一个混合云数据湖架构,支持临床和基因组学数据的整合
Apollo McOwiti1, Heidi Dowst1, Fei Zheng1
1Biomedical Informatics Group, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
Health informatics journal
|June 18, 2025
概括
混合云数据湖架构有效地整合了癌症研究和运营的各种临床基因组学数据. 这种具有成本效益的解决方案为管理大型数据集提供了灵活性和可扩展性.
科学领域:
- 生物信息学是一种生物信息学.
- 医疗信息学 医疗信息学
- 基因组数据管理管理
背景情况:
- 由于昂贵且不灵活的数据仓库架构,癌症中心面临整合多样化的临床基因组学数据的挑战.
- 瘤学研究的快速变化需要可适应的数据管理解决方案.
研究的目的:
- 引入一个具有成本效益的混合云数据湖架构,用于整合来自多个供应商的临床基因组学数据.
- 支持瘤学的临床和研究工作流程.
主要方法:
- 使用混合云方法实现了四层区域架构 (摄入,存储,转换,交互).
- 丰富的元数据是从患者和基因组数据中创建的,以实现基于患者的查询.
- 建立了数据治理工作流程,以控制数据访问.
主要成果:
- 数据湖架构将基因组数据存储在云中,与供应商存储同步,并由治理委员会管理.
- 实施支持独立的临床场所,为31个疾病组的149名临床医生提供服务.
- 它为5800名患者管理240TB的数据,每月成本低,约为350美元.
结论:
- 数据湖架构为整合临床和基因组数据提供了灵活和可扩展的解决方案.
- 它适用于任何规模的组织,寻求有效的数据管理,用于临床和研究目的.
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