DOI QR코드

DOI QR Code

The Effect of Increasing Control-to-case Ratio on Statistical Power in a Simulated Case-control SNP Association Study

  • Kang, Moon-Su (Department of Physiology, College of Medicine, Hanyang University) ;
  • Choi, Sun-Hee (Department of Physiology, College of Medicine, Hanyang University) ;
  • Koh, In-Song (Department of Physiology, College of Medicine, Hanyang University)
  • 발행 : 2009.09.30

초록

Generally, larger sample size leads to a greater statistical power to detect a significant difference. We may increase the sample size for both case and control in order to obtain greater power. However, it is often the case that increasing sample size for case is not feasible for a variety of reasons. In order to look at change in power as the ratio of control to case varies (1:1 to 4:1), we conduct association tests with simulated data generated by PLINK. The simulated data consist of 50 disease SNPs and 300 non-disease SNPs and we compute powers for disease SNPs. Genetic Power Calculator was used for computing powers with varying the ratio of control to case (1:1, 2:1, 3:1, 4:1). In this study, we show that gains in statistical power resulting from increasing the ratio of control to case are substantial for the simulated data. Similar results might be expected for real data.

키워드

참고문헌

  1. Ambrosius, W.T., Lange, E.M., and Langefeld, C.D. (2004). Power for genetic association studies with random allele frequencies and genotype distributions. Am. J. Hum. Genet. 74, 683-693 https://doi.org/10.1086/383282
  2. Burton, P.R., Hansell, A.L., Fortier I., Manolio, T.A., Khoury, M.J., Little, J., and Elliott, P. (2009). Size matters: just how big is BIG? Quantifying realistic sample size requirements for human genome epidemiology. Int. J. Epidemiol. 38, 263-273 https://doi.org/10.1093/ije/dyn147
  3. De La Vega, F.M., Gordon, D., Su, X., Scafe, C., Isaac, H., Gilbert, D.A., and Spier, E.G. (2005). Power and sample size calculations for genetic case/control studies using gene-centric SNP maps: Application to human chromosomes 6, 21, and 22 in three populations. Hum. Hered. 60, 43-60 https://doi.org/10.1159/000087918
  4. Dupont, W.D. (1988). Power calculations for matched case-control studies. Biometrics 44, 1157-1168 https://doi.org/10.2307/2531743
  5. Dupont, W.D., and Plummer, W.D.Jr. (1990). Power and sample size calculations. A review and computer program. Control Clin. Trials. 11, 116-128 https://doi.org/10.1016/0197-2456(90)90005-M
  6. Hennessy, S., Bilker, W.B., Berlin, J.A., and Storm B.L. (1999). Factors influencing the optimal control to case ratio in matched case-control studies. Am. J. Epidemiol. 149, 195-197 https://doi.org/10.1093/oxfordjournals.aje.a009786
  7. Lewis, C.M. (2002). Genetic association studies: design, analysis and interpretation. Brief Bioinform. 3, 144-153 https://doi.org/10.1093/bib/3.2.146
  8. Park, K., and Kim, H. (2007). A review of power and sample size estimation in genomewide association studies. J. Prev. Med. Public Health. 40, 114-121 https://doi.org/10.3961/jpmph.2007.40.2.114
  9. Purcell, S., Cherny, S.S., and Sham, P.C. (2003). Genetic power calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics 19, 149-150 https://doi.org/10.1093/bioinformatics/19.1.149
  10. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.R., Bender, D., Maller, J., Sklar, P., De Bakker, P.I.W., Daily, M.J., and Sham, P.C. (2007). PLINK: A toolset for whole-genome association and population-based linkage analysis. Am. J. Hum. Genet. 81,559-575 https://doi.org/10.1086/519795
  11. Schork, N.J. (2002). Power calculation for genetic association studies using estimated probability distributions. Am. J. Hum. Genet. 70, 1480-1489 https://doi.org/10.1086/340788

피인용 문헌

  1. Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder vol.25, pp.15, 2016, https://doi.org/10.1093/hmg/ddw181
  2. Power evaluation of asymptotic tests for comparing two binomial proportions to detect direct and indirect association in large-scale studies pp.1477-0334, 2017, https://doi.org/10.1177/0962280215608528
  3. IndOR: a new statistical procedure to test for SNP-SNP epistasis in genome-wide association studies vol.31, pp.21, 2012, https://doi.org/10.1002/sim.5364
  4. Diagnostic evaluation of risk for bleeding in cardiac surgery with extracorporeal circulation vol.26, pp.0, 2018, https://doi.org/10.1590/1518-8345.2523.3092