Searching for recursive causal structures in multivariate quantitative genetics mixed models

Genetics

Volumn 185, Issue 2, 2010, Pages 633-644

  Valente, Bruno D ^a,b   Rosa, Guilherme J M ^b,c   De Los Campos, Gustavo ^b   Gianola, Daniel ^b,c   Silva, Martinho A ^a  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

^c UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; GENETIC MODEL; PHENOTYPE; PRIORITY JOURNAL; QUANTITATIVE GENETICS; STRUCTURAL EQUATION MODELING; ALGORITHM; FACTORIAL ANALYSIS; HUMAN; MULTIVARIATE ANALYSIS;

ALGORITHMS; BAYES THEOREM; FACTOR ANALYSIS, STATISTICAL; HUMANS; MULTIVARIATE ANALYSIS; PHENOTYPE;

EID: 77955492575     PISSN: 00166731     EISSN: 00166731     Source Type: Journal    
DOI: 10.1534/genetics.109.112979     Document Type: Article

References (30)

1. AKAIKE, H., 1973 Information theory and an extension of the maximum likelihood principle, pp. 267-291 in 2nd International Symposium on Information Theory, edited by B. N. PETROV and F. CSAKI. Publishing House of the Hungarian Academy of Sciences, Budapest.
2. ATEN, J. E., T. F. FULLER, A. J. LUSIS and S. HORVATH, 2008 Using genetic markers to orient the edges in quantitative trait networks: the NEO software. BMC Syst. Biol. 2: 34.
3. CHAIBUB NETO, E., T. C. FERRARA, A. D. ATTIE and B. S. YANDELL, 2008 Inferring causal phenotype networks from segregating populations. Genetics 179: 1089-1100.
4. CHEN, L. S., F. EMMERT-STREIB and J. D. STOREY, 2007 Harnessing naturally randomized transcription to infer regulatory relationships among genes. Genome Biol. 8: R219.
5. DE LOS CAMPOS, G., D. GIANOLA, P. BOETTCHER and P. MORONI, 2006a A structural equation model for describing relationships between somatic cell score and milk yield in dairy goats. J. Anim. Sci. 84: 2934-2941.
6. DE LOS CAMPOS, G., D. GIANOLA and B. HERINGSTAD, 2006b A structural equation model for describing relationships between somatic cell score and milk yield in first-lactation dairy cows. J. Dairy Sci. 89: 4445-4455. (Pubitemid 44682946)
7. DE MATURANA, E. L., X. L. WU, D. GIANOLA, K. A. WEIGEL and G. J. M. ROSA, 2009 Exploring biological relationships between calving traits in primiparous cattle with a Bayesian recursive model. Genetics 181: 277-287.
8. GEMAN, S., and D. GEMAN, 1984 Stochastic relaxation, Gibbs distributions and Bayesian restoration of images. IEEE Trans. Patt. Anal. Mach. Intell. 6: 721-741.
9. GIANOLA, D., and D. SORENSEN, 2004 Quantitative genetic models for describing simultaneous and recursive relationships between phenotypes. Genetics 167: 1407-1424.
10. HAAVELMO, T., 1943 The statistical implications of a system of simultaneous equations. Econometrica 11: 1-12.
11. HERINGSTAD, B., X.-L. WU and D. GIANOLA, 2009 Inferring relationships between health and fertility in Norwegian red cows using recursive models. J. Dairy Sci. 92: 1778-1784.
12. KONIG, S., X. L. WU, D. GIANOLA, B. HERINGSTAD and H. SIMIANER, 2008 Exploration of relationships between claw disorders and milk yield in Holstein cows via recursive linear and threshold models. J. Dairy Sci. 91: 395-406.
13. LI, R., S. W. TSAIH, K. SHOCKLEY, I. M. STYLIANOU, J. WERGEDAL et al., 2006 Structural model analysis of multiple quantitative traits. PLoS Genet. 2: e114.
14. LIU, B., A. DE LA FUENTE and I. HOESCHELE, 2008 Gene network inference via structural equation modeling in genetical genomics experiments. Genetics 178: 1763-1776.
15. PEARL, J., 1988 Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kauffman, San Mateo, CA.
16. PEARL, J., 2000 Causality: Models, Reasoning and Inference. Cambridge University Press, Cambridge, UK.
17. R DEVELOPMENT CORE TEAM, 2008 R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. http://www.R-project.org.
18. RAFTERY, A. E., and S. LEWIS, 1992 How many iterations in the Gibbs sampler? pp. 763-773 in Bayesian Statistics IV, edited by J. M. BERNARDO, J. BERGER, A. P. DAWID and A. F. M. SMITH. Oxford University Press, Oxford.
19. SCHADT, E. E., J. LAMB, X. YANG, J. ZHU, S. EDWARDS et al., 2005 An integrative genomics approach to infer causal associations between gene expression and disease. Nat. Genet. 37: 710-717.
20. SCHWARZ, G., 1978 Estimating the dimension of a model. Ann. Stat. 6: 461-464.
21. SHIPLEY, B., 1997 Exploratory path analysis with applications in ecology and evolution. Am. Nat. 149: 1113-1138.
22. SHIPLEY, B., 2002 Cause and Correlation in Biology. Cambridge University Press, Cambridge, UK/London/New York.
23. SMITH, B. J., 2007 BOA: an R package for MCMC output convergence assessment and posterior inference. J. Stat. Softw. 21: 1-37.
24. SORENSEN, D., and D. GIANOLA, 2002 Likelihood, Bayesian and MCMC Methods in Quantitative Genetics. Springer-Verlag, New York.
25. SPIRTES, P., C. GLYMOUR and R. SCHEINES, 2000 Causation, Prediction and Search, Ed. 2. MIT Press, Cambridge, MA.
26. VARONA, L., D. SORENSEN and R. THOMPSON, 2007 Analysis of litter size and average litter weight in pigs using a recursive model. Genetics 177: 1791-1799. (Pubitemid 350277071)
27. VERMA, T., and J. PEARL, 1990 Equivalence and synthesis of causal models. Proceedings of the 6th Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, pp. 220-227. Elsevier, Amsterdam.
28. WRIGHT, S., 1921 Correlation and causation. J. Agric. Res. 201: 557-585.
29. WU, X.-L., B. HERINGSTAD, Y. M. CHANG, G. DE LOS CAMPOS and D. GIANOLA, 2007 Inferring relationships between somatic cell score and milk yield using simultaneous and recursive models. J. Dairy Sci. 90: 3508-3521.
30. WU, X.-L., B. HERINGSTAD and D. GIANOLA, 2010 Bayesian structural equation models for inferring relationships between phenotypes: a review of methodology, identifiability, and applications. J. Anim. Breed. Genet. 127: 3-15.