field of identifying RA biomarkers use single nucleotide polymorphism (SNP) approaches to express the significance of their results. Although, haplotype block methods are expected to play a complementary role in the future of that field. The used datasets belong to Egyptian population and North American population. Selection of the method used for the association discovery has a large impact on the resulted biomarkers. Finally, individual SNP approach and haplotype block methods should be applied side by side to discover valuable RA biomarkers.