通过聚合ChIP-seq和扰乱表达数据集来描述转录调节器的目标
Alexander Morin1,2,3, Eric Ching-Pan Chu1,2,3, Aman Sharma1
1Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada.
Genome research
|June 12, 2023
概括
本研究提出了一个工作流程,以整合ChIP-seq和转录调节器 (TR) 扰动数据. 它对人类和小鼠的TR-目标相互作用进行了排名,为研究人员提供了有价值的基因摘要.
科学领域:
- 基因组学和分子生物学
- 基因法规 基因法规
- 生物信息学是一种生物信息学.
背景情况:
- 在基因组学中,对转录调节器 (TRs) 的基因目标进行映射至关重要.
- 现有的CHIP-seq和TR扰动数据显示不太重叠,需要综合分析.
- 在科学文献中存在大量的TR特定数据.
研究的目的:
- 开发和介绍一个工作流程,用于识别,处理和聚合ChIP-seq和TR扰动实验.
- 通过整合多种数据类型来对人类和小鼠的转录调节器-目标相互作用进行排名.
- 为社区使用提供经验性排名的TR目标列表和透明的基因摘要.
主要方法:
- 对八个关键调节器进行了497次ChIP-seq和TR扰动实验的识别和统一处理.
- 来自这两种基因组学方法的数据的聚合.
- 对综合排名的评估与独立的,经过文献策划的证据进行评估.
主要成果:
- 检查CHIP-seq和TR扰动数据之间的数据一致性和系统模式.
- 确定人类和小鼠TRs之间的假定正统相互作用.
- 生成经验排序的TR-目标交互列表.
结论:
- 开发的工作流程有效地集成了ChIP-seq和TR扰动数据,用于排名TR-target交互.
- 该研究提供了一个可扩展到其他TR的框架,并为研究界提供了有价值,透明的数据资源.
- 整合多种实验策略可以提高基因调节见解的可靠性.
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