Bioinformatics Division (MF 1), Department for Methods Development and Research Infrastructure.
Centre for Biological Threats and Special Pathogens: Highly Pathogenic Viruses (ZBS 1).
Bioinformatics. 2018 Jul 15;34(14):2376-2383. doi: 10.1093/bioinformatics/bty128.
In next-generation sequencing, re-identification of individuals and other privacy-breaching strategies can be applied even for anonymized data. This also holds true for applications in which human DNA is acquired as a by-product, e.g. for viral or metagenomic samples from a human host. Conventional data protection strategies including cryptography and post-hoc filtering are only appropriate for the final and processed sequencing data. This can result in an insufficient level of data protection and a considerable time delay in the further analysis workflow.
We present PriLive, a novel tool for the automated removal of sensitive data while the sequencing machine is running. Thereby, human sequence information can be detected and removed before being completely produced. This facilitates the compliance with strict data protection regulations. The unique characteristic to cause almost no time delay for further analyses is also a clear benefit for applications other than data protection. Especially if the sequencing data are dominated by known background signals, PriLive considerably accelerates consequent analyses by having only fractions of input data. Besides these conceptual advantages, PriLive achieves filtering results at least as accurate as conventional post-hoc filtering tools.
PriLive is open-source software available at https://gitlab.com/rki_bioinformatics/PriLive.
Supplementary data are available at Bioinformatics online.
在下一代测序中，即使对于已匿名的数据，也可以应用重新识别个人和其他侵犯隐私的策略。这对于以人类 DNA 为副产品获取的应用程序也同样适用，例如来自人类宿主的病毒或宏基因组样本。传统的数据保护策略，包括加密和事后过滤，仅适用于最终和处理后的测序数据。这可能导致数据保护水平不足，并且在进一步的分析工作流程中会有相当长的延迟。
我们提出了 PriLive，这是一种在测序机运行时自动删除敏感数据的新工具。因此，可以在完全生成之前检测和删除人类序列信息。这有助于符合严格的数据保护法规。对于除数据保护以外的其他应用程序来说，几乎不会对进一步的分析造成时间延迟，这也是一个明显的优势。特别是如果测序数据主要由已知的背景信号主导，那么 PriLive 通过仅使用输入数据的一部分，就可以大大加速后续的分析。除了这些概念上的优势外，PriLive 的过滤结果至少与传统的事后过滤工具一样准确。
PriLive 是一个开源软件，可在 https://gitlab.com/rki_bioinformatics/PriLive 上获得。
补充数据可在 Bioinformatics 在线获得。
