Bayesian modeling of ChIP-chip data using latent variables

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Wu, Mingqi ^a   Liang, Faming ^a   Tian, Yanan ^b  

^a TEXAS A AND M UNIVERSITY   (United States)

^b TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN HIERARCHICAL MODEL; DECONVOLUTION MODELS; HISTONE MODIFICATION; HUMAN TRANSCRIPTION FACTORS; INDICATOR VARIABLES; MODEL-BASED METHOD; POSTERIOR DISTRIBUTIONS; SLIDING WINDOW METHODS;

BAYESIAN NETWORKS; HIDDEN MARKOV MODELS; HIERARCHICAL SYSTEMS; NUMERICAL METHODS; POISSON DISTRIBUTION; PROBES; STATISTICS;

COMPUTER SIMULATION;

ESTROGEN RECEPTOR; PROTEIN P53;

ARTICLE; BACTERIAL ARTIFICIAL CHROMOSOME; BAYES THEOREM; CHROMATIN IMMUNOPRECIPITATION; HIDDEN MARKOV MODEL; MATHEMATICAL MODEL; MICROARRAY ANALYSIS; POISSON DISTRIBUTION; SIMULATION; AUTOMATED PATTERN RECOGNITION; BIOLOGY; GENE EXPRESSION PROFILING; METHODOLOGY;

ANIMALIA;

BAYES THEOREM; CHROMATIN IMMUNOPRECIPITATION; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; PATTERN RECOGNITION, AUTOMATED; POISSON DISTRIBUTION;

EID: 71049155879     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-352     Document Type: Article

References (35)

1. Cawley S, Bekiranov S, Ng HH, Kapranov P, Sekinger EA, Kampa D, Piccolboni A, Sementchenko V, Cheng J, Williams AJ, Wheeler R, Wong B, Drenkow J, Yamanaka M, Patel S, Brubaker S, Tammana H, Helt G, Struhl K, R GT. Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 2004, 116:499-509. 10.1016/S0092-8674(04)00127-8, 14980218.
2. Zhang X, Yazakij J, Sundaresan A, Cokus S, Chan S, Chen H, Henderson IR, Shinn P, Pellegrini M, Jacobsen SE, Ecker JR. Genome-wide high-resolution mapping and functional analysis of DNA methylation in arabidopsis. Cell 2006, 126:1189-1201. 10.1016/j.cell.2006.08.003, 16949657.
3. Bernstein BE, Kamal M, Lindblad-Toh K, Bekiranov S, Bailey D, Huebert DJ, McMahon S, Karlsson EK, III EJK, Gingeras TR, Schreiber SL, Lander ES. Genomic maps and comparative analysis of histone modifications in human and mouse. Cell 2005, 120:169-181. 10.1016/j.cell.2005.01.001, 15680324.
4. Zhang X, Clarenz O, Cokus S, Bernatavichute YV, Goodrich J, Jacobsen SE. Whole-Genome analysis of histone H3 lysine 27 trimethylation in arabidopsis. PLoS Biol 2007, 5(5):e129. 1852588,1852588, 17439305, 10.1371/journal.pbio.0050129.
5. Bertone P, Stolc V, Royce TE, Rozowsky JS, Urban AE, Zhu X, Rinn JL, Tongprasit W, Samanta M, Weissman S, gerstein M, Snyder M. Global identification of human transcribed sequences with genome tiling arrays. Science 2004, 306(5750):2242-2246. 10.1126/science.1103388, 15539566.
6. Ji H, Wong WH. TileMap: create chromosomal map of tiling array hybridizations. Bioinformatics 2005, 21(18):3629-3636. 10.1093/bioinformatics/bti593, 16046496.
7. Keles S, Laan MJ, Dudoit S, Cawley SE. Multiple testing methods for ChIP-chip high density oligonucleotide array data. Journal of Computational Biology 2006, 13(3):579-613. 10.1089/cmb.2006.13.579, 16706714.
8. Li W, Meyer CA, Liu XS. A hidden markov model for analayzing ChIP-chip experiments on genome tiling arrays and its application to p53 binding sequences. Bioinformatics 2005, 21(Suppl 1):274-282.
9. Munch K, Gardner PP, Arctander P, Krogh A. A hidden markov model approach for determining expression from genomic tiling microarrays. BMC Bioinformatics 2006, 7:239. 1481622, 16672042, 10.1186/1471-2105-7-239.
10. Humburg P, Bulger D, Stone G. Parameter estimation for robust HMM analysis of ChIP-chip data. BMC Bioinformatics 2008, 9:343. 2536674, 18706106, 10.1186/1471-2105-9-343.
11. Qi Y, Rolfe A, MacIsaac KD, Gerber GK, Pokholok D, Zeitlinger J, Danford T, Dowell RD, Fraenkel E, Jaakkola TS, Young RA, Gifford DK. High-Resolution computational models of genome binding events. Nature Biotechnology 2006, 24(8):963-970. 10.1038/nbt1233, 16900145.
12. Keles S. Mixture modeling for genome-wide localization of transcription factors. Biometrics 2007, 63:10-21. 10.1111/j.1541-0420.2005.00659.x, 17447925.
13. Gottardo R, Li W, Johnson WE, Liu XS. A flexible and powerful bayesian hierarchical model for ChIP-chip experiments. Biometrics 2008, 64:468-478. 10.1111/j.1541-0420.2007.00899.x, 17888037.
14. Zheng M, Barrera LO, Ren B, Wu YN. ChIP-chip: data, model, and analysis. Biometrics 2007, 63(3):787-796. 10.1111/j.1541-0420.2007.00768.x, 17825010.
15. Huber W, Toedling J, Steinmetz LM. Transcript mapping with high-density oligonucleotide tiling arrays. Bioinformatics 2006, 22(16):1963-1970. 10.1093/bioinformatics/btl289, 16787969.
16. Reiss DJ, Facciotti MT, Baliga NS. Model-based deconvolution of genome-wide DNA binding. Bioinformatics 2008, 24(3):396-403. 10.1093/bioinformatics/btm592, 18056063.
17. Rabiner LR. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE 1989, 77:257-286.
18. Besag J, Kooperberg C. On conditional and intrinsic autoregrssions. Biometrika 1995, 82:733-746.
19. Opgen-Rhein R, Strimmer K. Accurate ranking of differentially expressed genes by a distribution-free shrinkage approach. Statistical Applications in Genetics and Molecular Biology 2007, 6. Article 9.
20. Phillips DB, Smith AFM. Bayesian model comparison via jump diffusions. Markov chain Monte Carlo in Practice 1996, 215-239. Chapman and Hall, Gilks WR, Richardson S, Spiegel-halter DJ.
21. Denison DG, Mallick BK, Smith AFM. Automatic Bayesian curve fitting. J Royal Statist Soc B 1998, 60:333-350.
22. Liang F, Wong WH. Evolutionary Monte Carlo sampling: applications to Cp model sampling and change-point problem. Statistica Sinica 2000, 10:317-342.
23. Liang F. Improving SAMC using smoothing methods: theory and applications to bayesian model selection problems. The Annals of Statistics 2009, 37:2626-2654.
24. Müller P. A generic approach to posterior integration and gibbs sampling. Technical Report 1991, 09. Purdue University, West Lafayette, Indiana.
25. Efron B. Large-scale simultaneous hypothesis testing:the choice of a null hypothesis. Journal of the American Statistical Association 2004, 99:96-104.
26. Liang F, Zhang J. Estimation the false discovery rate using the stochastic approximation algorithm. Biometrika 2008, 95(4):961-977.
27. Carroll JS, Liu XS, Brodsky AS, Li W, Meyer CA, Szary AJ, Shao W, Hestermann EV, Geistlinger TR, Fox EA, Silver PA, Brown M. Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein foxal. Cell 2005, 122:33-43. 10.1016/j.cell.2005.05.008, 16009131.
28. BAC software. , http://www.bioconductor.org/packages/2.2/bioc
29. Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences (with discussion). Statistical Science 1992, 7:457-511.
30. BAC and tileHMM software. , http://cran.r-project. org/web/packages
31. Rand WM. Objective criteria for the evaluation of clustering methods. Journal of the American Statistical Association 1971, 66:846-850.
32. Hubert L, Arabie P. Comparing partitions. Journal of Classification 1985, 2:193-218.
33. Bolstad BM, Irizarry RA, Astrand M, Speed TP. A comparison of normalization methods for high density ologonucleotide array data based on variance and bias. Bioinformatics 2003, 19:185-193. 10.1093/bioinformatics/19.2.185, 12538238.
34. Bradley A. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition 1997, 30:1145-1159.
35. R package: LatentChIP. , http://www.stat.tamu.edu/~fliang