Abstract
For each variant in a genome-wide association study, the risk allele is the one with an odds ratio greater than 1. For a given set of variants, the number of risk alleles in cases minus that in controls is evaluated and a p-value is obtained for this difference. Successive sums of these differences over the best 2, 3, etc. variants and associated p-values are obtained. The smallest such p-value is our genome-wide test statistic, for which an empirical significance level is obtained by permutation analysis. Applied to disease datasets, our approach furnishes significant results even with little single-locus effects.
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