Genetic analysis of complex traits via Bayesian variable selection: The utility of a mixture of uniform priors

Genetics Research

Volumn 93, Issue 4, 2011, Pages 303-318

  Knürr, Timo ^a   Läärä, Esa ^b   Sillanpää, Mikko J ^a,b  

^a UNIVERSITY OF HELSINKI   (Finland)

^b UNIVERSITY OF OULU   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER PROGRAM; GENETIC ANALYSIS; GENETIC TRAIT; HEREDITY; STATISTICAL ANALYSIS;

ALGORITHMS; BAYES THEOREM; CHROMOSOME MAPPING; CYSTIC FIBROSIS; GENETICS, POPULATION; HORDEUM; HUMANS; MARKOV CHAINS; MODELS, GENETIC; MONTE CARLO METHOD; QUANTITATIVE TRAIT LOCI; SELECTION, GENETIC;

EID: 80054880644     PISSN: 00166723     EISSN: 14695073     Source Type: Journal    
DOI: 10.1017/S0016672311000164     Document Type: Article

References (54)

1. Altman, D. G. & Bland, J. M. (1983). Measurement in medicine: the analysis of method comparison studies. Journal of the Royal Statistical Society - Series D: The Statistician 32, 307-317.
2. Andrews, D. F. & Mallows, C. L. (1974). Scale mixtures of normal distributions. Journal of the Royal Statistical Society - Series B: Statistical Methodology 36, 99-102.
3. Ball, R. D. (2007). Quantifying evidence for candidate gene polymorphisms: Bayesian analysis combining sequence-specific and quantitative trait loci colocation information. Genetics 177, 2399-2416. (Pubitemid 350277014)
4. Beavis, W. D. (1998). QTL analysis: power, precision and accuracy. In: Molecular Dissection of Complex Traits, (ed. A. H. Paterson), pp. 145-162. Boca Raton, FL: CRC Press.
5. Berger, J. O. & Delampady, M. (1987). Testing precise hypotheses. Statistical Science 2, 317-335.
6. Berger, J. O. & Sellke, T. (1987). Testing a point null hypothesis: the irreconcilability of P values and evidence. Journal of the American Statistical Association 82, 112-122.
7. Bertranpetit, J. & Calafell, F. (1996). Genetic and geographical variability in cystic fibrosis: evolutionary considerations. In: Variation in the Human Genome, (ed. D. Chadwick & G. Cardew), pp. 97-114. Chichester, UK: John Wiley & Sons.
8. Broman, K. W. & Speed, T. P. (2002). A model selection approach for the identification of quantitative trait loci in experimental crosses. Journal of the Royal Statistical Society - Series B: Statistical Methodology 64, 641-656.
9. Fisher, R. A. (1918). The correlation between relatives on the supposition of Mendelian inheritance. Transactions of the Royal Society of Edinburgh 52, 399-433.
10. George, E. I. & McCulloch, R. E. (1993). Variable selection via Gibbs sampling. Journal of the American Statistical Association 88, 881-889.
11. Geyer, C. J. (1992). Practical Markov Chain Monte Carlo. Statistical Science 7, 473-483.
12. Gianola, D., de los Campos, G., Hill, W. G., Manfredi, E. & Fernando, R. (2009). Additive genetic variability and the Bayesian alphabet. Genetics 183, 347-363.
13. Hartl, D. L. & Clark, A. G. (2007). Principles of Population Genetics. 4th edn. Sunderland, MA: Sinauer Associates.
14. Hayashi, T. & Iwata, H. (2010). EM algorithm for Bayesian estimation of genomic breeding values. BMC Genetics 11, 3.
15. Hayes, B. & Goddard, M. E. (2001). The distribution of the effects of genes affecting quantitative traits in livestock. Genetics, Selection, Evolution 33, 209-229. (Pubitemid 32591810)
16. Hosmer, D. W. & Lemeshow, S. (1989). Applied Logistic Regression. New York: John Wiley & Sons.
17. Ioannidis, J. P. A. (2008). Effect of formal statistical significance on the credibility of observational associations. American Journal of Epidemiology 168, 374-383.
18. Jeffreys, H. (1961). Theory of Probability. 3rd edn. Oxford, UK: Clarendon Press.
19. Kass, R. E. & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association 90, 773-795.
20. Kerem, B.-S., Rommens, J. M., Buchanan, J. A., Markiewicz, D., Cox, T. K., Chakravarti, A., Buchwald, M. & Tsui, L.-C. (1989). Identification of the cystic fibrosis gene: genetic analysis. Science 245, 1073-1080. (Pubitemid 19231815)
21. Kuo, L. & Mallick, B. (1998). Variable selection for regression models. Sankhya: The Indian Journal of Statistics Series B 60, 65-81.
22. Lande, R. & Thompson, R. (1990). Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124, 743-756. (Pubitemid 20106345)
23. Lazzeroni, L. C. (1998). Linkage disequilibrium and gene mapping: an empirical least-squares approach. American Journal of Human Genetics 62, 159-170. (Pubitemid 28093845)
24. Lee, J. K. & Thomas, D. C. (2000). Performance of Markov Chain Monte Carlo approaches for mapping genes in oligogenic models with an unknown number of loci. American Journal of Human Genetics 67, 1232-1250.
25. Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S. & Hirschhorn, J. N. (2003). Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nature Genetics 33, 177-182. (Pubitemid 36177070)
26. Mackay, T. F. C. (1996). The nature of quantitative genetic variation revisited: lessons from Drosophila bristles. BioEssays 18, 113-121.
27. Mackay, T. F. C. (2001). The genetic architecture of quantitative traits. Annual Review of Genetics 35, 303-339.
28. McCarthy, M. I. & Hirschhorn, J. N. (2008). Genome-wide association studies: potential next steps on a genetic journey. Human Molecular Genetics 17, R156-R165.
29. Meuwissen, T. H. E. & Goddard, M. E. (2004). Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data. Genetics, Selection, Evolution 36, 261-279. (Pubitemid 38630134)
30. Meuwissen, T. H. E., Hayes, B. J. & Goddard, M. E. (2001). Prediction of total genetic value using genome-wide dense marker maps. Genetics 157, 1819-1829. (Pubitemid 32298846)
31. Meuwissen, T. H. E., Solberg, T. R., Shepherd, R. & Woolliams, J. A. (2009). A fast algorithm for Bayes B type of prediction of genome-wide estimates of genetic value. Genetics, Selection, Evolution 41, 2.
32. Miller, A. (2002). Subset Selection in Regression. 2nd edn. Boca Raton, FL: Chapman & Hall/CRC.
33. Molitor, J., Marjoram, P. & Thomas, D. (2003). Application of Bayesian spatial statistical methods to analysis of haplotype effects and gene mapping. Genetic Epidemiology 25, 95-105. (Pubitemid 37064865)
34. O'Hara, R. B. & Sillanpaa, M. J. (2009). A review of Bayesian variable selection methods: what, how and which. Bayesian Analysis 4, 85-118.
35. Otto, S. P. & Jones, C. D. (2000). Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 156, 2093-2107. (Pubitemid 32001266)
36. Pikkuhookana, P. & Sillanpaa, M. J. (2009). Correcting for relatedness in Bayesian models for genomic data association analysis. Heredity 103, 223-237.
37. Robertson, A. (1967). The nature of quantitative genetic variation. In: Heritage from Mendel (ed. A. Brink) pp. 265-280. Madison, WI: The University of Wisconsin Press.
38. Sasieni, P. D. (1997). Genotypes to genes: doubling the sample size. Biometrics 53, 1253-1261. (Pubitemid 28013569)
39. Satagopan, J. M., Yandell, B. S., Newton, M. A. & Osborn, T. C. (1996). A Bayesin approach to detect quantitative trait loci using Markov Chain Monte Carlo. Genetics 144, 805-816. (Pubitemid 26325871)
40. Sillanpaa, M. J. & Bhattacharjee, M. (2005). Bayesian association-based fine mapping in small chromosomal segments. Genetics 169, 427-439. (Pubitemid 40239182)
41. Sillanpaa, M. J. & Bhattacharjee, M. (2006). Association mapping of complex trait loci with context-dependent effects and unknown context variable. Genetics 174, 1597-1611. (Pubitemid 44808326)
42. Sillanpaa, M. J. & Corander, J. (2002). Model choice in gene mapping: what and why. Trends in Genetics 18, 301-307. (Pubitemid 34607120)
43. Thomas, A., O'Hara, B., Ligges, U. & Sturtz, S. (2006). Making BUGS open. R News 6/1, 12-17.
44. Tinker, N. A., Mather, D. E., Rossnagel, B. G., Kasha, K. J., Kleinhofs, A., Hayes, P. M., Falk, D. E., Ferguson, T., Shugar, L. P., Legge, W. G., Irvine, R. B., Choo, T. M., Briggs, K. G., Ullrich, S. E., Franckowiak, J. D., Blake, T. K., Graf, R. J., Dofing, S. M., Saghai Maroof, M. A., Scoles, G. J., Hoffman, D., Dahleen, L. S., Kilian, A., Chen, F., Biyashev, R. M., Kudrna, D. A. & Steffenson, B. J. (1996). Regions of the genome that affect agronomic performance in two-row barley. Crop Science 36, 1053-1062. (Pubitemid 26406977)
45. Verbyla, K. L., Bowman, P. J., Hayes, B. J. & Goddard, M. E. (2010). Sensitivity of genomic selection to using different prior distributions. BMC Proceedings 4(Suppl 1), S5.
46. Waagepetersen, R., Ibanez-Escriche, N. & Sorensen, D. (2008). A comparison of strategies for Markov Chain Monte Carlo computation in quantitative genetics. Genetics, Selection, Evolution 40, 161-176. (Pubitemid 351317198)
47. Wakefield, J. (2008). Reporting and interpretation in genome-wide association studies. International Journal of Epidemiology 37, 641-653. (Pubitemid 351804020)
48. Wakefield, J. (2009). Bayes factors for genome-wide association studies: comparison with P-values. Genetic Epidemiology 33, 79-86.
49. Xiao, R. & Boehnke, M. (2009). Quantifying and correcting for the winner's curse in genetic association studies. Genetic Epidemiology 33, 453-462.
50. Xu, S. (2003a). Estimating polygenic effects using markers of the entire genome. Genetics 163, 789-801. (Pubitemid 36314558)
51. Xu, S. (2003b). Theoretical basis of the Beavis effect. Genetics 165, 2259-2268. (Pubitemid 38040305)
52. Xu, S. (2010). An expectation-maximization algorithm for the Lasso estimation of quantitative trait locus effects. Heredity 105, 483-494.
53. Yi, N. & Banerjee, S. (2009). Hierarchical generalized linear models for multiple quantitative trait locus mapping. Genetics 181, 1101-1113.
54. Yi, N. & Xu, S. (2008). Bayesian LASSO for quantitative trait loci mapping. Genetics 179, 1045-1055.