Genomic Control for Association Studies
Article first published online: 25 MAY 2004
Volume 55, Issue 4, pages 997–1004, December 1999
How to Cite
Devlin, B. and Roeder, K. (1999), Genomic Control for Association Studies. Biometrics, 55: 997–1004. doi: 10.1111/j.0006-341X.1999.00997.x
- Issue published online: 25 MAY 2004
- Article first published online: 25 MAY 2004
- Received February 1999. Revised June 1999. Accepted July 1999.
- Bayesian inference;
- Complex genetic disorder;
- Population heterogeneity;
- Single nucleotide polymorphism genotypes
Summary. A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with case-control data and yet, like family-based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly independent; and, by using Bayesian outlier methods, it circumvents the need for Bonferroni correction for multiple tests, leading to better performance in many settings while still constraining risk for false positives. The performance of our genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.