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A wavelet-based Monte Carlo simulation of Odds Ratio Contour in genome-wide association study

Genome-wide case-control association study of complex disease requires effective and robust measurement of statistical difference of genetic markers, particularly single nucleotide polymorphisms (SNP). This paper presents a development of Odds Ratio Contour Analysis (ORCA) which is a method for identifying disease susceptible SNP from the odds ratio signal in genome-wide association study using a wavelet-based Monte Carlo simulation. Wavelet approximation uncovers the trends in odds ratio signal while Monte Carlo simulation robustly and effectively selects candidate SNPs. The simulation test shows that ORCA can help not only reducing the rate to discover false positive SNPs but also enhancing the chance to detect SNPs that are biologically related the disease under study.