This article is part of the supplement: Genetic Analysis Workshop 16
Proceedings
Gene hunting of the Genetic Analysis Workshop 16 rheumatoid arthritis data using rough set theory
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* Corresponding author: Hongyu Zhao hongyu.zhao@yale.edu
1 Department of Psychiatry, Yale University, 300 George Street, Suite 503, New Haven, Connecticut 06511, USA
2 Department of Mathematics, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok, 10330, Thailand
3 Program in Computational Biology and Bioinformatics, Yale University, 100 Howe Street, New Haven, Connecticut 06511, USA
4 Biostatistics Resource, Keck Laboratory, Yale University, 300 George Street, Suite 503, New Haven, Connecticut 06511, USA
5 Department of Epidemiology and Public Health, Yale University, 300 George Street, Suite 503, New Haven, Connecticut 06511, USA
6 Department of Genetics, Yale University, 300 George Street, Suite 503, New Haven, Connecticut 06511, USA
BMC Proceedings 2009, 3(Suppl 7):S126 doi:
Published: 15 December 2009Abstract
We propose to use the rough set theory to identify genes affecting rheumatoid arthritis risk from the data collected by the North American Rheumatoid Arthritis Consortium. For each gene, we employ generalized dynamic reducts in the rough set theory to select a subset of single-nucleotide polymorphisms (SNPs) to represent the genetic information from this gene. We then group the study subjects into different clusters based on their genotype similarity at the selected markers. Statistical association between disease status and cluster membership is then studied to identify genes associated with rheumatoid arthritis. Based on our proposed approach, we are able to identify a number of statistically significant genes associated with rheumatoid arthritis. Aside from genes on chromosome 6, our identified genes include known disease-associated genes such as PTPN22 and TRAF1. In addition, our list contains other biologically plausible genes, such as ADAM15 and AGPAT2. Our findings suggest that ADAM15 and AGPAT2 may contribute to a genetic predisposition through abnormal angiogenesis and adipose tissue.