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COCOA: coordinate covariation analysis of epigenetic heterogeneity

机译:Cocoa:表述异质性的坐标协变分析

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A key challenge in epigenetics is to determine the biological significance of epigenetic variation among individuals. We present Coordinate Covariation Analysis (COCOA), a computational framework that uses covariation of epigenetic signals across individuals and a database of region sets to annotate epigenetic heterogeneity. COCOA is the first such tool for DNA methylation data and can also analyze any epigenetic signal with genomic coordinates. We demonstrate COCOA’s utility by analyzing DNA methylation, ATAC-seq, and multi-omic data in supervised and unsupervised analyses, showing that COCOA provides new understanding of inter-sample epigenetic variation. COCOA is available on Bioconductor ( http://bioconductor.org/packages/COCOA ).
机译:表观遗传学的关键挑战是确定个体表观遗传变异的生物学意义。我们呈现坐标协变量分析(Cocoa),计算框架,该计算框架利用各个人的表观遗传信号的协调以及区域组数据库,以注释表观遗传异质性。可可是DNA甲基化数据的第一种工具,并且还可以通过基因组坐标来分析任何外膜遗传信号。通过在监督和无监督分析中分析DNA甲基化,ATAC-SEQ和多OMIC数据,证明了可可的效用,表明Cocoa提供了对样本间表观遗传变异的了解。可可在Biocumons(http://biocumon.org/packages/cocoa)上有。

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