Estimating coverage and power for genetic association studies using near-complete variation data
Tushar R Bhangale1, Mark J Rieder, Deborah A Nickerson
1Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA.
Abstract:
Although studies suggest that SNPs derived from HapMap provide promising coverage and power for association studies, the lack of alternative variation datasets limits independent analysis. Using near-complete variation data for 76 genes resequenced in HapMap samples, we find that coverage of common variation by commercial genotyping arrays is substantially lower compared to the HapMap-based estimates. We quantify the power offered by these arrays for a range of disease models.
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