EpiChIP: gene-by-gene quantification of epigenetic modification levels
EpiChIP: gene-by-gene quantification of epigenetic modification levels
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DOI：
10.1093/nar/gkq1226
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发表时间：
2011-03-01
影响因子：
14.9
通讯作者：
Teichmann, Sarah A.
中科院分区：
文献类型：
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作者：
Hebenstreit, Daniel;Gu, Muxin;Teichmann, Sarah A.
染色质免疫沉淀与下一代测序技术（ChIP-seq）的结合是一种强大且日益流行的方法，用于以全基因组方式绘制蛋白质-DNA相互作用。分析该数据的常规方法是鉴定沿着染色体的测序峰，所述测序峰显著高于读取背景。对于组蛋白修饰和其他表观遗传标记，通常优选的是相对于基因注释在测序读段中找到富集的特征区域。例如，许多组蛋白修饰通常在转录起始位点周围富集。计算描述这种富集的最佳窗口允许量化每个单独基因的修饰水平。使用Th细胞中H3 K9/14 ac组蛋白修饰的数据集和伴随的IgG对照，我们提出了一种分析策略，该策略在单基因和全局数据分布水平之间交替，并允许实验背景和信号之间的明确区分。曲线拟合允许基于错误发现率将基因分类为修饰的与未修饰的。我们开发了一个名为EpiChIP的软件包，可以进行这种类型的分析，包括整合和可视化基因表达数据。
The combination of chromatin immunoprecipitation with next-generation sequencing technology (ChIP-seq) is a powerful and increasingly popular method for mapping protein-DNA interactions in a genome-wide fashion. The conventional way of analyzing this data is to identify sequencing peaks along the chromosomes that are significantly higher than the read background. For histone modifications and other epigenetic marks, it is often preferable to find a characteristic region of enrichment in sequencing reads relative to gene annotations. For instance, many histone modifications are typically enriched around transcription start sites. Calculating the optimal window that describes this enrichment allows one to quantify modification levels for each individual gene. Using data sets for the H3K9/14ac histone modification in Th cells and an accompanying IgG control, we present an analysis strategy that alternates between single gene and global data distribution levels and allows a clear distinction between experimental background and signal. Curve fitting permits false discovery rate-based classification of genes as modified versus unmodified. We have developed a software package called EpiChIP that carries out this type of analysis, including integration with and visualization of gene expression data.