Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate
Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.
Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies
Mieth, Bettina et al.