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

Abstract

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.

• Authors: Bingshu E Chen, Lori C Sakoda, Ann W Hsing, Philip S Rosenberg
• Journal: Genetic epidemiology (Genet Epidemiol) Vol. 30 Issue 6 Pg. 495-507 (Sep 2006) ISSN: 0741-0395 [Print] United States
• PMID: 16755536 (Publication Type: Comparative Study, Journal Article, Research Support, N.I.H., Intramural)

Chemical References

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

Topics

• 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