A new statistic and its power to infer membership in a genome-wide association study using genotype frequencies Export

@article{Jacobs2009, abstract = {Aggregate results from genome-wide association studies (GWAS)1, 2, 3, such as genotype frequencies for cases and controls, were until recently often made available on public websites4, 5 because they were thought to disclose negligible information concerning an individual's participation in a study. Homer et al.6 recently suggested that a method for forensic detection of an individual's contribution to an admixed DNA sample could be applied to aggregate GWAS data. Using a likelihood-based statistical framework, we developed an improved statistic that uses genotype frequencies and individual genotypes to infer whether a specific individual or any close relatives participated in the GWAS and, if so, what the participant's phenotype status is. Our statistic compares the logarithm of genotype frequencies, in contrast to that of Homer et al.6, which is based on differences in either SNP probe intensity or allele frequencies. We derive the theoretical power of our test statistics and explore the empirical performance in scenarios with varying numbers of randomly chosen or top-associated SNPs.}, author = {Jacobs, Kevin B. and Yeager, Meredith and Wacholder, Sholom and Craig, David and Kraft, Peter and Hunter, David J. and Paschal, Justin and Manolio, Teri A. and Tucker, Margaret and Hoover, Robert N. and Thomas, Gilles D. and Chanock, Stephen J. and Chatterjee, Nilanjan}, citeulike-article-id = {5887963}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/ng.455}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/ng.455}, day = {04}, doi = {10.1038/ng.455}, issn = {1061-4036}, journal = {Nature Genetics}, keywords = {gwas}, month = {October}, number = {11}, pages = {1253--1257}, posted-at = {2009-10-30 13:34:39}, priority = {3}, publisher = {Nature Publishing Group}, title = {A new statistic and its power to infer membership in a genome-wide association study using genotype frequencies}, url = {http://dx.doi.org/10.1038/ng.455}, volume = {41}, year = {2009} }

TY - JOUR ID - Jacobs2009 L3 - citeulike-article-id:5887963 N2 - Aggregate results from genome-wide association studies (GWAS)1, 2, 3, such as genotype frequencies for cases and controls, were until recently often made available on public websites4, 5 because they were thought to disclose negligible information concerning an individual's participation in a study. Homer et al.6 recently suggested that a method for forensic detection of an individual's contribution to an admixed DNA sample could be applied to aggregate GWAS data. Using a likelihood-based statistical framework, we developed an improved statistic that uses genotype frequencies and individual genotypes to infer whether a specific individual or any close relatives participated in the GWAS and, if so, what the participant's phenotype status is. Our statistic compares the logarithm of genotype frequencies, in contrast to that of Homer et al.6, which is based on differences in either SNP probe intensity or allele frequencies. We derive the theoretical power of our test statistics and explore the empirical performance in scenarios with varying numbers of randomly chosen or top-associated SNPs. IS - 11 JF - Nature Genetics SN - 1061-4036 EP - 1257 TI - A new statistic and its power to infer membership in a genome-wide association study using genotype frequencies PB - Nature Publishing Group VL - 41 SP - 1253 KW - gwas AU - Jacobs, Kevin AU - Yeager, Meredith AU - Wacholder, Sholom AU - Craig, David AU - Kraft, Peter AU - Hunter, David AU - Paschal, Justin AU - Manolio, Teri AU - Tucker, Margaret AU - Hoover, Robert AU - Thomas, Gilles AU - Chanock, Stephen AU - Chatterjee, Nilanjan PY - 2009/10/04/ UR - http://dx.doi.org/10.1038/ng.455 ER -