Exploring Data From Genetic Association Studies Using Bayesian Variable Selection and the Dirichlet Process: Application to Searching for Gene × Gene Patterns

Genetic Epidemiology

Volumn 36, Issue 6, 2012, Pages 663-674

  Papathomas, Michail ^a,b   Molitor, John ^b,c   Hoggart, Clive ^b   Hastie, David ^b   Richardson, Sylvia ^b,d  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c OREGON STATE UNIVERSITY   (United States)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Clustering; Covariate profiles; Profile regression

Indexed keywords

ARTICLE; BAYESIAN LEARNING; GENE CLUSTER; GENETIC ASSOCIATION; GENETIC RISK; HETEROZYGOSITY; HOMOZYGOSITY; LUNG CANCER; MATHEMATICAL MODEL; PHENOTYPE; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM;

BAYES THEOREM; CLUSTER ANALYSIS; COMPUTER SIMULATION; GENETIC ASSOCIATION STUDIES; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; LUNG NEOPLASMS; MODELS, GENETIC; MODELS, STATISTICAL; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84865067602     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21661     Document Type: Article

References (43)

1. Amos CI, Wu X, Broderick P, Gorlov IP, Gu J, Eisen T, Dong Q, Zhang Q, Gu X, Vijayakrishnan J, Sullivan K, Matakidou A, Wang Y, Mills G, Doheny K, Tsai YY, Chen WV, Shete S, Spitz MR, Houlston RS. 2008. Genome-wide association scan of tag SNPs identifies a susceptibility locus for lung cancer at 15q25.1. Nat Genet 40: 616-622.
2. Bastone L, Reilly M, Rader DJ, Foulkes AS. 2004. MDR and PRP: a comparison of methods for high-order genotype-phenotype associations. Hum Hered 58: 82-92.
3. Bigelow LJ, Dunson DB. 2009. Bayesian semiparametric joint models for functional predictors. J Am Stat Assoc 104: 26-36.
4. Chernoff H, Lo SH, Zheng T. 2009. Discovering influencial variables: a method of partitions. Ann Appl Stat 3: 1335-1369.
5. Chung Y, Dunson DB. 2009. Nonparametric Bayes conditional distribution modelling with variable selection. J Am Stat Assoc 104: 1646-1660.
6. Dahl DB, Qianxing M, Vannucci M. 2008. Simultaneous inference for multiple testing and clustering via a Dirichlet process mixture model. Stat Model 8: 23-39.
7. Dahl DB, Newton MA. 2007. Multiple hypothesis testing by clustering treatment effects. J Am Stat Assoc 102: 517-526.
8. Dirichlet Process Bayesian Clustering (DiPBaC). 2012. BGX (Bayesian Gene eXpression web site). Available from: http://www.bgx.org.uk/software/DiPBaC_Matlab.zip. Accessed on June 28, 2012.
9. Escobar M, West M. 1995. Bayesian density estimation and inference using mixtures. J Am Stat Assoc 90: 577-588.
10. Ferguson TS. 1973. A semiparametric Bayesian analysis of some non-parametric problems. Ann Stat 1: 209-230.
11. Green PJ, Richardson S. 2001. Modelling heterogeneity with and without the Dirichlet process. Scand J Stat 28: 355-375.
12. Gui J, Andrew AS, Andrews P, Nelson HM, Kelsey KT, Karagas MR, Moore JH. 2010. A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility. Ann Hum Genet 75: 20-28.
13. Hung RJ, McKay1 JD, Gaborieau V, Boffetta P, Hashibe M, Zaridze D, Mukeria A, Szeszenia-Dabrowska N, Lissowska J, Rudnai P, Fabianova E, Mates D, Bencko V, Foretova L, Janout V, Chen C, Goodman G, Field JK, Liloglou T, Xinarianos G, Cassidy A, McLaughlin J, Liu G, Narod S, Krokan HE, Skorpen F, Elvestad MB, Hveem K, Vatten L, Linseisen J, Clavel-Chapelon F, Vineis P, Bueno-de-Mesquita HB, Lund E, Martinez C, Bingham S, Rasmuson T, Hainaut P, Riboli E, Ahrens W, Benhamou S, Lagiou P, Trichopoulos D, Holcátová I, Merletti F, Kjaerheim K, Agudo A, Macfarlane G, Talamini R, Simonato L, Lowry R, Conway DI, Znaor A, Healy C, Zelenika D, Boland A, Delepine M, Foglio M, Lechner D, Matsuda F, Blanche H, Gut I, Heath S, Lathrop M, Brennan P. 2008. A susceptibility locus for lung cancer maps to nicotinic acetylcholine receptor subunit genes on 15q25. Nature 452: 633-637.
14. Huelsenbeck JP, Andolfatto P. 2007. Inference of population structure under a Dirichlet process model. Genetics 175: 1787-1802.
15. Ishwaran H, James L. 2001. Gibbs sampling methods for stick-breaking priors. J Am Stat Assoc 96: 161-173.
16. Jain S, Neal R. 2004. A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model. J Comput Graph Stat 13: 158-182.
17. Jain S, Neal R. 2007. Splitting and merging components of a nonconjugate Dirichlet process mixture model. Bayesian Anal 2: 445-472.
18. Kim S, Tadesse M, Vannuci M. 2006. Variable selection in clustering via Dirichlet process mixture models. Biometrika 93: 877-893.
19. Kim S, Dahl DB, Vannucci M. 2009. Spiked Dirichlet process prior for Bayesian multiple hypothesis testing in random effects models. Bayesian Anal 4: 707-732.
20. MacEachern SN, Muller P. 1998. Estimating mixture of Dirichlet process models. J Comput Graph Stat 7: 223-238.
21. Molitor J, Papathomas M, Jerrett M, Richardson S. 2010. Bayesian profile regression with an application to the National Survey of Children's Health. Biostatistics 11: 484-498.
22. Moore JH. 2010. Detecting, characterizing, and interpreting nonlinear gene-gene interactions using multifactor dimensionality reduction. Adv Genet 72: 101-116.
23. Müller P, Quintana F. 2010. Random partition models with regression on covariates. J Statist Plann Inference 140: 2801-2808.
24. Papaspiliopoulos O, Roberts GO. 2008. Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models. Biometrika 95: 169-186.
25. Papathomas M, Molitor J, Riboli E, Richardson S, Vineis P. 2011. Examining the joint effect of multiple risk factors using exposure risk profiles: lung cancer in non-smokers. Environ Health Perspect 119: 84-91.
26. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. 2006. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38: 904-909.
27. Reich BJ, Bondell HD. 2011. A spatial Dirichlet process mixture model for clustering population genetics data. Biometrics 67: 381-390.
28. Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, Moore JH. 2001. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet 69: 138-147.
29. Schwartz AG, Cote ML, Wenzlaff AS, Land S, Amos CI. 2009. Racial differences in the association between SNPs on 15q25.1, smoking behavior, and risk of non-small cell lung cancer. J Thorac Oncol 4: 1195-1201.
30. Sinha S, Mallick BK, Kipnis V, Carroll RJ. 2010. Semiparametric Bayesian analysis of nutritional epidemiology data in the presence of measurement error. Biometrics 66: 444-454.
31. Speigelhalter D, Thomas A, Best N. 2003. WinBUGS User Manual 1.4. Cambridge: MRC Biostatistics Unit.
32. Tadesse M, Sha N, Vannucci M. 2005. Bayesian variable selection in clustering high-dimensional data. J Am Stat Assoc 100: 602-617.
33. Tibshirani R. 1996. Regression shrinkage and selection via the Lasso. J R Stat Soc B 58: 267-288.
34. Wakefield J, De Vocht F, Hung RJ. 2010. Bayesian mixture modelling of gene-environment and gene-gene interactions. Genet Epidemiol 34: 16-25.
35. Walker S, Damien P, Laud P, Smith A. 1999. Bayesian nonparametric inference for random distributions and related functions (with discussion). J R Statist Soc B 61: 485-527.
36. Walker SG. 2007. Sampling the Dirichlet mixture model with slices. Comm Stat Simulat Comput 36: 45-54.
37. Wang Y, Broderick P, Webb E, Wu X, Vijayakrishnan J, Matakidou A, Qureshi M, Dong Q, Gu X, Chen WV, Spitz MR, Eisen T, Amos CI, Houlston RS. 2008. Common 5p15.33 and 6p21.33 variants influence lung cancer risk. Nat Genet 40: 1407-1409.
38. Wang L, Dunson DB. 2011. Fast Bayesian inference in Dirichlet process mixture models. J Comput Graph Stat 20: 196-216.
39. Xun WW, Brennan P, Tjonneland A, Vogel U, Overvad K, Kaaks R, Canzian F, Boeing H, Trichopoulou A, Oustoglou E, Giotaki Z, Johansson M, Palli D, Agnoli C, Tumino R, Sacerdote C, Panico S, Bueno-de-Mesquita HB, Peeters PHM, Lund E, Kumle M, Rodriguez L, Agudo A, Sanchez M-J, Arriola L, Chirlaque M-D, Barricarte A, Hallmans G, Rasmuson T, Khaw K-T, Wareham N, Key T, Riboli E, Vineis P. 2011. Single-nucleotide polymorphisms (5p15.33, 15q25.1, 6p22.1, 6q27 and 7p15.3) and lung cancer survival in the European Prospective Investigation into Cancer and Nutrition (EPIC). Mutagenesis 26: 657-666.
40. Yau C, Holmes C. 2011. Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination. Bayesian Anal 6: 329-352.
41. Yau C, Papaspiliopoulos O, Roberts GO, Holmes C. 2011. Bayesian non-parametric hidden Markov models with applications in genomics. J R Statist Soc B 73: 37-57.
42. Zhang W, Zhu J, Schadt EE, Liu JS. 2010. A Bayesian partition method for detecting Pleiotropic and Epistatic eQTL modules. PLoS Comput Biol 6: 1-10.
43. Ziegler A, König IR. 2010. A Statistical Approach to Genetic Epidemiology. Weinheim: Wiley-VCH Verlag GmbH & Co. KGaA.