Abstract
The Human Genome Project and its spin-offs are making it increasingly feasible to determine the genetic basis of complex traits using genome-wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome-wide family-based association studies, using single SNPs or haplotypes, can identify associations that achieve genome-wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease-susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease-susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype-tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome-wide significance, as population-based designs do.
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Acknowledgements
We thank the families with CAMP for their participation in the CAMP Genetics Ancillary Study, supported by the US National Heart, Lung and Blood Institute; the CAMP investigators and research team, supported by the US National Heart, Lung and Blood Institute, for collection of CAMP Genetic Ancillary Study data; N.A. Beattie and J.T. Follweiler for editorial help; and D. Cutler for comments and suggestions. Additional support for this research came from the US National Heart Lung and Blood Institute. K.V.S. was supported by a grant from the US National Institutes of Health. All work undertaken in the CAMP Genetics Ancillary Study was done at the Channing Laboratory at the Brigham and Women's Hospital under appropriate CAMP policies and human subject protections. M.B.M. was supported by the National Research Service Award, Training Program in Psychiatric Epidemiology and Biostatistics.
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Supplementary Fig. 1
Estimated lower bounds for PBAT's screening techniques accounting for genomic control. (PDF 154 kb)
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Van Steen, K., McQueen, M., Herbert, A. et al. Genomic screening and replication using the same data set in family-based association testing. Nat Genet 37, 683–691 (2005). https://doi.org/10.1038/ng1582
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DOI: https://doi.org/10.1038/ng1582
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