While SNP-based marker sets and population-level DNA repositories are approaching sufficient size for whole-genome association studies, individual genotyping remains very costly. Pooled DNA tests are a less costly alternative, but uncertainty about loss of power due to allele frequency measurement error and population stratification hinder their use. Here we describe how to optimize pooled tests as an explicit function of measurement error, and we present family-based tests that eliminate stratification effects. We show that identification of functional genetic variants and linked markers may be feasible with current-day instruments.
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