Balding DJ. A tutorial on statistical methods for population association studies. Nat Rev Genet 7: 781-791

Department of Epidemiology and Public Health, Imperial College, St Marys Campus, Norfolk Place, London W2 1PG, UK.
Nature Reviews Genetics (Impact Factor: 36.98). 11/2006; 7(10):781-91. DOI: 10.1038/nrg1916
Source: PubMed


Although genetic association studies have been with us for many years, even for the simplest analyses there is little consensus on the most appropriate statistical procedures. Here I give an overview of statistical approaches to population association studies, including preliminary analyses (Hardy-Weinberg equilibrium testing, inference of phase and missing data, and SNP tagging), and single-SNP and multipoint tests for association. My goal is to outline the key methods with a brief discussion of problems (population structure and multiple testing), avenues for solutions and some ongoing developments.

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    • "All statistical analyses were performed using STATA software, version 11.0. Testing for deviations from Hardy–Weinberg equilibrium (HWE) was carried out using a fast exact test [19], and the significance level of departure from HWE among controls was set at a = 10 À3 [20]. The PLINK software v1.07 was used for haplotypes construction and analyses. "
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    • "Genetic methods like association mapping (see Balding [2] for a review), aiming at finding correlations between genetic markers and phenotypic traits in germplasm, may allow to complete the knowledge of both reblooming genetic control and rose breeding history. "
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    • "For example, if m 5 100,000, it is expected that about 5,000 false positive associations are observed by chance even none of SNPs is diseaserelated . Thus, multiple comparison is an important consideration in GWAS analysis, and must be handled appropriately [18] . "
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