Article thumbnail

Comparison of tagging single-nucleotide polymorphism methods in association analyses

By Ellen L Goode, Brooke L Fridley, Zhifu Sun, Elizabeth J Atkinson, Alex S Nord, Shannon K McDonnell, Gail P Jarvik, Mariza de Andrade and Susan L Slager


Several methods to identify tagging single-nucleotide polymorphisms (SNPs) are in common use for genetic epidemiologic studies; however, there may be loss of information when using only a subset of SNPs. We sought to compare the ability of commonly used pairwise, multimarker, and haplotype-based tagging SNP selection methods to detect known associations with quantitative expression phenotypes. Using data from HapMap release 21 on unrelated Utah residents with ancestors from northern and western Europe (CEPH-Utah, CEU), we selected tagging SNPs in five chromosomal regions using ldSelect, Tagger, and TagSNPs. We found that SNP subsets did not substantially overlap, and that the use of trio data did not greatly impact SNP selection. We then tested associations between HapMap genotypes and expression phenotypes on 28 CEU individuals as part of Genetic Analysis Workshop 15. Relative to the use of all SNPs (n = 210 SNPs across all regions), most subset methods were able to detect single-SNP and haplotype associations. Generally, pairwise selection approaches worked extremely well, relative to use of all SNPs, with marked reductions in the number of SNPs required. Haplotype-based approaches, which had identified smaller SNP subsets, missed associations in some regions. We conclude that the optimal tagging SNP method depends on the true model of the genetic association (i.e., whether a SNP or haplotype is responsible); unfortunately, this is often unknown at the time of SNP selection. Additional evaluations using empirical and simulated data are needed

Topics: Proceedings
Publisher: BioMed Central
OAI identifier:
Provided by: PubMed Central

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

Suggested articles


  1. (2005). A haplotype map of the human genome. Nature
  2. (2003). Boerwinkle E: Comparison of strategies for selecting single nucleotide polymorphisms for case/control association studies. Hum Genet
  3. (2005). Burdick JT: Mapping determinants of human gene expression by regional and genome-wide association. Nature
  4. (2007). Common variation in KLKB1 and essential hypertension risk: tagging-SNP haplotype analysis in a case-control study. Hum Genet
  5. (2005). D: A comparison of five methods for selecting tagging single-nucleotide polymorphisms.
  6. (2004). DA: Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium.
  7. (2004). DO: Tag SNP selection for association studies. Genet Epidemiol
  8. (2005). Efficiency and power in genetic association studies. Nat Genet
  9. (2006). Fallin MD: Comparison of SNP tagging methods using empirical data: association study of 713 SNPs on chromosome 12q14.3-12q24.21 for asthma and total serum IgE in an African Caribbean population. Genet Epidemiol
  10. (2002). GA: Score tests for association between traits and haplotypes when linkage phase is ambiguous.
  11. (2006). HapMapbased study of the 17q21 ERBB2 amplicon in susceptibility to breast cancer.
  12. (2006). International HapMap Project []. Build 35;
  13. MacCluer JW: Genetic Analysis Workshop 15: gene expression analysis and approaches to detecting multiple functional loci. BMC Proc 2007, 1(Suppl 1):S1.