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加强临床数据存储与来源数据,以支持纵向分析和大型文件管理: gitOmmix 方法用于基因组和图像数据

Maxime Wack¹, Adrien Coulet², Anita Burgun³

¹Centre de Recherche des Cordeliers, UMRS 1138, Inserm, Université Paris Cité, Sorbonne Université, Paris, France; Inria Paris, Paris, France; Department of Biomedical Informatics, Hôpital Européen Georges Pompidou, AP-HP, Paris, France; Centre Hospitalier National d'Ophtalmologie des Quinze-Vingts, IHU FOReSIGHT, 75012 Paris, France.

Journal of biomedical informatics

|February 14, 2025

概括

gitOmmix通过添加源地数据来增强临床数据仓库,用于纵向患者跟踪和管理大型omics数据集. 这种开源解决方案确保了个性化医学研究的数据完整性和可追溯性.

科学领域:

生物医学信息学生物医学信息学
基因组学就是基因组学.
数据科学数据科学数据科学

背景情况:

目前的临床数据仓库 (CDW) 缺乏用于纵向患者跟踪和管理个性化医疗所需的大型omics数据集的能力.
现有的系统无法为复杂的数据类型提供可靠的来源,例如全基因组测序,RNA分析和先进的成像.
这就需要丰富CDW,以应对现代生物医学研究的需求.

研究的目的:

介绍 gitOmmix,这是一个开源方法,以丰富 CDWs 的来源数据.
为了使纵向患者数据跟踪和大规模omics数据的高效管理.
提供适用于任何CDW系统的通用化解决方案,无论其数据模式如何.

主要方法:

gitOmmix将git文件版本管理系统与git-annex集成在一起,用于大型文件管理.
它使用PROV-O来源知识图来表示数据谱系和关系.
在git版本信息和PROV-O知识图之间建立了对齐,用于全面的数据跟踪.

主要成果:

gitOmmix可以通过支持数据和分析追溯临床解释到患者样本.
集成的来源知识图允许查询和浏览数据关系.
这有助于对数据来源和分析工作流程的清晰理解.

结论:

gitOmmix为CDW提供了一个可扩展的来源层,擅长处理大型文件.
该解决方案与特定的CDW系统无关,具有广泛的适用性.
gitOmmix为omics临床研究提供了可行的和可通用的解决方案,推进了个性化医学.

关键词:

临床数据仓库临床数据仓库大数据文件是大型的数据文件.奥米克斯数据数据的数据.产地来源产地来源语义网络是一个语义网络.翻译医学是一种翻译医学.

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