ExampleDataCor is a list consisting of three components: BetaHat, SE, cor. ExampleDataCor$BetaHat is a
numeric vector that contains the main genetic effect (beta/log(odds ratio)) estimates
for a SNP across 10 overlapping case-control studies for 10 different diseases. Each of the 10 studies has
a distinct set of 7000 cases and a common set of 10000 controls shared across all the studies.
In each case-control study, we fit a logistic regression of the case-control status on the genotype
coded as the minor allele count for all the individuals in the sample. One can also include various
covariates, such as, age, gender, principal components (PCs) of ancestries in the logistic regression.
From each logistic regression for a disease, we obtain the estimate of the main genetic association
parameter (beta/log(odds ratio)) along with the corresponding standard error. Since the studies have overlapping
subjects, the beta-hat across traits are correlated. ExampleDataCor$SE contains the standard error vector
corresponding to the correlated beta-hat vector. ExampleDataCor$cor is a numeric square matrix providing
the correlation matrix of the correlated beta-hat vector.