A General Framework for Formal Tests of Interaction after Exhaustive Search Methods with Applications to MDR and MDR-PDT

PLoS ONE

Volumn 5, Issue 2, 2010, Pages

  Edwards, Todd L ^a,b,c   Turner, Stephen D ^b   Torstenson, Eric S ^b   Dudek, Scott M ^b   Martin, Eden R ^c   Ritchie, Marylyn D ^b  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF MIAMI MILLER SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; GENE INTERACTION; GENE LOCUS; GENE MUTATION; GENETIC MODEL; MULTIFACTOR DIMENSIONALITY REDUCTION; MULTIFACTOR DIMENSIONALITY REDUCTION PEDIGREE DISEQUILIBRIUM TEST; REGRESSION ANALYSIS; SIMULATION; ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; GENE FREQUENCY; GENETIC EPISTASIS; GENETIC HETEROGENEITY; GENETIC POLYMORPHISM; GENETIC PREDISPOSITION; GENETICS; GENOTYPE; HUMAN; METHODOLOGY; MULTIFACTORIAL INHERITANCE;

ALGORITHMS; COMPUTATIONAL BIOLOGY; EPISTASIS, GENETIC; GENE FREQUENCY; GENETIC HETEROGENEITY; GENETIC PREDISPOSITION TO DISEASE; GENOTYPE; HUMANS; MODELS, GENETIC; MULTIFACTORIAL INHERITANCE; POLYMORPHISM, GENETIC; REGRESSION ANALYSIS;

EID: 77949617596     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0009363     Document Type: Article

References (42)

1. Risch N, Merikangas K (1996) The future of genetic studies of complex human diseases. Science 273: 1516-1517.
2. Hahn LW, Ritchie MD, Moore JH (2003) Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 19: 376-382.
3. Moore JH (2004) Computational analysis of gene-gene interactions using multifactor dimensionality reduction. Expert Rev Mol Diagn 4: 795-803.
4. Moore JH, Gilbert JC, Tsai CT, Chiang FT, Holden T, 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.
5. Moore JH (2007) Genome-wide analysis of epistasis using mutifactor dimensionality reduction: feature selection and construction in the domain of human genetics. In: Zu X, Davidson I, eds. Knowledge Discovery and Data Mining: Challenges and Realities with Real World Data. Hershey: IGI Press.
6. Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, et al. (2001) Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet 69: 138-147.
7. Ritchie MD, Hahn LW, Moore JH (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.
8. Martin ER, Ritchie MD, Hahn L, Kang S, Moore JH (2006) A novel method to identify gene-gene effects in nuclear families: the MDR-PDT. Genet Epidemiol 30: 111-123.
9. Bush WS, Edwards TL, Dudek SM, McKinney BA, Ritchie MD (2008) Alternative contingency table measures improve the power and detection of multifactor dimensionality reduction. BMC Bioinformatics 9: 238.
10. Edwards TL, Lewis K, Velez DR, Dudek S, Ritchie MD (2008) Exploring the Performance of Multifactor Dimensionality Reduction in Large Scale SNP studies and in the Presence of Genetic Heterogeneity among Epistatic Disease Models. Human Heredity Accepted July 1, 2008.
11. Velez DR, White BC, Motsinger AA, Bush WS, Ritchie MD, et al. (2007) A balanced accuracy function for epistasis modeling in imbalanced datasets using multifactor dimensionality reduction. Genet Epidemiol 31: 306-315.
12. Michalsky RS (1983) A theory and methodology of inductive learning. Artif Intell. pp 111-161.
13. Bellman RE (1961) Dynamic Programming. PrincetonNJ.: Princeton University Press.
14. Hosmer DW, Lemeshow S (2000) Applied logistic regression. New York: Wiley.
15. Templeton A (2000) Epistasis and complex traits. In:WadeM, Brodie BI,Wolf J, eds. Epistasis and Evolutionary Process. London: Oxford University Press.
16. Schlicting, Pigliucci (1998) Phenotypic evolution: A reaction norm perspective Sinauer Associates, Inc.
17. Marchini J, Donnelly P, Cardon LR (2005) Genome-wide strategies for detecting multiple loci that influence complex diseases. Nat Genet 37: 413-417.
18. Evans DM, Marchini J, Morris AP, Cardon LR (2006) Two-stage two-locus models in genome-wide association. PLoS Genet 2: e157.
19. Pattin KA, White BC, Barney N, Gui J, Nelson HH, et al. (2009) A computationally efficient hypothesis testing method for epistasis analysis using multifactor dimensionality reduction. Genet Epidemiol 33(1): 87-94.
20. Bush WS, Dudek SM, Ritchie MD (2006) Parallel multifactor dimensionality reduction: a tool for the large-scale analysis of gene-gene interactions. Bioinformatics 22: 2173-2174.
21. Owens JD, Luebke D, Govindaraju N, Harris M, Kruger J, et al. (2007) A survey of general-purpose computation on graphics hardware. Computer Graphics Forum 26: 80-113.
22. Coffey CS, Hebert PR, Krumholz HM, Morgan TM, Williams SM, et al. (2004) Reporting of model validation procedures in human studies of genetic interactions. Nutrition 20: 69-73.
23. Motsinger AA, Ritchie MD (2006) The effect of reduction in cross-validation intervals on the performance of multifactor dimensionality reduction. Genet Epidemiol 30: 546-555.
24. Edwards TL, Pericak-Vance M, Gilbert JR, Haines JL, Martin ER, et al. (2009) An association analysis of Alzheimer disease candidate genes detects an ancestral risk haplotype clade in ACE and putative multilocus association between ACE, A2M, and LRRTM3. Am J Med Genet B Neuropsychiatr Genet 150B: 721-735.
25. Milne RL, Fagerholm R, Nevanlinna H, Benitez J (2008) The importance of replication in gene-gene interaction studies: multifactor dimensionality reduction applied to a two-stage breast cancer case-control study. Carcinogenesis 29: 1215-1218.
26. Millstein J, Conti DV, Gilliland FD, Gauderman WJ (2006) A testing framework for identifying susceptibility genes in the presence of epistasis. Am J Hum Genet 78: 15-27.
27. Liang KY, Zeger SL (1986) Longitudinal Data-Analysis Using Generalized Linear-Models. Biometrika 73: 13-22.
28. Zeger SL, Liang KY (1986) Longitudinal data analysis for discrete and continuous outcomes. Biometrics 42: 121-130.
29. Hancock DB, Martin ER, Li YJ, Scott WK (2007) Methods for interaction analyses using family-based case-control data: conditional logistic regression versus generalized estimating equations. Genet Epidemiol 31: 883-893.
30. Baksh MF, Balding DJ, Vyse TJ, Whittaker JC (2007) Family-based association analysis with ordered categorical phenotypes, covariates and interactions. Genet Epidemiol 31: 1-8.
31. Culverhouse R, Klein T, Shannon W (2004) Detecting epistatic interactions contributing to quantitative traits. Genet Epidemiol 27: 141-152.
32. Motsinger AA, Lee SL, Mellick G, Ritchie MD (2006) GPNN: power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease. BMC Bioinformatics 7: 39.
33. Martin ER, Bass MP, Gilbert JR, Pericak-Vance MA, Hauser ER (2003) Genotype-based association test for general pedigrees: the genotype-PDT. Genet Epidemiol 25: 203-213.
34. Edwards TL, Torstensen E, Dudek S, Martin ER, Ritchie MD (2009) A crossvalidation procedure for general pedigrees and matched odds ratio fitness metric implemented for the multifactor dimensionality reduction pedigree disequilibrium test. Genet Epidemiol, epub ahead of print.
35. Feng Z, Prentice R, Srivastava S (2004) Research issues and strategies for genomic and proteomic biomarker discovery and validation: a statistical perspective. Pharmacogenomics 5: 709-719.
36. Hastie T, Tibshirani R, Friedman J (2001) The elements of statistical learning: data mining, inference and prediction. New York: Springer-Verlag.
37. Edwards TL, Bush WS, Turner SD, Dudek SM, Torstenson ES, et al. (2008) Generating Linkage Disequilibrium Patterns in Data Simulations using genomeSIMLA. Lect Notes Comput Sci 4973: 24-35.
38. Dudek SM, Motsinger AA, Velez DR, Williams SM, Ritchie MD (2006) Data simulation software for whole-genome association and other studies in human genetics. Pac Symp Biocomput. pp 499-510.
39. Bass MP, Martin ER, Hauser ER (2004) Pedigree generation for analysis of genetic linkage and association. Pac Symp Biocomput. pp 93-103.
40. Schmidt M, Hauser ER, Martin ER, Schmidt S (2005) Extension of the SIMLA package for generating pedigrees with complex inheritance patterns: environmental covariates, gene-gene and gene-environment interaction. Stat Appl Genet Mol Biol 4: Article15.
41. Siegmund KD, Langholz B, Kraft P, Thomas DC (2000) Testing linkage disequilibrium in sibships. Am J Hum Genet 67: 244-248.
42. Moore JH, Hahn LW, Ritchie MD, Thornton TA, White B (2004) Routine Discovery of High-Order Epistasis Models for Computational Studies in Human Genetics. Applied Soft Computing 4: 79-86.