Abstract
Correlated samples have been frequently avoided in case-controlgenetic association studies in part because the methods for handling them are either noteasily implemented or not widely known. Weadvocate one method for case-control association analysis of correlatedsamples -- the effective sample size method -- as a simple andaccessible approach that does not require specialized computer programs.The effective sample size method captures the variance inflationof allele frequency estimation exactly, and can be used to modify thechi-square test statistic, p-value, and 95% confidence interval ofodds-ratio simply by replacing the apparent number of allele counts with theeffective ones. For genotype frequency estimation, although a singleeffective sample size is unable to completely characterize the variance inflation,an averaged one can satisfactorily approximate the simulated result.The effective sample size method is applied to the rheumatoid arthritissiblings data collected from the North American Rheumatoid Arthritis Consortium (NARAC)to establish a significant association with the interferon-inducedhelicasel gene (IFIH1) previously being identified as a type 1 diabetessusceptibility locus. Connections between the effective sample sizemethod and other methods, such as generalized estimation equation,variance of eigenvalues for correlation matrices, and genomic controls,are also discussed.
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Yang, Y., Remmers, E., Ogunwole, C. et al. Effective Sample Size: Quick Estimation of the Effect of Related Samples in Genetic Case-Control Association Analyses. Nat Prec (2007). https://doi.org/10.1038/npre.2007.400.1
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DOI: https://doi.org/10.1038/npre.2007.400.1