Higher order methylation features for clustering and prediction in epigenomic studies

Bioinformatics

Volumn 32, Issue 17, 2016, Pages i405-i412

  Kapourani, Chantriolnt Andreas ^a   Sanguinetti, Guido ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CPG ISLAND; DNA METHYLATION; EPIGENETICS; FORECASTING; GENE EXPRESSION; GENOME; MACHINE LEARNING; PROMOTER REGION;

CPG ISLANDS; DNA METHYLATION; EPIGENOMICS; FORECASTING; GENE EXPRESSION; GENOME; MACHINE LEARNING; PROMOTER REGIONS, GENETIC;

EID: 84990890478     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btw432     Document Type: Conference Paper

References (30)

1. Baylin, S.B. and Jones, P.A. (2011) A decade of exploring the cancer epigenome-biological and translational implications. Nat. Rev. Cancer, 11, 726-734
2. Benveniste, D. et al. (2014) Transcription factor binding predicts histone modifications in human cell lines. Proc. Natl. Acad. Sci. USA, 111, 13367-13372
3. Bird, A. (2002) DNA methylation patterns and epigenetic memory. Genes Dev., 16, 6-21
4. Bock, C. et al. (2012) DNA methylation dynamics during in vivo differentiation of blood and skin stem cells. Mol. Cell, 47, 633-647
5. Deaton, A. and Bird, A. (2011) CpG islands and the regulation of transcription. Genes Dev., 25, 1010-1022
6. Dempster, A.P. et al. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B Stat. Methodol., 39, 1-38
7. Dong, X. et al. (2012) Modeling gene expression using chromatin features in various cellular contexts. Genome Biol., 13, R53
8. Dunham, I., et al. (2012) An integrated encyclopedia of DNA elements in the human genome. Nature, 489, 57-74
9. Edgar, R. et al. (2014) Meta-analysis of human methylomes reveals stably methylated sequences surrounding CpG islands associated with high gene expression. Epigenetics Chromatin, 7, 28
10. Eisenberg, E. and Levanon, E.Y. (2013) Human housekeeping genes, revisited. Trends Genet., 29, 569-574
11. Feinberg, A.P. and Vogelstein, B. (1983) Hypomethylation distinguishes genes of some human cancers from their normal counterparts. Nature, 301, 89-92
12. Friedman, J.H. (1991) Multivariate adaptive regression splines. Ann. Stat., 19, 1-67
13. Hansen, K.D. et al. (2011) Increased methylation variation in epigenetic domains across cancer types. Nat. Genet., 43, 768-775
14. Hansen, K.D. et al. (2012) BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biol., 13, R83
15. Hebestreit, K. et al. (2013) Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. Bioinformatics, 29, 1647-1653
16. Jeong, M. et al. (2014) Large conserved domains of low DNA methylation maintained by Dnmt3a. Nat. Genet., 46, 17-23
17. Jones, P.A. (2012) Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet., 13, 484-492
18. Krueger, F. et al. (2012) DNA methylome analysis using short bisulfite sequencing data. Nat. Methods, 9, 145-151
19. Laird, P.W. (2003) The power and the promise of DNA methylation markers. Nat. Rev. Cancer, 3, 253-266
20. Li, E. et al. (1993) Role for DNA methylation in genomic imprinting. Nature, 366, 362-365
21. Lou, S. et al. (2014) Whole-genome bisulfite sequencing of multiple individuals reveals complementary roles of promoter and gene body methylation in transcriptional regulation. Genome Biol., 15, 408
22. Mayo, T.R. et al. (2015) M 3 D: A kernel-based test for spatially correlated changes in methylation profiles. Bioinformatics, 31, 809-816
23. McLachlan, G. and Peel, D. (2004). Finite Mixture Models. John Wiley &Sons, Hoboken
24. Meissner, A. et al. (2005) Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res., 33, 5868-5877
25. Min, I.M. et al. (2011) Regulating RNA polymerase pausing and transcription elongation in embryonic stem cells. Genes Dev., 25, 742-754
26. Trapnell, C. et al. (2012) Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc., 7, 562-578
27. Vanderkraats, N.D. et al. (2013) Discovering high-resolution patterns of differential DNA methylation that correlate with gene expression changes. Nucleic Acids Res., 41, 6816-6827
28. Varley, K.E. et al. (2013) Dynamic DNA methylation across diverse human cell lines and tissues. Genome Res., 23, 555-567
29. Wu, C.J. (1983) On the convergence properties of the EM algorithm. Ann. Stat., 11, 95-103
30. Wu, H. et al., (2010) Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science, 329, 444-448