Bayesian mixture models for complex high dimensional count data in phage display experiments

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 56, Issue 2, 2007, Pages 139-152

  Ji, Yuan ^a   Yin, Guosheng ^a   Tsui, Kam Wah ^b   Kolonin, Mikhail G ^a   Sun, Jessica ^a   Arap, Wadih ^a   Pasqualini, Renata ^a   Do, Kim Anh ^a  

^a UNIVERSITY OF TEXAS   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Bayesian inference; Gibbs sampler; Markov chain Monte Carlo simulation; Metropolis hastings algorithm; Peptide

Indexed keywords

EID: 33947690149     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2007.00570.x     Document Type: Article

References (20)

1. Agresti, A. (2002) Categorical Data Analysis, 2nd edn. New York: Wiley.
2. Albert, J. (1997) Bayesian testing and estimation of association in a two-way contingency table. J. Am. Statist. Ass., 92, 685-693.
3. Arap, W., Kolonin, M. G., Trepel, M., Lahdenranta, J., Cardo-Vila, M., Giordano, R. J., Mintz, P. J., Ardelt, P. U., Yao, V. J., Vidai, C. I., Chen, L., Flamm, A., Valtanen, H., Weavind, L. M., Hicks, M. E., Pollock, R. E., Botz, G. H., Bucana, C. D., Koivunen, E., Cahill, D., Troncoso, P., Baggerly, K. A., Pentz, R. D., Do, K.-A., Logothetis, C. J. and Pasqualini, R. (2002) Steps toward mapping the human vasculature by phage display. Nat. Med., 8, 121-127.
4. Carlin, B. and Louis, T. (2000) Bayes and Empirical Bayes Methods for Data Analysis, 2nd edn. Boca Raton: Chapman and Hall-CRC.
5. Clackson, T. and Lowman, H. (2004) Phage Display - a Practical Approach, Oxford: Oxford University Press.
6. Cowles, M. and Carlin, B. (1996) Markov chain Monte Carlo convergence diagnostics: a comparative review. J. Am. Statist. Ass., 91, 883-904.
7. Geman, S. and Geman, D. (1984) Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Pattn Anal. Mach. Intell., 6, 721-741.
8. Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (eds) (1996) Markov Chain Monte Carlo in Practice. Boca Raton: Chapman and Hall-CRC.
9. Hastings, W. (1970) Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97-109.
10. Kolonin, M., Sun, I. Do, K.-A., Vidai, C., Ji, Y., Baggerly, K., Pasqualini, R. and Arap, W. (2006) Synchronized selection of homing peptides for multiple tissues with in vivo phage display. FASEB J., 20, 979-981.
11. Leonard, T. and Hsu, J. (1999) Bayesian Methods: an Analysis for Statisticians and Interdisciplinary Researchers. Cambridge: Cambridge University Press.
12. McLachlan, G. and Peel, D. (2000) Finite Mixture Models. New York: Wiley.
13. Metropolis, N., Rosenbluth, A., Rosenbluth, M., Teller, A. and Teller, E. (1953) Equations of state calculations by fast computing machines. J. Chem. Phys., 21, 1087-1091.
14. Müller, P., Parmigiani, G., Robert, C. and Rousseau, J. (2004) Optimal sample size for multiple testing: the case of gene expression microarrays. J. Am. Statist. Ass., 99, 990-1001.
15. Newton, M., Noueiry, A., Sarkar, D. and Ahlquist, P. (2004) Detecting differential gene expression with a semiparametric hierarchical mixture method. Biostatistics, 5, 155-176.
16. Nowakowski, G., Donner, M., Valinski, H., Mihaliak, A., Quesenberry, P. and Becker, P. (2004) A specific heptapeptide from a phage display peptide library homes to bone marrow and binds to primitive hematopoietic stem cells. Stem Cells, 22, 1030-1038.
17. Pasqualini, R. and Ruoslahti, E. (1996) Organ targeting in vivo using phage display peptide libraries. Nature, 380, 364-366.
18. Raftery, A. E. (1986) A note on Bayes factors for log-linear contingency table models with vague prior information. J. R. Statist. Soc. B, 48, 249-250.
19. Spiegelhalter, D. J. and Smith, A. F. M. (1982) Bayes factors for linear and log-linear models with vague prior information. J. R. Statist. Soc. B, 44, 377-387.
20. Wasserman, L. (2000) Asymptotic inference for mixture models using data-dependent priors. J. R. Statist. Soc. B. 62, 159-180.