Optimal two-stage strategy for detecting interacting genes in complex diseases

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Optimal two-stage strategy for detecting interacting genes in complex diseases

Publisher
BioMed Central
Publication Date
Jun 15, 2006
Source
PMC
Keywords
Disciplines
  • Design
  • Medicine
License
Unknown

Abstract

1471-2156-7-39.fm ral ss BioMed CentBMC Genetics Open AcceResearch article Optimal two-stage strategy for detecting interacting genes in complex diseases luliana lonita*1 and Michael Man2 Address: 1Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY, 10012, USA and 2Nonclinical Statistics, Pfizer PGRD, 2800 Plymouth Rd, Ann Arbor, Ml, 48105, USA Email: luliana lonita* - [email protected]; Michael Man - [email protected] * Corresponding author Abstract Background: The mapping of complex diseases is one of the most important problems in human genetics today. The rapid development of technology for genetic research has led to the discovery of millions of polymorphisms across the human genome, making it possible to conduct genome- wide association studies with hundreds of thousands of markers. Given the large number of markers to be tested in such studies, a two-stage strategy may be a reasonable and powerful approach: in the first stage, a small subset of promising loci is identified using single-locus testing, and, in the second stage, multi-locus methods are used while taking into account the loci selected in the first stage. In this report, we investigate and compare two possible two-stage strategies for genome-wide association studies: a conditional approach and a simultaneous approach. Results: We investigate the power of both the conditional and the simultaneous approach to detect the disease loci for a range of two-locus disease models in a case-control study design. Our results suggest that, overall, the conditional approach is more robust and more powerful than the simultaneous approach; the conditional approach can greatly outperform the simultaneous approach when one of the two disease loci has weak marginal effect, but interacts strongly with the other, stronger locus (easily detectable using single-locus methods in the first stage). Conclusion: Genome-wide association studies hold the promise of finding new g

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