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高通量芯片和深度测序技术为在全基因组水平上绘制高分辨率的基因组变异、RNA转录、转录因子结合及组蛋白修饰图谱等研究提供了前所未有的机遇.这些技术彻底改变了以往有关转录组学、调控网络以及表观遗传调控的研究方法,产生了海量的多水平组学数据,并开启了高效数据整合研究的先河.然而,如何有效地整合这些数据仍然是一个巨大的挑战.本文总结了高通量组学数据的产生对相关领域研究的主要影响及其与人类疾病的关系,并介绍了多种用于数据整合分析的生物信息学方法.最后,以炎症疾病为例进行说明.
High throughput chip and depth sequencing provide unprecedented opportunities to map high-resolution genomic variation, RNA transcription, transcription factor binding and histone modification maps at the genome-wide level that have revolutionized the previous work on transcriptomes Learning, regulatory networks and epigenetic regulation research methods have produced a great deal of multi-level omics data and started the study of efficient data integration.However, how to effectively integrate these data remains a huge challenge. The main effects of high-throughput omics data on research in related fields and their relationship with human diseases are introduced, and a variety of bioinformatics methods for data integration analysis are introduced.Finally, the case of inflammatory diseases is illustrated.