Power of Single- vs. Multi-Marker Tests of Association

Xuefeng Wang, Nathan J. Morris, Daniel J Schaid, Robert C. Elston

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Current genome-wide association studies still heavily rely on a single-marker strategy, in which each single nucleotide polymorphism (SNP) is tested individually for association with a phenotype. Although methods and software packages that consider multimarker models have become available, they have been slow to become widely adopted and their efficacy in real data analysis is often questioned. Based on conducting extensive simulations, here we endeavor to provide more insights into the performance of simple multimarker association tests as compared to single-marker tests. The results reveal the power advantage as well as disadvantage of the two- vs. the single-marker test. Power differentials depend on the correlation structure among tag SNPs, as well as that between tag SNPs and causal variants. A two-marker test has relatively better performance than single-marker tests when the correlation of the two adjacent markers is high. However, using HapMap data, two-marker tests tended to have a greater chance of being less powerful than single-marker tests, due to constraints on the number of actual possible haplotypes in the HapMap data. Yet, the average power difference was small whenever the one-marker test is more powerful, while there were many situations where the two-marker test can be much more powerful. These findings can be useful to guide analyses of future studies.

Original languageEnglish (US)
Pages (from-to)480-487
Number of pages8
JournalGenetic Epidemiology
Volume36
Issue number5
DOIs
StatePublished - Jul 2012

Fingerprint

HapMap Project
Single Nucleotide Polymorphism
Genome-Wide Association Study
Haplotypes
Software
Phenotype

Keywords

  • Asymptotic power
  • Genome-wide association
  • Single-marker test
  • Two-marker test

ASJC Scopus subject areas

  • Genetics(clinical)
  • Epidemiology

Cite this

Power of Single- vs. Multi-Marker Tests of Association. / Wang, Xuefeng; Morris, Nathan J.; Schaid, Daniel J; Elston, Robert C.

In: Genetic Epidemiology, Vol. 36, No. 5, 07.2012, p. 480-487.

Research output: Contribution to journalArticle

Wang, Xuefeng ; Morris, Nathan J. ; Schaid, Daniel J ; Elston, Robert C. / Power of Single- vs. Multi-Marker Tests of Association. In: Genetic Epidemiology. 2012 ; Vol. 36, No. 5. pp. 480-487.
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