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META2：细胞间DNA甲基化成对注释与综合分析。

META2: Intercellular DNA Methylation Pairwise Annotation and Integrative Analysis.

作者信息

Tang Binhua

机构信息

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

出版信息

Biomed Res Int. 2016;2016:1597489. doi: 10.1155/2016/1597489. Epub 2016 Dec 27.

DOI:10.1155/2016/1597489
PMID:28116291
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5223072/
Abstract

Genome-wide deciphering intercellular differential DNA methylation as well as its roles in transcriptional regulation remains elusive in cancer epigenetics. Here we developed a toolkit META2 for DNA methylation annotation and analysis, which aims to perform integrative analysis on differentially methylated loci and regions through deep mining and statistical comparison methods. META2 contains multiple versatile functions for investigating and annotating DNA methylation profiles. Benchmarked with T-47D cell, we interrogated the association within differentially methylated CpG (DMC) and region (DMR) candidate count and region length and identified major transition zones as clues for inferring statistically significant DMRs; together we validated those DMRs with the functional annotation. Thus META2 can provide a comprehensive analysis approach for epigenetic research and clinical study.

摘要

在癌症表观遗传学中，全基因组层面解析细胞间差异DNA甲基化及其在转录调控中的作用仍不清楚。在此，我们开发了一个用于DNA甲基化注释和分析的工具包META2，其目的是通过深度挖掘和统计比较方法，对差异甲基化位点和区域进行综合分析。META2具有多种用于研究和注释DNA甲基化图谱的通用功能。以T-47D细胞为基准，我们探究了差异甲基化CpG（DMC）和区域（DMR）候选计数与区域长度之间的关联，并确定主要过渡区作为推断具有统计学意义的DMR的线索；我们一起用功能注释验证了那些DMR。因此，META2可为表观遗传学研究和临床研究提供一种全面的分析方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/15f41e478fd8/BMRI2016-1597489.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/1716d9152d1e/BMRI2016-1597489.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/15f41e478fd8/BMRI2016-1597489.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/1716d9152d1e/BMRI2016-1597489.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/9948ca40c00d/BMRI2016-1597489.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/b33acdc10809/BMRI2016-1597489.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/1aece0866800/BMRI2016-1597489.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/069bafd958bc/BMRI2016-1597489.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/b7bde54ce84d/BMRI2016-1597489.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/18df/5223072/15f41e478fd8/BMRI2016-1597489.007.jpg

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本文引用的文献

1
Integrative analysis of 111 reference human epigenomes.111 个人类参考基因组的综合分析。
Nature. 2015 Feb 19;518(7539):317-30. doi: 10.1038/nature14248.
2
Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes.泛癌网络分析确定了跨通路和蛋白质复合物的罕见体细胞突变组合。
Nat Genet. 2015 Feb;47(2):106-14. doi: 10.1038/ng.3168. Epub 2014 Dec 15.
3
Pan-cancer patterns of DNA methylation.泛癌症 DNA 甲基化模式。
Genome Med. 2014 Aug 30;6(8):66. doi: 10.1186/s13073-014-0066-6. eCollection 2014.
4
Global loss of DNA methylation uncovers intronic enhancers in genes showing expression changes.DNA甲基化的整体缺失揭示了表达发生变化的基因中的内含子增强子。
Genome Biol. 2014 Sep 20;15(9):469. doi: 10.1186/s13059-014-0469-0.
5
The DNA methylation landscape of human early embryos.人类早期胚胎的 DNA 甲基化图谱。
Nature. 2014 Jul 31;511(7511):606-10. doi: 10.1038/nature13544. Epub 2014 Jul 23.
6
CTCF haploinsufficiency destabilizes DNA methylation and predisposes to cancer.CTCF单倍体不足会破坏DNA甲基化并易患癌症。
Cell Rep. 2014 May 22;7(4):1020-9. doi: 10.1016/j.celrep.2014.04.004. Epub 2014 May 1.
7
Principles and methods of integrative genomic analyses in cancer.癌症综合基因组分析的原则和方法。
Nat Rev Cancer. 2014 May;14(5):299-313. doi: 10.1038/nrc3721.
8
Differential methylation of the TRPA1 promoter in pain sensitivity.疼痛敏感性中TRPA1启动子的差异甲基化
Nat Commun. 2014;5:2978. doi: 10.1038/ncomms3978.
9
The Cancer Genome Atlas Pan-Cancer analysis project.癌症基因组图谱泛癌分析项目。
Nat Genet. 2013 Oct;45(10):1113-20. doi: 10.1038/ng.2764.
10
Charting a dynamic DNA methylation landscape of the human genome.绘制人类基因组动态 DNA 甲基化图谱。
Nature. 2013 Aug 22;500(7463):477-81. doi: 10.1038/nature12433. Epub 2013 Aug 7.