Biostatistical aspects of genome-wide association studies
- PMID: 18217698
- DOI: 10.1002/bimj.200710398
Biostatistical aspects of genome-wide association studies
Abstract
To search the entire human genome for association is a novel and promising approach to unravelling the genetic basis of complex genetic diseases. In these genome-wide association studies (GWAs), several hundreds of thousands of single nucleotide polymorphisms (SNPs) are analyzed at the same time, posing substantial biostatistical and computational challenges. In this paper, we discuss a number of biostatistical aspects of GWAs in detail. We specifically consider quality control issues and show that signal intensity plots are a sine qua condition non in today's GWAs. Approaches to detect and adjust for population stratification are briefly examined. We discuss different strategies aimed at tackling the problem of multiple testing, including adjustment of p -values, the false positive report probability and the false discovery rate. Another aspect of GWAs requiring special attention is the search for gene-gene and gene-environment interactions. We finally describe multistage approaches to GWAs.
(c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Similar articles
-
Universal false discovery rate estimation methodology for genome-wide association studies.Hum Hered. 2008;65(4):183-94. doi: 10.1159/000112365. Epub 2007 Dec 11. Hum Hered. 2008. PMID: 18073488
-
Using genome-wide pathway analysis to unravel the etiology of complex diseases.Genet Epidemiol. 2009 Jul;33(5):419-31. doi: 10.1002/gepi.20395. Genet Epidemiol. 2009. PMID: 19235186
-
Reporting and interpretation in genome-wide association studies.Int J Epidemiol. 2008 Jun;37(3):641-53. doi: 10.1093/ije/dym257. Epub 2008 Feb 11. Int J Epidemiol. 2008. PMID: 18270206
-
Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure.Curr Opin Lipidol. 2008 Apr;19(2):133-43. doi: 10.1097/MOL.0b013e3282f5dd77. Curr Opin Lipidol. 2008. PMID: 18388693 Review.
-
The pursuit of genome-wide association studies: where are we now?J Hum Genet. 2010 Apr;55(4):195-206. doi: 10.1038/jhg.2010.19. Epub 2010 Mar 19. J Hum Genet. 2010. PMID: 20300123 Review.
Cited by
-
Using Bayesian networks to discover relations between genes, environment, and disease.BioData Min. 2013 Mar 21;6(1):6. doi: 10.1186/1756-0381-6-6. BioData Min. 2013. PMID: 23514120 Free PMC article.
-
Empirical hierarchical bayes approach to gene-environment interactions: development and application to genome-wide association studies of lung cancer in TRICL.Genet Epidemiol. 2013 Sep;37(6):551-559. doi: 10.1002/gepi.21741. Epub 2013 Jul 26. Genet Epidemiol. 2013. PMID: 23893921 Free PMC article.
-
Pharmacogenetics of antihypertensive treatment: detailing disciplinary dissonance.Pharmacogenomics. 2009 Aug;10(8):1295-307. doi: 10.2217/pgs.09.61. Pharmacogenomics. 2009. PMID: 19663674 Free PMC article. Review.
-
Beta2-adrenergic receptor gene polymorphisms as systemic determinants of healthy aging in an evolutionary context.Mech Ageing Dev. 2010 May;131(5):338-45. doi: 10.1016/j.mad.2010.04.001. Epub 2010 Apr 24. Mech Ageing Dev. 2010. PMID: 20399803 Free PMC article.
-
Genome-wide analysis of genetic predisposition to Alzheimer's disease and related sex disparities.Alzheimers Res Ther. 2019 Jan 12;11(1):5. doi: 10.1186/s13195-018-0458-8. Alzheimers Res Ther. 2019. PMID: 30636644 Free PMC article.
