Identifying gene regulatory network rewiring using latent differential graphical models

Nucleic Acids Research

Volumn 44, Issue 17, 2016, Pages

  Tian, Dechao ^a,b   Gu, Quanquan ^c   Ma, Jian ^a,b,d  

^a United States of America   (United States)

^b Carnegie Mellon University ^*  (United States)

^c UNIVERSITY OF VIRGINIA   (United States)

^d UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BLOOD; BRAIN; BREAST CANCER; GENE EXPRESSION; GENE REGULATORY NETWORK; LATENT DIFFERENTIAL GRAPHICAL MODEL; MATHEMATICAL MODEL; PRIORITY JOURNAL; SIMULATION; AREA UNDER THE CURVE; BIOLOGICAL MODEL; BREAST TUMOR; COMPUTER GRAPHICS; COMPUTER SIMULATION; FEMALE; GENETIC DATABASE; GENETICS; HUMAN; MCF-7 CELL LINE; RECEIVER OPERATING CHARACTERISTIC; SIGNAL TRANSDUCTION;

AREA UNDER CURVE; BREAST NEOPLASMS; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATABASES, GENETIC; FEMALE; GENE REGULATORY NETWORKS; HUMANS; MCF-7 CELLS; MODELS, GENETIC; ROC CURVE; SIGNAL TRANSDUCTION;

EID: 84991270631     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkw581     Document Type: Article

References (42)

1. Ravasi, T., Suzuki, H., Cannistraci, C.V., Katayama, S., Bajic, V.B., Tan, K., Akalin, A., Schmeier, S., Kanamori-Katayama, M., Bertin, N. et al. (2010) An atlas of combinatorial transcriptional regulation in mouse and man. Cell, 140, 744-752.
2. Vaquerizas, J.M., Kummerfeld, S.K., Teichmann, S.A. and Luscombe, N.M. (2009) A census of human transcription factors: function, expression and evolution. Nat. Rev. Genet., 10, 252-263.
3. Davidson, E.H. (2006) The regulatory genome: gene regulatory networks in development and evolution. Academic Press, San Diego.
4. Neph, S., Stergachis, A.B., Reynolds, A., Sandstrom, R., Borenstein, E. and Stamatoyannopoulos, J.A. (2012) Circuitry and dynamics of human transcription factor regulatory networks. Cell, 150, 1274-1286.
5. Ardlie, K.G., Deluca, D.S., Segre, A.V., Sullivan, T.J., Young, T.R., Gelfand, E.T., Trowbridge, C.A., Maller, J.B., Tukiainen, T., Lek, M. et al. (2015) The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans. Science, 348, 648-660.
6. Melé, M., Ferreira, P.G., Reverter, F., DeLuca, D.S., Monlong, J., Sammeth, M., Young, T.R., Goldmann, J.M., Pervouchine, D.D., Sullivan, T.J. et al. (2015) The human transcriptome across tissues and individuals. Science, 348, 660-665.
7. Ideker, T. and Krogan, N.J. (2012) Differential network biology. Mol. Syst. Biol. 8, 565.
8. Mitra, K., Carvunis, A.-R., Ramesh, S.K. and Ideker, T. (2013) Integrative approaches for finding modular structure in biological networks. Nat. Rev. Genet., 14, 719-732.
9. Zhang, S., Tian, D., Tran, N.H., Choi, K.P. and Zhang, L. (2014) Profiling the transcription factor regulatory networks of human cell types. Nucleic Acids Res., 42, 12380-12387.
10. Vidal, M., Cusick, M.E. and Barabasi, A.-L. (2011) Interactome networks and human disease. Cell, 144, 986-998.
11. Lonsdale, J., Thomas, J., Salvatore, M., Phillips, R., Lo, E., Shad, S., Hasz, R., Walters, G., Garcia, F., Young, N. et al. (2013) The genotype-tissue expression (GTEx) project. Nat. Genet., 45, 580-585.
12. Dobra, A., Hans, C., Jones, B., Nevins, J.R., Yao, G. and West, M. (2004) Sparse graphical models for exploring gene expression data. J. Multivariate Anal., 90, 196-212.
13. Yuan, M. and Lin, Y. (2007) Model selection and estimation in the Gaussian graphical model. Biometrika, 94, 19-35.
14. Friedman, J., Hastie, T. and Tibshirani, R. (2008) Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9, 432-441.
15. Mohan, K., London, P., Fazel, M., Witten, D. and Lee, S.-I. (2014) Node-based learning of multiple gaussian graphical models. J. Mach. Learn. Res., 15, 445-488.
16. Danaher, P., Wang, P. and Witten, D.M. (2014) The joint graphical lasso for inverse covariance estimation across multiple classes. J. R. Stat. Soc. B, 76, 373-397.
17. Oshlack, A., Robinson, M.D., Young, M.D. et al. (2010) From RNA-seq reads to differential expression results. Genome Biol., 11, 220.
18. Li, P., Piao, Y., Shon, H.S. and Ryu, K.H. (2015) Comparing the normalization methods for the differential analysis of Illumina high-throughput RNA-Seq data. BMC Bioinform., 16, 1.
19. Liu, H., Lafferty, J. and Wasserman, L. (2009) The nonparanormal: Semiparametric estimation of high dimensional undirected graphs. J. Mach. Learn. Res., 10, 2295-2328.
20. Liu, H., Han, F., Yuan, M., Lafferty, J., Wasserman, L. et al. (2012) High-dimensional semiparametric Gaussian copula graphical models. Ann. Stat., 40, 2293-2326.
21. Greene, C.S., Krishnan, A., Wong, A.K., Ricciotti, E., Zelaya, R.A., Himmelstein, D.S., Zhang, R., Hartmann, B.M., Zaslavsky, E., Sealfon, S.C. et al. (2015) Understanding multicellular function and disease with human tissue-specific networks. Nat. Genet., 47, 569-576.
22. Pierson, E., Koller, D., Battle, A., Mostafavi, S., Consortium, G. et al. (2015) Sharing and specificity of co-expression networks across 35 human tissues. PLoS Comput. Biol., 13, e1004220.
23. Zhao, S.D., Cai, T.T. and Li, H. (2014) Direct estimation of differential networks. Biometrika, 101, 253-268.
24. Beck, A. and Teboulle, M. (2009) A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci., 2, 183-202.
25. Lauritzen, S.L. (1996) Graphical models, Oxford University Press, NY.
26. Van der Vaart, A.W. (2000) Asymptotic statistics. Cambridge University Press, ambridge, Vol. 3.
27. Cai, T., Liu, W. and Luo, X. (2011) A constrained l1 minimization approach to sparse precision matrix estimation. J. Am. Stat. Assoc., 106, 594-607.
28. Kruskal, W. (1958) Ordinal Measures of Association. , 53, 814-861.
29. Golub, G.H. and Van Loan, C.F. (2012) Matrix computations. Johns Hopkins University Press, London, Vol. 3.
30. Zhao, T., Liu, H., Roeder, K., Lafferty, J. and Wasserman, L. (2012) The huge package for high-dimensional undirected graph estimation in R. J. Mach. Learn. Res., 13, 1059-1062.
31. Barabasi, A.-L. and Albert, R. (1999) Emergence of scaling in random networks. Science, 286, 509-512.
32. Sørlie, T., Tibshirani, R., Parker, J., Hastie, T., Marron, J., Nobel, A., Deng, S., Johnsen, H., Pesich, R., Geisler, S. et al. (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. U.S.A., 100, 8418-8423.
33. Ma, C.X., Reinert, T., Chmielewska, I. and Ellis, M.J. (2015) Mechanisms of aromatase inhibitor resistance. Nat. Rev. Cancer, 15, 261-275.
34. Rakha, E.A., Reis-Filho, J.S. and Ellis, I.O. (2008) Basal-like breast cancer: a critical review. J. Clin. Oncol., 26, 2568-2581.
35. Hah, N. and Kraus, W.L. (2014) Hormone-regulated transcriptomes: lessons learned from estrogen signaling pathways in breast cancer cells. Mol. Cell. Endocrinol., 382, 652-664.
36. Alvord, G., Roayaei, J., Stephens, R., Baseler, M.W., Lane, H.C. and Lempicki, R.A. (2007) The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists. Genome Biol., 8, 183.
37. Huang, D.W., Sherman, B.T., Tan, Q., Kir, J., Liu, D., Bryant, D., Guo, Y., Stephens, R., Baseler, M.W., Lane, H.C. et al. (2007) DAVID Bioinformatics Resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res., 35(Suppl 2), W169-W175.
38. Lehmann, B.D. and Pietenpol, J.A. (2014) Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes. J. Pathol., 232, 142-150.
39. Sun, H., Qin, B., Liu, T., Wang, Q., Liu, J., Wang, J., Lin, X., Yang, Y., Taing, L., Rao, P.K. et al. (2013) CistromeFinder for ChIP-seq and DNase-seq data reuse. Bioinformatics, 29, 1352-1354.
40. Qin, B., Zhou, M., Ge, Y., Taing, L., Liu, T., Wang, Q., Wang, S., Chen, J., Shen, L., Duan, X. et al. (2012) CistromeMap: a knowledgebase and web server for ChIP-Seq and DNase-Seq studies in mouse and human. Bioinformatics, 28, 1411-1412.
41. Consortium, E.P. et al. (2012) An integrated encyclopedia of DNA elements in the human genome. Nature, 489, 57-74.
42. Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., Ziller, M.J. et al. (2015) Integrative analysis of 111 reference human epigenomes. Nature, 518, 317-330.