Abstract
We develop an analysis method for genome-wide case-control association studies that is based on a polygenic threshold model. For each SNP in a given study, the risk allele is determined as that allele leading to an odds ratio greater than 1. For a given set of SNPs, the number of risk alleles in cases minus that in controls is evaluated and a p-value is obtained for this difference. For SNPs selected in a given order based on some single-locus test statistic, successive sums of these differences over the best 2, 3, etc. SNPs (located anywhere in the genome) and associated p-values are obtained. The smallest such p-value among L SNPs tested is our genome-wide test statistic, for which an empirical significance level is obtained by permutation analysis. Our approach is applied to several disease datasets and shown to furnish significant results even for traits with little evidence of single-locus effects.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
