الفهرس 
Title : Association Analysis for Big Data Related to Rheumatoid Arthritis Based on Haplotype Block Partitioning and Single Nucleotide Polymorphisms
SummaryOnly 14 pages are availabe for public view
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Abstract
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 (185 individuals, 8 SNPs) and North American population (2,062 individuals, 545,080 SNPs). Our goal in this thesis differs according to the studied dataset. For the Egyptian dataset, the goal is the detection of the significant SNPs that are associated with RA disease. The individual SNP approaches that were used with the Egyptian population are multiplicative, co-dominant, dominant, and recessive approaches. The haplotype methods couldn{u2019}t be applied on the Egyptian dataset because of the small number of the studied SNPs. The associations between the eight SNPs and RA susceptibility and severity were detected using the four applied individual SNP approaches