Hierarchical false discovery rate-controlling methodology

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We discuss methodology for controlling the false discovery rate (FDR) in complex large-scale studies that involve testing multiple families of hypotheses; the tested hypotheses are arranged in a tree of disjoint subfamilies, and the subfamilies of hypotheses are hierarchically tested by the Benjamini and Hochberg FDR-controlling (BH) procedure. We derive an approximation for the multiple family FDR for independently distributed test statistics: q, the level at which the BH procedure is applied, times the number of families tested plus the number of discoveries, divided by the number of discoveries plus 1. We provide a universal bound for the FDR of the discoveries in the new hierarchical testing approach, 2 × 1.44 × q, and demonstrate in simulations that when the data has an hierarchical structure the new testing approach can be considerably more powerful than the BH procedure.

Original languageEnglish
Pages (from-to)309-316
Number of pages8
JournalJournal of the American Statistical Association
Issue number481
StatePublished - Mar 2008


  • False-discovery rate
  • Hierarchical testing


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