Assessing the Probability that a Finding Is Genuine for Large-Scale Genetic Association Studies.

ABSTRACT: Genetic association studies routinely involve massive numbers of statistical tests accompanied by P-values. Whole genome sequencing technologies increased the potential number of tested variants to tens of millions. The more tests are performed, the smaller P-value is required to be deemed significant. However, a small P-value is not equivalent to small chances of a spurious finding and significance thresholds may fail to serve as efficient filters against false results. While the Bayesian approach can provide a direct assessment of the probability that a finding is spurious, its adoption in association studies has been slow, due in part to the ubiquity of P-values and the automated way they are, as a rule, produced by software packages. Attempts to design simple ways to convert an associa

SUBMITTER: Kuo CL 

PROVIDER: S-EPMC4425705 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature