An efficient Monte Carlo approach to assessing statistical significance in genomic studies
An efficient Monte Carlo approach to assessing statistical significance in genomic studies
Abstract Motivation: Multiple hypothesis testing is a common problem in genome research, particularly in microarray experiments and genomewide association studies. Failure to account for the effects of multiple comparisons would result in an abundance of false positive results. The Bonferroni correction and Holm's step-down procedure are overly conservative, whereas the …