Genomic control

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Genomic control (GC) is a statistical method that is commonly used to control for the confounding effects of population stratification in genetic association studies. The method was originally outlined by Bernie Devlin and Kathryn Roeder in a 1999 paper. [1] It involves using a set of anonymous genetic markers to estimate the effect of population structure on the distribution of the chi-square statistic. The distribution of the chi-square statistics for a given allele that is suspected to be associated with a given trait can then be compared to the distribution of the same statistics for an allele that is expected not to be related to the trait. [2] [3] The method is supposed to involve the use of markers that are not linked to the marker being tested for a possible association. [4] In theory, it takes advantage of the tendency of population structure to cause overdispersion of test statistics in association analyses. [5] The genomic control method is as robust as family-based designs, despite being applied to population-based data. [6] It has the potential to lead to a decrease in statistical power to detect a true association, and it may also fail to completely eliminate the biasing effects of population stratification. [7] A more robust form of the genomic control method can be performed by expressing the association being studied as two Cochran–Armitage trend tests, and then applying the method to each test separately. [8]

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References

  1. ↑ Devlin, Bernie; Roeder, Kathryn (1999). "Genomic Control for Association Studies". Biometrics . 55 (4): 997–1004. CiteSeerX   10.1.1.420.1751 . doi:10.1111/j.0006-341X.1999.00997.x. ISSN   1541-0420. PMID   11315092.
  2. ↑ Donnelly, Peter; Phillips, Michael S.; Cardon, Lon R.; Marchini, Jonathan (May 2004). "The effects of human population structure on large genetic association studies". Nature Genetics . 36 (5): 512–517. doi: 10.1038/ng1337 . ISSN   1546-1718. PMID   15052271.
  3. ↑ Altshuler, David; Hirschhorn, Joel N.; Henderson, Brian; Sklar, Pamela; Lander, Eric S.; Kolonel, Laurence N.; Petryshen, Tracey L.; Pato, Michele T.; Pato, Carlos N. (April 2004). "Assessing the impact of population stratification on genetic association studies". Nature Genetics. 36 (4): 388–393. doi: 10.1038/ng1333 . ISSN   1546-1718. PMID   15052270.
  4. ↑ Krawczak, Michael; Dempfle, Astrid; Lieb, Wolfgang; Freitag-Wolf, Sandra; Yadav, Pankaj (2015-10-01). "Allowing for population stratification in case-only studies of gene–environment interaction, using genomic control". Human Genetics . 134 (10): 1117–1125. doi:10.1007/s00439-015-1593-y. ISSN   1432-1203. PMID   26297539. S2CID   18146948.
  5. ↑ Devlin, Bernie; Roeder, Kathryn; Wasserman, Larry (2001-11-01). "Genomic Control, a New Approach to Genetic-Based Association Studies". Theoretical Population Biology . 60 (3): 155–166. doi:10.1006/tpbi.2001.1542. ISSN   0040-5809. PMID   11855950. S2CID   11547174.
  6. ↑ Roeder, Kathryn; Devlin, B.; Bacanu, Silviu-Alin (2000-06-01). "The Power of Genomic Control". The American Journal of Human Genetics . 66 (6): 1933–1944. doi:10.1086/302929. ISSN   1537-6605. PMC   1378064 . PMID   10801388.
  7. ↑ Greenberg, David A.; Zhang, Junying; Shmulewitz, Dvora (2004). "Case-Control Association Studies in Mixed Populations: Correcting Using Genomic Control". Human Heredity . 58 (3–4): 145–153. doi:10.1159/000083541. ISSN   1423-0062. PMID   15812171. S2CID   24635575.
  8. ↑ Gastwirth, Joseph L.; Freidlin, Boris; Zheng, Gang (2006-02-01). "Robust Genomic Control for Association Studies". The American Journal of Human Genetics. 78 (2): 350–356. doi:10.1086/500054. ISSN   1537-6605. PMC   1380242 . PMID   16400614.
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