Resampling-based multiple hypothesis testing procedures for genetic case-control association studies

Genet Epidemiol. 2006 Sep;30(6):495-507. doi: 10.1002/gepi.20162.


In case-control studies of unrelated subjects, gene-based hypothesis tests consider whether any tested feature in a candidate gene--single nucleotide polymorphisms (SNPs), haplotypes, or both--are associated with disease. Standard statistical tests are available that control the false-positive rate at the nominal level over all polymorphisms considered. However, more powerful tests can be constructed that use permutation resampling to account for correlations between polymorphisms and test statistics. A key question is whether the gain in power is large enough to justify the computational burden. We compared the computationally simple Simes Global Test to the min P test, which considers the permutation distribution of the minimum p-value from marginal tests of each SNP. In simulation studies incorporating empirical haplotype structures in 15 genes, the min P test controlled the type I error, and was modestly more powerful than the Simes test, by 2.1 percentage points on average. When disease susceptibility was conferred by a haplotype, the min P test sometimes, but not always, under-performed haplotype analysis. A resampling-based omnibus test combining the min P and haplotype frequency test controlled the type I error, and closely tracked the more powerful of the two component tests. This test achieved consistent gains in power (5.7 percentage points on average), compared to a simple Bonferroni test of Simes and haplotype analysis. Using data from the Shanghai Biliary Tract Cancer Study, the advantages of the newly proposed omnibus test were apparent in a population-based study of bile duct cancer and polymorphisms in the prostaglandin-endoperoxide synthase 2 (PTGS2) gene.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Intramural

MeSH terms

  • Algorithms
  • Bile Duct Neoplasms / genetics*
  • Case-Control Studies*
  • Computer Simulation
  • Cyclooxygenase 2 / genetics
  • Genetic Markers
  • Genetic Predisposition to Disease / genetics*
  • Haplotypes
  • Humans
  • Linkage Disequilibrium
  • Membrane Proteins / genetics
  • Models, Statistical
  • Polymorphism, Single Nucleotide / genetics*
  • Research Design
  • Sampling Studies*
  • Selection, Genetic


  • Genetic Markers
  • Membrane Proteins
  • Cyclooxygenase 2
  • PTGS2 protein, human