Genomic screening and replication using the same data set in family-based association testing |
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Authors: | Van Steen Kristel McQueen Matthew B Herbert Alan Raby Benjamin Lyon Helen Demeo Dawn L Murphy Amy Su Jessica Datta Soma Rosenow Carsten Christman Michael Silverman Edwin K Laird Nan M Weiss Scott T Lange Christoph |
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Institution: | Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. kvanstee@hsph.harvard.edu |
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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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