Spatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells.
Spatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells.
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DOI：
10.1007/978-1-4939-0512-6_5
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发表时间：
2014
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染色质状态是胚胎干细胞多能性和分化的关键。染色质免疫沉淀（ChIP）和高通量测序（ChIP-Seq）越来越多地用于绘制染色质状态和功能注释基因组。许多ChIP-Seq图谱，特别是组蛋白甲基化图谱，都是嘈杂和弥散的。在这里，我们描述了SICER（Zang等人，Bioinformatics 25（15）：1952-1958，2009），一种专门设计用于以高灵敏度和特异性鉴定分散的ChIP富集区域的算法。该算法在表观基因组学研究中得到了广泛的应用。在本章中，我们将详细演示如何运行SICER来描绘ChIP富集区域并评估其统计学意义，以及如何在比较两种染色质状态时识别差异富集区域。
Chromatin states are the key to embryonic stem cell pluripotency and differentiation. Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) is increasingly used to map chromatin states and to functionally annotate the genome. Many ChIP-Seq profiles, especially those of histone methylations, are noisy and diffuse. Here we describe SICER (Zang et al., Bioinformatics 25(15):1952–1958, 2009), an algorithm specifically designed to identify disperse ChIP-enriched regions with high sensitivity and specificity. This algorithm has found a lot of applications in epigenomic studies. In this Chapter, we will demonstrate in detail how to run SICER to delineate ChIP-enriched regions and assess their statistical significance, and to identify regions of differential enrichment when two chromatin states are compared.