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EAP:一个基于云的多功能平台,用于对大型ChIP/ATAC-seq数据集进行有效的定量分析
Guangyong Zheng1,2, Haojie Chen1,3, Zhijie Guo1,3
1CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, China.
Computational and structural biotechnology journal
|December 4, 2025
概括
研究人员现在可以使用EAP (表观基因组分析平台) 轻松分析大型表观基因组数据集. 这种基于云的工具简化了复杂的ChIP-seq和ATAC-seq数据分析,使新的生物发现成为可能.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 像ChIP-seq和ATAC-seq这样的表观基因组分析技术对于理解基因调节至关重要.
- 越来越多的表观基因组数据需要先进的分析平台.
- 现有的云平台往往需要配置和管理方面的技术专长.
研究的目的:
- 开发一个可扩展的,基于云的平台,用于对大型ChIP-seq和ATAC-seq数据集进行高效和可重复的分析.
- 为研究人员,特别是实验生物学家提供一个用户友好的,无配置的环境.
- 整合一套全面的计算工具套件,用于各种表观基因组分析.
主要方法:
- 开发了表观基因组分析平台 (EAP),这是一个基于网络,云集成的系统.
- 整合一个精心策划的计算工具集合,包括新的监督和无监督方法.
- 实现一个无需配置的环境,提供无的用户体验.
主要成果:
- EAP提供大规模ChIP/ATAC-seq数据的高效和可重复分析.
- 该平台支持广泛的下游功能分析,从数据预处理到生物见解.
- 在异质数据集上,EAP促进了复杂的分析,如瘤亚型和治疗点的发现.
结论:
- 欧洲表观基因组计划解决了对可访问和强大的表观基因组数据分析工具的需求.
- 该平台使研究人员能够探索发育和疾病中的表观基因组动态.
- EAP使先进的表观基因组分析民主化,加速生物发现.
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