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BioMed Research International
Volume 2016, Article ID 1597489, 10 pages
http://dx.doi.org/10.1155/2016/1597489
Research Article

META2: Intercellular DNA Methylation Pairwise Annotation and Integrative Analysis

1Epigenetics & Function Group, School of Internet of Things, Hohai University, Jiangsu 213022, China
2School of Public Health, Shanghai Jiao Tong University, Shanghai 200025, China

Received 17 September 2016; Accepted 12 December 2016

Academic Editor: Hao-Teng Chang

Copyright © 2016 Binhua Tang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. The Cancer Genome Atlas Research Network, J. N. Weinstein, E. A. Collisson et al., “The cancer genome Atlas pan-cancer analysis project,” Nature Genetics, vol. 45, pp. 1113–1120, 2013. View at Publisher · View at Google Scholar
  2. V. N. Kristensen, O. C. Lingjærde, H. G. Russnes, H. K. M. Vollan, A. Frigessi, and A.-L. Børresen-Dale, “Principles and methods of integrative genomic analyses in cancer,” Nature Reviews Cancer, vol. 14, no. 5, pp. 299–313, 2014. View at Publisher · View at Google Scholar · View at Scopus
  3. T. Witte, C. Plass, and C. Gerhauser, “Pan-cancer patterns of DNA methylation,” Genome Medicine, vol. 6, no. 8, article 66, pp. 1–18, 2014. View at Publisher · View at Google Scholar · View at Scopus
  4. M. D. M. Leiserson, F. Vandin, H.-T. Wu et al., “Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes,” Nature Genetics, vol. 47, no. 2, pp. 106–114, 2015. View at Publisher · View at Google Scholar · View at Scopus
  5. The Cancer Genome Atlas Research Networ, “Comprehensive genomic characterization of squamous cell lung cancers,” Nature, vol. 489, no. 7417, pp. 519–525, 2012. View at Publisher · View at Google Scholar
  6. The Cancer Genome Atlas Research Network, “Comprehensive molecular portraits of human breast tumours,” Nature, vol. 490, no. 7418, pp. 61–70, 2012. View at Publisher · View at Google Scholar
  7. A. Meissner, T. S. Mikkelsen, H. Gu et al., “Genome-scale DNA methylation maps of pluripotent and differentiated cells,” Nature, vol. 454, no. 7205, pp. 766–770, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. H. Heyn, F. Carmona Javier, A. Gomez et al., “DNA methylation profiling in breast cancer discordant identical twins identifies DOK7 as novel epigenetic biomarker,” Carcinogenesis, vol. 34, no. 1, pp. 102–108, 2013. View at Publisher · View at Google Scholar · View at Scopus
  9. R. Lister, E. A. Mukamel, J. R. Nery et al., “Global epigenomic reconfiguration during mammalian brain development,” Science, vol. 341, no. 6146, Article ID 1237905, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. J. T. Bell, A. K. Loomis, L. M. Butcher et al., “Differential methylation of the TRPA1 promoter in pain sensitivity,” Nature Communications, vol. 5, article no. 2978, 2014. View at Publisher · View at Google Scholar · View at Scopus
  11. A. Meissner, A. Gnirke, G. W. Bell, B. Ramsahoye, E. S. Lander, and R. Jaenisch, “Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis,” Nucleic Acids Research, vol. 33, no. 18, pp. 5868–5877, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. H. Guo, P. Zhu, L. Yan et al., “The DNA methylation landscape of human early embryos,” Nature, vol. 511, no. 7511, pp. 606–610, 2014. View at Publisher · View at Google Scholar · View at Scopus
  13. A. Kundaje, W. Meuleman, J. Ernst et al., “Integrative analysis of 111 reference human epigenomes,” Nature, vol. 518, no. 7539, pp. 317–330, 2015. View at Publisher · View at Google Scholar
  14. J. Maksimovic, L. Gordon, and A. Oshlack, “SWAN: subset-quantile within array normalization for illumina infinium humanmethylation450 beadchips,” Genome Biology, vol. 13, no. 6, 2012. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Bibikova, B. Barnes, C. Tsan et al., “High density DNA methylation array with single CpG site resolution,” Genomics, vol. 98, no. 4, pp. 288–295, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. R. Lister, M. Pelizzola, R. H. Dowen et al., “Human DNA methylomes at base resolution show widespread epigenomic differences,” Nature, vol. 462, no. 7271, pp. 315–322, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. M. J. Ziller, H. Gu, F. Müller et al., “Charting a dynamic DNA methylation landscape of the human genome,” Nature, vol. 500, no. 7463, pp. 477–481, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. A. Blattler, L. Yao, H. Witt et al., “Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes,” Genome Biology, vol. 15, article 469, 2014. View at Publisher · View at Google Scholar
  19. C. J. Kemp, J. M. Moore, R. Moser et al., “CTCF haploinsufficiency destabilizes DNA methylation and predisposes to cancer,” Cell Reports, vol. 7, no. 4, pp. 1020–1029, 2014. View at Publisher · View at Google Scholar · View at Scopus
  20. B. Langmead and S. L. Salzberg, “Fast gapped-read alignment with Bowtie 2,” Nature Methods, vol. 9, no. 4, pp. 357–359, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. H. Li, B. Handsaker, A. Wysoker et al., “The sequence alignment/map format and SAMtools,” Bioinformatics, vol. 25, no. 16, pp. 2078–2079, 2009. View at Publisher · View at Google Scholar · View at Scopus
  22. D. W. Barnett, E. K. Garrison, A. R. Quinlan, M. P. Strömberg, and G. T. Marth, “Bamtools: A C++ API and toolkit for analyzing and managing BAM files,” Bioinformatics, vol. 27, no. 12, Article ID btr174, pp. 1691–1692, 2011. View at Publisher · View at Google Scholar · View at Scopus
  23. A. Akalin, M. Kormaksson, S. Li et al., “methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles,” Genome Biology, vol. 13, no. 10, article R87, 2012. View at Publisher · View at Google Scholar · View at Scopus
  24. S. Anders and W. Huber, “Differential expression analysis for sequence count data,” Genome Biology, vol. 11, no. 10, article R106, 2010. View at Publisher · View at Google Scholar · View at Scopus