ExampleDataUncor is a list which has two components: BetaHat, SE. The numeric vector ExampleDataUncor$BetaHat contains the main genetic effect (beta/log(odds ratio)) estimates for a single nucleotide polymorphism (SNP) obtained from 10 separate case-control studies for 10 different diseases. In each case-control study comprising a distinct set of 7000 cases and 10000 controls, we fit a logistic regression of the case-control status on the genotype coded as the minor allele count for all the individuals in the sample. One can also include various covariates, such as, age, gender, principal components (PCs) of ancestries in the logistic regression. From each logistic regression for a disease, we obtain the estimate of the main genetic association parameter (beta/log(odds ratio)) along with the corresponding standard error. Since the studies do not have any overlapping subject, the beta-hat across the traits are uncorrelated. ExampleDataUncor$SE is the second numeric vector that contains the standard errors corresponding to the uncorrelated beta-hat vector.
A list of two numeric vectors each of length 10 (for 10 studies):
beta hat vector of length 10.
standard error vector corresponding to beta-hat vector.
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