Please use this identifier to cite or link to this item: 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
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