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Comparison of tagging single-nucleotide polymorphism methods in association analyses.
Ellen L Goode1, Brooke L Fridley, Zhifu Sun
1Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. egoode@mayo.edu
BMC Proceedings
|May 10, 2008
Summary
Selecting subsets of single-nucleotide polymorphisms (SNPs) for genetic studies is efficient, but the best method depends on the unknown genetic association model. Pairwise SNP selection effectively identifies associations with fewer markers.
Area of Science:
- Genetics
- Bioinformatics
- Statistical Genomics
Background:
- Tagging single-nucleotide polymorphisms (SNPs) are crucial for genetic association studies.
- Using a subset of SNPs may lead to information loss compared to analyzing all SNPs.
- Various methods exist for selecting tagging SNPs, including pairwise, multimarker, and haplotype-based approaches.
Purpose of the Study:
- To compare the effectiveness of common tagging SNP selection methods in detecting associations with quantitative expression phenotypes.
- To evaluate the performance of pairwise, multimarker, and haplotype-based methods using HapMap data.
Main Methods:
- Utilized HapMap release 21 data from CEPH-Utah (CEU) individuals.
- Applied ldSelect, Tagger, and TagSNPs for tagging SNP selection across five chromosomal regions.
- Tested associations between selected SNP subsets and quantitative expression phenotypes in 28 CEU individuals.
Main Results:
- SNP subsets generated by different methods showed minimal overlap.
- Most subset methods successfully detected single-SNP and haplotype associations compared to using all SNPs.
- Pairwise selection methods demonstrated high efficiency, significantly reducing the number of SNPs required while detecting associations.
Conclusions:
- The optimal tagging SNP selection strategy is contingent on the underlying genetic association model (SNP vs. haplotype), which is often unknown.
- Pairwise approaches are highly effective for detecting associations with substantial SNP reduction.
- Haplotype-based methods, while selecting fewer SNPs, occasionally missed significant associations.
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