An efficient Monte Carlo approach to assessing statistical significance in genomic studies

Applications to simulated and real data demonstrate that the proposed Monte Carlo approach provides accurate error control, and can be substantially more powerful than the Bonferroni and Holm methods, especially when the test statistics are highly correlated.