DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts.
DMRcaller: a versatile R/Bioconductor package for detection and visualization of differentially methylated regions in CpG and non-CpG contexts.
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DOI：
10.1093/nar/gky602
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发表时间：
2018-11-02
影响因子：
14.9
通讯作者：
Zabet NR
中科院分区：
文献类型：
--
作者：
Catoni M;Tsang JM;Greco AP;Zabet NR
DNA甲基化与转录抑制有关，检测差异甲基化对于理解差异基因表达的潜在原因很重要。亚硫酸氢盐转换基因组DNA测序是目前在DNA甲基化碱基对分辨率下构建全基因组图谱领域的金标准。在这里，我们系统地研究了CpG和非CpG背景下检测差异DNA甲基化的潜在特征，同时考虑了哺乳动物系统和植物的情况。我们特别介绍了DMRcaller，一种高效的R/Bioconductor封装，它实现了几种方法来检测两个样品之间的差异甲基化区域（DMRs）。最重要的是，我们证明了计算dmr需要不同的算法，每种情况下最合适的算法取决于序列上下文和甲基化水平。此外，我们表明DMRcaller优于其他可用的包，我们提出了一种新的方法来选择该工具和其他可用工具的参数。DMRcaller是一种用于差异甲基化分析的综合工具，对DMRs的检测具有高灵敏度和特异性，并在几小时内进行全基因组分析。
DNA methylation has been associated with transcriptional repression and detection of differential methylation is important in understanding the underlying causes of differential gene expression. Bisulfite-converted genomic DNA sequencing is the current gold standard in the field for building genome-wide maps at a base pair resolution of DNA methylation. Here we systematically investigate the underlying features of detecting differential DNA methylation in CpG and non-CpG contexts, considering both the case of mammalian systems and plants. In particular, we introduce DMRcaller, a highly efficient R/Bioconductor package, which implements several methods to detect differentially methylated regions (DMRs) between two samples. Most importantly, we show that different algorithms are required to compute DMRs and the most appropriate algorithm in each case depends on the sequence context and levels of methylation. Furthermore, we show that DMRcaller outperforms other available packages and we propose a new method to select the parameters for this tool and for other available tools. DMRcaller is a comprehensive tool for differential methylation analysis which displays high sensitivity and specificity for the detection of DMRs and performs entire genome wide analysis within a few hours.
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DOI：
10.1038/nrm4043
发表时间：
2015-09
期刊：
Nature reviews. Molecular cell biology
影响因子：
--
作者：
Du J;Johnson LM;Jacobsen SE;Patel DJ
通讯作者：
Patel DJ
影响因子：
14.9
作者：
Feng H;Conneely KN;Wu H
通讯作者：
Wu H
影响因子：
64.8
作者：
Schultz, Matthew D.;He, Yupeng;Whitaker, John W.;Hariharan, Manoj;Mukamel, Eran A.;Leung, Danny;Rajagopal, Nisha;Nery, Joseph R.;Urich, Mark A.;Chen, Huaming;Lin, Shin;Lin, Yiing;Jung, Inkyung;Schmitt, Anthony D.;Selvaraj, Siddarth;Ren, Bing;Sejnowski, Terrence J.;Wang, Wei;Ecker, Joseph R.
通讯作者：
Ecker, Joseph R.
DOI：
10.1038/nrg3788
发表时间：
2014-11
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
通讯作者：
--
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J