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https://doi.org/10.1371/journal.pgen.0030170
Title: | Power to detect risk alleles using genome-wide tag SNP panels | Authors: | Eberle M.A. Ng P.C. Kuhn K. Zhou L. Peiffer D.A. Galver L. Viaud-Martinez K.A. Lawley C.T. Gunderson K.L. Shen R. Murray S.S. |
Keywords: | article controlled study gene locus gene mapping gene sequence genetic risk genome analysis genotype high throughput screening human human genome major histocompatibility complex risk assessment single nucleotide polymorphism Alleles Genome, Human Haploidy Humans Polymorphism, Single Nucleotide Risk Factors |
Issue Date: | 2007 | Citation: | Eberle M.A., Ng P.C., Kuhn K., Zhou L., Peiffer D.A., Galver L., Viaud-Martinez K.A., Lawley C.T., Gunderson K.L., Shen R., Murray S.S. (2007). Power to detect risk alleles using genome-wide tag SNP panels. PLoS Genetics 3 (10) : 1827-1837. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pgen.0030170 | Rights: | Attribution 4.0 International | Abstract: | Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (? ? 1.8-2.0). Relative risks as low as ? ? 1.1-1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%-35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data. � 2007 Eberle et al. | Source Title: | PLoS Genetics | URI: | https://scholarbank.nus.edu.sg/handle/10635/161865 | ISSN: | 15537390 | DOI: | 10.1371/journal.pgen.0030170 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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