AMBIENCE: A novel approach and efficient algorithm for identifying informative genetic and environmental associations with complex phenotypes

Genetics

Volumn 180, Issue 2, 2008, Pages 1191-1210

  Chanda, Pritam ^a   Sucheston, Lara ^b,c   Zhang, Aidong ^a   Brazeau, Daniel ^b   Freudenheim, Jo L ^b   Ambrosone, Christine ^c   Ramanathan, Murali ^b  

^a the State University of New York   (United States)

^b UNIVERSITY AT BUFFALO   (United States)

^c ROSWELL PARK CANCER INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CROHN DISEASE; ENVIRONMENTAL FACTOR; GENE INTERACTION; GENETIC RISK; GENETIC SUSCEPTIBILITY; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; HUMAN; INTERMETHOD COMPARISON; PHENOTYPE; PRIORITY JOURNAL; RHEUMATOID ARTHRITIS; SINGLE NUCLEOTIDE POLYMORPHISM; BIOLOGICAL MODEL; CHROMOSOME 5; COMPARATIVE STUDY; ENVIRONMENT; GENE LINKAGE DISEQUILIBRIUM; GENETIC DATABASE; GENETICS; IMMUNOLOGY; PEDIGREE; POPULATION GENETICS;

ALGORITHMS; CHROMOSOMES, HUMAN, PAIR 5; DATABASES, GENETIC; ENVIRONMENT; GENETICS, POPULATION; HUMANS; LINKAGE DISEQUILIBRIUM; MODELS, GENETIC; PEDIGREE; PHENOTYPE;

EID: 58149353029     PISSN: 00166731     EISSN: 00166731     Source Type: Journal    
DOI: 10.1534/genetics.108.088542     Document Type: Article

References (47)

1. AMBROSONE, C. B., P. G. SHIELDS, J. L. FREUDENHEIM and C. C. HONG, 2007 Re: commonly studied single-nucleotide polymorphisms and breast cancer: results from the Breast Cancer Association Consortium. J. Natl. Cancer Inst. 99: 487 (author reply 488-489).
2. ANDERSON, E. C., and E. A. THOMPSON, 2002 A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160: 1217-1229.
3. ARASON, G. J., J. KRAMER, B. BLASKO, R. KOLKA, P. THORBJORNSDOTTIR et al., 2007 Smoking and a complement gene polymorphism interact in promoting cardiovascular disease morbidity and mortality. Clin. Exp. Immunol. 149: 132-138.
4. BENJAMINI, Y., and Y. HOCHBERG, 1995 Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 57: 289-300.
5. BHASI, K., L. ZHANG, D. BRAZEAU, A. ZHANG and M. RAMANATHAN, 2006a Information-theoretic identification of predictive SNPs and supervised visualization of genome-wide association studies. Nucleic Acids Res. 34: e101.
6. BHASI, K., L. ZHANG, D. BRAZEAU, A. ZHANG and M. RAMANATHAN, 2006b VizStruct for visualization of genome-wide SNP analyses. Bioinformatics 22: 1569-1576.
7. BUSH, W. S., S. M. DUDEK and M. D. RITCHIE, 2006 Parallel multifactor dimensionality reduction: a tool for the large-scale analysis of gene-gene interactions. Bioinformatics 22: 2173-2174.
8. CASPI, A., and T. E. MOFFITT, 2006 Gene-environment interactions in psychiatry: joining forces with neuroscience. Nat. Rev. Neurosci. 7: 583-590.
9. CHANDA, P., A. ZHANG, D. BRAZEAU, L. SUCHESTON, J. L. FREUDENHEIM et al., 2007 Information-theoretic metrics for visualizing gene-environment interactions. Am. J. Hum. Genet. 81: 939-963.
10. CHO, Y. M., M. D. RITCHIE, J. H. MOORE, J. Y. PARK, K. U. LEE et al., 2004 Multifactor-dimensionality reduction shows a two-locus interaction associated with type 2 diabetes mellitus. Diabetologia 47: 549-554.
11. CORMAN, T. H., C. E. LEISERSON and R. L. RIVEST, 2001 Introduction to Algorithms. MIT Press, Cambridge, MA.
12. CULVERHOUSE, R., 2007 The use of the restricted partition method with case-control data. Hum. Hered. 63: 93-100.
13. DALY, M. J., J. D. RIOUX, S. F. SCHAFFNER, T. J. HUDSON and E. S. LANDER, 2001 High-resolution haplotype structure in the human genome. Nat. Genet. 29: 229-232.
14. DONG, C., X. CHU, Y. WANG, L. JIN, T. SHI et al., 2007 Exploration of gene-gene interaction effects using entropy-based methods. Eur. J. Hum. Genet. 16(2): 229-235.
15. DUDBRIDGE, F., 2003 Pedigree disequilibrium tests for multilocus haplotypes. Genet. Epidemiol. 25: 115-121.
16. FANO, R. M., 1961 Transmission of Information: A Statistical Theory of Communications. MIT Press, Cambridge, MA.
17. HAHN, L. W., and J. H. MOORE, 2004 Ideal discrimination of discrete clinical endpoints using multilocus genotypes. In Silico Biol. 4: 183-194.
18. HAHN, L. W., M. D. RITCHIE and J. H. MOORE, 2003 Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 19: 376-382.
19. HAN, T. S., 1980 Multiple mutual informations and multiple interactions in frequency data. Inf. Control 46: 26-45.
20. JAKULIN, A., 2005 Machine learning based on attribute interactions, p. 240 in Computer Science. University of Ljubljana, Ljubljana, Slovenia.
21. JAKULIN, A., and I. BRATKO, 2003 Analyzing attribute dependencies, pp. 229-240 in Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2003), edited by N. LAVRAC, D. GAMBERGER, H. BLOCKEEL and L. TODOROVSKI. Springer, Cavtat-Dubrovnik, Croatia.
22. JAKULIN, A., and I. BRATKO, 2004 Testing the significance of attribute interactions, pp. 409-416 in Proceedings of the Twenty-First International Conference on Machine Learning (ICML-2004), edited by R. GREINER and D. SCHUURMANS. Association for Computing Machinery (ACM), New York, USA.
23. LI, Y., Y. XIANG, H. DENG and Z. SUN, 2007 An entropy-based index for fine-scale mapping of disease genes. J. Genet. Genomics 34: 661-668.
24. LIU, Z., and S. LIN, 2005 Multilocus LD measure and tagging SNP selection with generalized mutual information. Genet. Epidemiol. 29: 353-364.
25. LOU, X. Y., G. B. CHEN, L. YAN, J. Z. MA, J. ZHU et al., 2007 A generalized combinatorial approach for detecting gene-by-gene and gene-by-environment interactions with application to nicotine dependence. Am. J. Hum. Genet. 80: 1125-1137.
26. MA, D. Q., P. L. WHITEHEAD, M. M. MENOLD, E. R. MARTIN, A. E. ASHLEY-KOCH et al., 2005 Identification of significant association and gene-gene interaction of GABA receptor subunit genes in autism. Am. J. Hum. Genet. 77: 377-388.
27. MARTIN, E. R., S. A. MONKS, L. L. WARREN and N. L. KAPLAN, 2000 A test for linkage and association in general pedigrees: the pedigree disequilibrium test. Am. J. Hum. Genet. 67: 146-154.
28. MARTIN, E. R., M. D. RITCHIE, L. HAHN, S. KANG and J. H. MOORE, 2006 A novel method to identify gene-gene effects in nuclear families: the MDR-PDT. Genet. Epidemiol. 30: 111-123.
29. MCGILL, W. J., 1954 Multivariate information transmission. Psychometrika 19: 97-116.
30. MILLER, M. B., G. R. LIND, N. LI and S.-Y. JANG, 2007 Genetic Analysis Workshop 15: simulation of a complex genetic model for rheumatoid arthritis in nuclear families including a dense SNP map with linkage disequilibrium between marker loci and trait loci. BMC Genet. 1 (Suppl 1): S4.
31. MOORE, J. H., J. C. GILBERT, C. T. TSAI, F. T. CHIANG, T. HOLDEN et al., 2006 A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility. J. Theor. Biol. 241: 252-261.
32. MOTSINGER, A. A., B. S. DONAHUE, N. J. BROWN, D. M. RODEN and M. D. RITCHIE, 2006 Risk factor interactions and genetic effects associated with post-operative atrial fibrillation. Pac. Symp. Biocomput. 584-595.
33. OBREITER, M., C. FISCHER, J. CHANG- CLAUDE and L. BECKMANN, 2005 SDMinP: a program to control the family wise error rate using step-down minP adjusted P-values. Bioinformatics 21: 3183-3184.
34. ONNIE, C., S. A. FISHER, K. KING, M. MIRZA, R. ROBERTS et al., 2006 Sequence variation, linkage disequilibrium and association with Crohn's disease on chromosome 5q31. Genes Immun. 7: 359-365.
35. PURCELL, S., B. NEALE, K. TODD-BROWN, L. THOMAS, M. A. FERREIRA et al., 2007 PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81: 559-575.
36. RIOUX, J. D., M. J. DALY, M. S. SILVERBERG, K. LINDBLAD, H. STEINHART et al., 2001 Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease. Nat. Genet. 29: 223-228.
37. RITCHIE, M. D., L. W. HAHN, N. ROODI, L. R. BAILEY, W. D. DUPONT et al., 2001 Multifactor- dimensionality reduction reveals hig-horder interactions among estrogen-metabolism genes in sporadic breast cancer. Am. J. Hum. Genet. 69: 138-147.
38. RITCHIE, M. D., L. W. HAHN and J. H. MOORE, 2003 Power of multifactor dimensionality reduction for detecting gene-gene interactions in the presence of genotyping error, missing data, phenocopy, and genetic heterogeneity. Genet. Epidemiol. 24: 150-157.
39. ROSENBERG, N. A., L. M. LI, R. WARD and J. K. PRITCHARD, 2003 Informativeness of genetic markers for inference of ancestry. Am. J. Hum. Genet. 73: 1402-1422.
40. SHIELDS, P. G., and C. C. HARRIS, 2000 Cancer risk and low-penetrance susceptibility genes in gene-environment interactions. J. Clin. Oncol. 18: 2309-2315.
41. SMITH, M. W., J. A. LAUTENBERGER, H. D. SHIN, J. P. CHRETIEN, S. SHRESTHA et al., 2001 Markers for mapping by admixture linkage disequilibrium in African American and Hispanic populations. Am. J. Hum. Genet. 69: 1080-1094.
42. TALMUD, P. J., and J. W. STEPHENS, 2004 Lipoprotein lipase gene variants and the effect of environmental factors on cardiovascular disease risk. Diabetes Obes. Metab. 6: 1-7.
43. TSAI, C. T., L. P. LAI, J. L. LIN, F. T. CHIANG, J. J. HWANG et al., 2004 Renin-angiotensin system gene polymorphisms and atrial fibrillation. Circulation 109: 1640-1646.
44. VELEZ, D. R., B. C. WHITE, A. A. MOTSINGER, W. S. BUSH, M. D. RITCHIE et al., 2007 A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction. Genet. Epidemiol. 31: 306-315.
45. WATANABE, S., 1960 Information theoretical analysis of multivariate correlation. IBM J. Res. Dev. 4: 66-82.
46. ZHAO, J., E. BOERWINKLE and M. XIONG, 2005 An entropy-based statistic for genomewide association studies. Am. J. Hum. Genet. 77: 27-40.
47. ZHAO, J., E. BOERWINKLE and M. XIONG, 2007 An entropy-based genomewide transmission/disequilibrium test. Hum. Genet. 121: 357-367.