How Well Do HapMap SNPs Capture the Untyped SNPs?

Overview

Journal BMC Genomics

Publisher Biomed Central

Specialty Genetics

Date 2006 Sep 20

PMID 16982009

Citations 14

Authors

Erwin Tantoso

Yuchen Yang

Kuo-Bin Li

Affiliations

Soon will be listed here.

Abstract

Background: The recent advancement in human genome sequencing and genotyping has revealed millions of single nucleotide polymorphisms (SNP) which determine the variation among human beings. One of the particular important projects is The International HapMap Project which provides the catalogue of human genetic variation for disease association studies. In this paper, we analyzed the genotype data in HapMap project by using National Institute of Environmental Health Sciences Environmental Genome Project (NIEHS EGP) SNPs. We first determine whether the HapMap data are transferable to the NIEHS data. Then, we study how well the HapMap SNPs capture the untyped SNPs in the region. Finally, we provide general guidelines for determining whether the SNPs chosen from HapMap may be able to capture most of the untyped SNPs.

Results: Our analysis shows that HapMap data are not robust enough to capture the untyped variants for most of the human genes. The performance of SNPs for European and Asian samples are marginal in capturing the untyped variants, i.e. approximately 55%. Expectedly, the SNPs from HapMap YRI panel can only capture approximately 30% of the variants. Although the overall performance is low, however, the SNPs for some genes perform very well and are able to capture most of the variants along the gene. This is observed in the European and Asian panel, but not in African panel. Through observation, we concluded that in order to have a well covered SNPs reference panel, the SNPs density and the association among reference SNPs are important to estimate the robustness of the chosen SNPs.

Conclusion: We have analyzed the coverage of HapMap SNPs using NIEHS EGP data. The results show that HapMap SNPs are transferable to the NIEHS SNPs. However, HapMap SNPs cannot capture some of the untyped SNPs and therefore resequencing may be needed to uncover more SNPs in the missing region.

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Evaluating the transferability of Hapmap SNPs to a Singapore Chinese population.

Andiappan A, Anantharaman R, Nilkanth P, Wang D, Chew F BMC Genet. 2010; 11:36.

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Beyond the HapMap Genotypic Data: Prospects of Deep Resequencing Projects.

Zhang W, Dolan M Curr Bioinform. 2011; 3(3):178.

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References

. The International HapMap Project. Nature. 2003; 426(6968):789-96. DOI: 10.1038/nature02168. View

Carlson C, Eberle M, Rieder M, Yi Q, Kruglyak L, Nickerson D . Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium. Am J Hum Genet. 2003; 74(1):106-20. PMC: 1181897. DOI: 10.1086/381000. View

Zhang K, Qin Z, Liu J, Chen T, Waterman M, Sun F . Haplotype block partitioning and tag SNP selection using genotype data and their applications to association studies. Genome Res. 2004; 14(5):908-16. PMC: 479119. DOI: 10.1101/gr.1837404. View

Reich D, Cargill M, Bolk S, Ireland J, Sabeti P, Richter D . Linkage disequilibrium in the human genome. Nature. 2001; 411(6834):199-204. DOI: 10.1038/35075590. View

Daly M, Rioux J, Schaffner S, Hudson T, Lander E . High-resolution haplotype structure in the human genome. Nat Genet. 2001; 29(2):229-32. DOI: 10.1038/ng1001-229. View

Johnson G, Esposito L, Barratt B, Smith A, Heward J, Di Genova G . Haplotype tagging for the identification of common disease genes. Nat Genet. 2001; 29(2):233-7. DOI: 10.1038/ng1001-233. View

Patil N, Berno A, Hinds D, BARRETT W, Doshi J, Hacker C . Blocks of limited haplotype diversity revealed by high-resolution scanning of human chromosome 21. Science. 2001; 294(5547):1719-23. DOI: 10.1126/science.1065573. View

Gabriel S, Schaffner S, Nguyen H, Moore J, Roy J, Blumenstiel B . The structure of haplotype blocks in the human genome. Science. 2002; 296(5576):2225-9. DOI: 10.1126/science.1069424. View

Botstein D, Risch N . Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease. Nat Genet. 2003; 33 Suppl:228-37. DOI: 10.1038/ng1090. View

10.

Stram D, Haiman C, Hirschhorn J, Altshuler D, Kolonel L, Henderson B . Choosing haplotype-tagging SNPS based on unphased genotype data using a preliminary sample of unrelated subjects with an example from the Multiethnic Cohort Study. Hum Hered. 2003; 55(1):27-36. DOI: 10.1159/000071807. View

11.

Weale M, Depondt C, Macdonald S, Smith A, Lai P, Shorvon S . Selection and evaluation of tagging SNPs in the neuronal-sodium-channel gene SCN1A: implications for linkage-disequilibrium gene mapping. Am J Hum Genet. 2003; 73(3):551-65. PMC: 1180680. DOI: 10.1086/378098. View

12.

Carlson C, Eberle M, Kruglyak L, Nickerson D . Mapping complex disease loci in whole-genome association studies. Nature. 2004; 429(6990):446-52. DOI: 10.1038/nature02623. View

13.

Livingston R, von Niederhausern A, Jegga A, Crawford D, Carlson C, Rieder M . Pattern of sequence variation across 213 environmental response genes. Genome Res. 2004; 14(10A):1821-31. PMC: 524406. DOI: 10.1101/gr.2730004. View

14.

Collins F, Brooks L, Chakravarti A . A DNA polymorphism discovery resource for research on human genetic variation. Genome Res. 1999; 8(12):1229-31. DOI: 10.1101/gr.8.12.1229. View

15.

Clayton D, Chapman J, Cooper J . Use of unphased multilocus genotype data in indirect association studies. Genet Epidemiol. 2004; 27(4):415-28. DOI: 10.1002/gepi.20032. View

16.

Zhang K, Qin Z, Chen T, Liu J, Waterman M, Sun F . HapBlock: haplotype block partitioning and tag SNP selection software using a set of dynamic programming algorithms. Bioinformatics. 2004; 21(1):131-4. DOI: 10.1093/bioinformatics/bth482. View

17.

Barrett J, Fry B, Maller J, Daly M . Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2004; 21(2):263-5. DOI: 10.1093/bioinformatics/bth457. View

18.

Wang W, Barratt B, Clayton D, Todd J . Genome-wide association studies: theoretical and practical concerns. Nat Rev Genet. 2005; 6(2):109-18. DOI: 10.1038/nrg1522. View

19.

Thorisson G, Smith A, Krishnan L, Stein L . The International HapMap Project Web site. Genome Res. 2005; 15(11):1592-3. PMC: 1310647. DOI: 10.1101/gr.4413105. View

20.

. A haplotype map of the human genome. Nature. 2005; 437(7063):1299-320. PMC: 1880871. DOI: 10.1038/nature04226. View