MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments
MAPS: Model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments
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DOI：
10.1371/journal.pcbi.1006982
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发表时间：
2019-04-01
影响因子：
4.3
通讯作者：
Hu, Ming
中科院分区：
文献类型：
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作者：
Juric, Ivan;Yu, Miao;Hu, Ming
HI-C和染色质免疫沉淀(CHIP)相结合，以降低成本和提高分辨率的方式在全基因组范围内识别染色质的远程相互作用，但从产生的数据集中提取信息一直是具有挑战性的。在这里，我们描述了一种计算方法，MAP，Plac-Seq和HiChIP的基于模型的分析，以处理来自此类实验的数据并识别远程染色质相互作用。MAP采用零截断泊松回归框架来明确消除PLAC-SEQ和HiChIP数据集中的系统偏差，然后使用归一化染色质接触频率来识别锚定在目标蛋白质结合的基因组区域的显著染色质相互作用。在分析以不同转录因子和组蛋白标记为中心的多个Plac-Seq和HiChIP数据集的染色质相互作用时，MAP显示出优于现有软件工具的性能。地图可在https://github.com/ijuric/MAPS.上免费获取
Hi-C and chromatin immunoprecipitation (ChIP) have been combined to identify long-range chromatin interactions genome-wide at reduced cost and enhanced resolution, but extracting information from the resulting datasets has been challenging. Here we describe a computational method, MAPS, Model-based Analysis of PLAC-seq and HiChIP, to process the data from such experiments and identify long-range chromatin interactions. MAPS adopts a zero-truncated Poisson regression framework to explicitly remove systematic biases in the PLAC-seq and HiChIP datasets, and then uses the normalized chromatin contact frequencies to identify significant chromatin interactions anchored at genomic regions bound by the protein of interest. MAPS shows superior performance over existing software tools in the analysis of chromatin interactions from multiple PLAC-seq and HiChIP datasets centered on different transcriptional factors and histone marks. MAPS is freely available at https://github.com/ijuric/MAPS.