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Assessing The Probability That A Finding Is Genuine For Large-Scale Genetic Association Studies, Chia-Ling Kuo, Olga A. Vsevolozhskaya, Dmitri V. Zaykin
Assessing The Probability That A Finding Is Genuine For Large-Scale Genetic Association Studies, Chia-Ling Kuo, Olga A. Vsevolozhskaya, Dmitri V. Zaykin
Olga A. Vsevolozhskaya
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 …
Use Of P-Values To Evaluate The Probability Of A Genuine Finding In Large-Scale Genetic Association Studies, Olga A. Vsevolozhskaya, Qing Lu, Chia-Ling Kuo, Dmitri V. Zaykin
Use Of P-Values To Evaluate The Probability Of A Genuine Finding In Large-Scale Genetic Association Studies, Olga A. Vsevolozhskaya, Qing Lu, Chia-Ling Kuo, Dmitri V. Zaykin
Olga A. Vsevolozhskaya
To claim the existence of an association in modern genome-wide association studies (GWAS), a nominal P-value has to exceed a stringent Bonferroni-adjusted significance level. Despite strictness of the correction, a significant P-value does not indicate high probability that the claimed association is genuine. A simple Bayesian solution -- the False Positive Report Probability (FPRP) -- was previously proposed to convert the observed P-value to the corresponding probability of no true association. Although the FPRP solution is highly popular, it does not reflect probability that a particular finding is false. Here, we offer a simple POFIG method -- a Probability that …