SWGTS - 一个基于流的宿主DNA枯竭平台.
Philipp Spohr1,2, Max Ried1,2, Laura Kühle1,2
1Algorithmic Bioinformatics, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany.
Bioinformatics (Oxford, England)
|May 24, 2024
概括
我们开发了SWGTS,这是一种基于流的工具,可以在传输过程中从微生物数据中删除人类DNA序列. 这增强了数据隐私,并通过限制遗传信息的暴露来遵守GDPR等法规.
科学领域:
- 生物信息学是一种生物信息学.
- 基因组数据分析 基因组数据分析
- 计算生物学 计算生物学
背景情况:
- 临床微生物测序生成的数据往往被人类DNA污染.
- 当前的人类读取删除方法需要完整的数据检索,构成隐私风险和GDPR合规挑战.
- 在数据传输期间基于流的宿主耗尽是敏感遗传数据的首选替代方案.
研究的目的:
- 为了呈现SWGTS,一个基于流的主机耗尽序列的客户端-服务器应用程序读取.
- 通过在运输过程中处理遗传数据来确保隐私和监管合规性.
- 为了减轻与共享临床测序数据相关的重新识别风险.
主要方法:
- SWGTS采用客户端-服务器架构,具有有限大小的缓冲区来控制人类遗传数据的内存使用.
- 数据传输速率被抑制以匹配服务器的后台主机耗尽速度.
- 该应用程序使用Docker,Redis和Traefik,需要最小的RAM (<8GB).
主要成果:
- SWGTS实现了高过准确度,可用于人类读取删除.
- 在保守的配置中,数据传输速率高达每秒1.65兆数据库.
- 通过限制可检测的SNP的数量,成功地减轻了重新识别风险.
结论:
- SWGTS提供了一种高效和安全的方法来处理受污染的微生物测序数据.
- 基于流的方法增强了数据隐私和监管合规性.
- 在GitHub上随时可以使用SWGTS,并提供可复制的基准.
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