A model selection approach for the identification of quantitative trait loci in experimental crosses

Journal of the Royal Statistical Society. Series B: Statistical Methodology

Volumn 64, Issue 4, 2002, Pages 641-656

  Broman, Karl W ^a   Speed, Terence P ^b,c  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c WALTER AND ELIZA HALL INSTITUTE OF MEDICAL RESEARCH   (Australia)

Author keywords

Bayesian information criterion; Composite interval mapping; Markov chain Monte Carlo methods; Model selection; Quantitative trait loci; Regression

Indexed keywords

EID: 0036433546     PISSN: 13697412     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9868.00354     Document Type: Article

References (34)

1. Akaike, H. (1969) Fitting autoregressive models for prediction. Ann. Inst. Statist. Math., 21, 243-247.
2. An, H. and Gu, L. (1985) On the selection of regression variables. Acta Math. Appl. Sin., 2, 27-36.
3. Ball, R.D. (2001) Bayesian methods for quantitative trait loci mapping based on model selection: approximate analysis using the Bayesian information criterion. Genetics, 159, 1351-1364.
4. Basten, C.J., Weir, B.S. and Zeng, Z.-B. (2000) QTL Cartographer, Version 1.14. Raleigh: North Carolina State University.
5. Broman, K.W. (1997) Identifying quantitative trait loci in experimental crosses. PhD Dissertation. Department of Statistics, University of California, Berkeley.
6. Broman, K.W. and Speed, T.P. (1999) A review of methods for identifying QTLs in experimental crosses. IMS Lect. Notes Monogr. Ser., 33, 114-142.
7. Carlborg, O., Andersson, L. and Kinghorn, B. (2000) The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci. Genetics, 155, 2003-2010.
8. Churchill, G.A. and Doerge, R.W. (1994) Empirical threshold values for quantitative trait mapping. Genetics, 138, 963-971.
9. Cowen, N.M. (1989) Multiple linear regression analysis of RFLP data sets used in mapping QTLs. In Development and Application of Molecular Markers to Problems in Plant Genetics (eds T Helentjaris and B. Burr), pp. 113-116. Cold Spring Harbor: Cold Spring Harbor Laboratory.
10. Dempster, A.P., Laird, N.M. and Rubin, D.B. (1977) Maximum likelihood from incomplete data via the EM algorithm (with discussion). J. R. Statist. Soc. B, 39, 1-38.
11. Doerge, R.W. and Churchill, G.A. (1996) Permutation tests for multiple loci affecting a quantitative character. Genetics, 142, 285-294.
12. Doerge, R.W., Zeng, Z.-B. and Weir, B.S. (1997) Statistical issues in the search for genes affecting quantitative traits in experimental populations. Statist. Sci., 12, 195-219.
13. Frankel, W.N. and Schork, N.J. (1996) Who's afraid of epistasis? Nat. Genet., 14, 371-373.
14. Hannan, E.J. and Quinn, B.G. (1979) The determination of the order of an autoregression. J. R. Statist. Soc. B, 41, 190-195.
15. Jansen, R.C. (1993) Interval mapping of multiple quantitative trait loci. Genetics, 135, 205-211.
16. Jansen, R.C. and Stam, P. (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics, 136, 1447-1455.
17. Kao, C.-H., Zeng, Z.-B. and Teasdale, R.D. (1999) Multiple interval mapping for quantitative trait loci. Genetics, 152, 1203-1216.
18. Lander, E.S. and Botstein, D. (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 121, 185-199.
19. Lynch, M. and Walsh, B. (1998) Genetics and Analysis of Quantitative Traits, ch. 15. Sunderland: Sinauer.
20. Miller, A.J. (1990) Subset Selection in Regression. New York: Chapman and Hall.
21. Rao, C.R. and Wu, Y. (1989) A strongly consistent procedure for model selection in a regression problem. Biometrika, 76, 369-374.
22. Roberts, L.J., Baldwin, T.M., Speed, T.P., Handman, E. and Foote, S.J. (1999) Chromosomes X, 9, and the H2 locus interact epistatically to control Leishmania major infection. Eur. J. Immunol., 29, 3047-3050.
23. Satagopan, J.M., Yandell, B.S., Newton, M.A. and Osbom, T.C. (1996) A Bayesian approach to detect quantitative trait loci using Markov chain Monte Carlo. Genetics, 144, 805-816.
24. Schwarz, G. (1978) Estimating the dimension of a model. Ann. Statist., 6, 461-464.
25. Sen, Ś. and Churchill, G.A. (2001) A statistical framework for quantitative trait mapping. Genetics, 159, 371-387.
26. Shimomura, K., Low-Zeddies, S.S., King, D.P., Steeves, T.D., Whiteley, A., Kushla, J., Zemenides, P.D., Lin, A., Vitaterna, M.H., Churchill, G.A. and Takahashi, J.S. (2001) Genome-wide epistatic interaction analysis reveals complex genetic determinants of circadian behavior in mice. Genome Res., 11, 959-980.
27. Shrimpton, A.E. and Robertson, A. (1988) The isolation of polygenic factors controlling bristle score in Drosophila melanogaster: I, Allocation of third chromosome sternopleural bristle effects to chromosome sections. Genetics, 118, 437-443.
28. Sillanpää, M.J. and Arias, E. (1998) Bayesian mapping of multiple quantitative trait loci from incomplete inbred line cross data. Genetics, 148, 1373-1388.
29. Smith, M.S. (1996) Nonparametric regression: a Markov chain Monte Carlo approach. PhD Dissertation. University of New South Wales, Sydney.
30. Soller, M., Brody, T. and Genizi, A. (1976) On the power of experimental designs for the detection of linkage between marker loci and quantitative loci in crosses between inbred lines. Theoret. Appl. Genet., 47, 35-39.
31. Whittaker, J.C., Curnow, R.N., Haley, C.S. and Thompson, R. (1995) Using marker-maps in marker-assisted selection. Genet. Res., 66, 255-265.
32. Zeng, Z.-B. (1993) Theoretical basis for separation of multiple linked gene effects in mapping quantitative trait loci. Proc. Natn. Acad. Sci. USA, 90, 10972-10976.
33. _(1994) Precision mapping of quantitative trait loci. Genetics, 136, 1457-1468.
34. Zeng, Z.-B., Kao, C.-H. and Basten, C.J. (1999) Estimating the genetic architecture of quantitative traits. Genet. Res., 74, 279-289.