Weighted multiple testing procedures for genomic studies

With the rapid development of biological technology, measurement of thousands of genes or SNPs can be carried out simultaneously. Improved procedures for multiple hypothesis testing when the number of tests is very large are critical for interpreting genomic data. In this paper, we review recent developments on three distinct but closely related methods involving p-value weighting to improve statistical power while also controlling for the false discovery rate or the family wise error rate.