In genome-wide association studies (GWAS), hundreds of thousands of genetic
markers (SNPs) are tested for association with a trait or phenotype. Reported
effects tend to be larger in magnitude than the true effects of these markers,
the so-called ``winner's curse.'' We argue that the classical definition of
unbiasedness is not useful in this context and propose to use a different
definition of unbiasedness that is a property of the estimator we advocate.