Simple F test reveals gene-gene interactions in case-control studies

Bioinformatics and Biology Insights

Volumn 6, Issue , 2012, Pages 169-176

  Chen, Guanjie ^a   Yuan, Ao ^b   Zhou, Jie ^a   Bentley, Amy R ^a   Adeyemo, Adebowale ^a   Rotimi, Charles N ^a  

^a NATIONAL HUMAN GENOME RESEARCH INSTITUTE   (United States)

^b HOWARD UNIVERSITY COLLEGE OF MEDICINE   (United States)

Author keywords

F ratio test; G g interactions; Power

Indexed keywords

AFRICAN AMERICAN; ARTICLE; CASE CONTROL STUDY; CONTROLLED STUDY; GENE INTERACTION; GENE LOCUS; GENETIC ASSOCIATION; GENETIC IDENTIFICATION; GENOTYPE; HUMAN; NON INSULIN DEPENDENT DIABETES MELLITUS; NONPARAMETRIC TEST; SAMPLE SIZE; SIMPLE F TEST; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 84863885035     PISSN: None     EISSN: 11779322     Source Type: Journal    
DOI: 10.4137/BBI.S9867     Document Type: Article

References (28)

1. Altmuller J, Palmer LJ, Fischer G, Scherb H, Wjst M. Genomewide scans of complex human diseases: true linkage is hard to find. Am J Hum Genet. 2001;69:936-50.
2. Hirschhorn JN, Lohmueller K, Byrne E, Hirschhorn K. A comprehensive review of genetic association studies. 2002;4:45-61.
3. Joannidis JP, Trikalinos TA, Ntzani EE. Contopouloc-Ioannidis DG, Genetic association in large versus small studies: an empirical assessment. Lancet. 2003;361:567-71.
4. Wang WYS, Barratt BJ, Todd JA. Genome-Wide association studies: theoretical issues and practical concerns. Nat Rev Genet. 2003:109-18.
5. Templeton AR. Epistasis and complex traits. In: Wade M, Brodie B III, Wolf J, editors. Epistasis and Evolutionary Process. Oxford University Press, Oxford; 2000:41-57.
6. Jarvik G, Larson EB, Goddard K, Schellenberg GD, Wijsman EM. Influence of apolipoprotein E genotype on the transmission of Alzheimer disease in a community-based sample. Am J Hum Genet. 1996;58:191-200.
7. MacLeod S, Sinha R, Kadlubar FF, Lang NP. Polymorphism of CTP1A1 and GSTM1 influence the in vivo function of CYP1A2. Mutat Res. 1997;376:135-42.
8. Beales PL, Kopelman PG. Obesity genes. Clin Endocrinol. 1996;45:373-8.
9. Hosmer DW, Lemeshow S. Applied Logistic Regression. New York: John Wiley & Sons, Inc; 2000.
10. Holmans P. Detecting gene-gene interactions using affected sib pair analysis with covariates. Human Heredity. 2002;53:92-102.
11. Kang JH, Kim MJ, Ko SH, et al. Upregulation of rat Ccnd1 gene by exendim-4 in pancreatic beta cell line INS-1: interaction of early growth response-1 with cis-regulatory element. Diabetologia. March 18, 2006.
12. Huang WY, Berndt SI, Kang D, et al. Nucleotide excision repair gene polymorphisms and risk of advanced colorectal adenoma: XPC polymorphisms modify smoking-related risk. Cancer Epidemiology Biomarkers and Prevention. 2006;15:306-11.
13. Li MC, Cui ZS, He QC, Zhou BS. Association of genetic polymorphism in the DNA repair gene XRCC1 with susceptivility to lung cancer in nonsmoking women. Zhonghua Zhong Liu Za Shi. 2005;12(12):713-6.
14. Wang C, Zhou X, Ye S, et al. Combined effects of apo E-CI-CII cluster and LDL-R gene polymorphisms on chromosome 19 and coronary artery disease risk. Int J Hyg Environ Health. February 2, 2006.
15. Qi Y, Bar-Joseph Z, Klein-Seetharaman J. Evaluation of different bilogical data and computaional classification methods for use in protein interaction prediction. Proteins. January 31, 2006.
16. Huber P. The behavior of maximum likelihood estimates under nonstandard conditions. Proc Fifth Berkeley Symp Math Statist Probab. 1967;1: 221-33.
17. Pfanzagl J. On the measurability and consistency of minimum contrast estimators. Metrika. 1969;14:249-72.
18. Rttchie DM. Bioinformatics approaches for detecting gene-gene and gene-enviroment interactions in studies of human disease. Neurosurg Focus. 2005;19(4):E2.
19. Moore HJ. Computational approaches to detecting and characterizing genegene interactions. PSB 2003 Tutotial.
20. Moore HJ, Gilbert CJ, Tsai CT, et al. A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J Theor Biol. January 31, 2006.
21. Cordell JH. Detecting gene-gene interactions that underlie human diseases. Nat Rev Genet. 2009;10(6):392-404.
22. Adeyemo A, Gerry N, Chen G, et al. A Genome Wide association Study of hypertension and blood pressure in African Americans. PLoS Genet. 2009;5(7):e1000564.
23. Storey J, Tibshirani R. Statistical significance for genome wide studies. Proc Natl Acad Sci. 2003;100:9440-5
24. Marchini J, Donnelly P, Cardon LR. Genome wide strategies for detecting multiple loci that influence complex diseases. Nature Genet. 2005; 37:413-7.
25. Parikh H, Groop L. Candidate genes for type 2 diabetes. Reviews in Endocrine and Metabolic Disorders. 2004;5:151-76.
26. Voight B, Scott L, Steinthorsdottir V, et al. Twelve type 2 diabetes susceptibility loci identified through large scale association analysis. Nat Genet. 2010;42(7):579-89.
27. Clemmons DR. Role of insulin-like growth factor in maintaining normal glucose homeostasis. Horm Res. 2004;62(Suppl 1):77-82.
28. Abdi H. Bonferroni and Sidak corrections for multiple comparisons. In: Salkind NJ, editor. Encyclopedia of Measurement and Statistics. Thousand Oaks, CA: Sage; 2007.