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在多中心研究中，使用完全开源的分析平台进行联合隐私保护的元组学和宏组学数据分析。

Federated privacy-protected meta- and mega-omics data analysis in multi-center studies with a fully open-source analytic platform.

作者信息

Escriba-Montagut Xavier, Marcon Yannick, Anguita-Ruiz Augusto, Avraam Demetris, Urquiza Jose, Morgan Andrei S, Wilson Rebecca C, Burton Paul, Gonzalez Juan R

机构信息

Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain.

Universitat Pompeu Fabra (UPF), Barcelona, Spain.

出版信息

PLoS Comput Biol. 2024 Dec 9;20(12):e1012626. doi: 10.1371/journal.pcbi.1012626. eCollection 2024 Dec.

DOI:10.1371/journal.pcbi.1012626
PMID:39652598
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11658699/
Abstract

The importance of maintaining data privacy and complying with regulatory requirements is highlighted especially when sharing omic data between different research centers. This challenge is even more pronounced in the scenario where a multi-center effort for collaborative omics studies is necessary. OmicSHIELD is introduced as an open-source tool aimed at overcoming these challenges by enabling privacy-protected federated analysis of sensitive omic data. In order to ensure this, multiple security mechanisms have been included in the software. This innovative tool is capable of managing a wide range of omic data analyses specifically tailored to biomedical research. These include genome and epigenome wide association studies and differential gene expression analyses. OmicSHIELD is designed to support both meta- and mega-analysis, so that it offers a wide range of capabilities for different analysis designs. We present a series of use cases illustrating some examples of how the software addresses real-world analyses of omic data.

摘要

在不同研究中心之间共享组学数据时，维护数据隐私和遵守监管要求的重要性尤为凸显。在需要多中心协作进行组学研究的情况下，这一挑战更为突出。OmicSHIELD作为一种开源工具被引入，旨在通过对敏感组学数据进行隐私保护的联合分析来克服这些挑战。为确保这一点，该软件纳入了多种安全机制。这种创新工具能够管理专门为生物医学研究量身定制的广泛组学数据分析。这些分析包括全基因组和表观基因组关联研究以及差异基因表达分析。OmicSHIELD旨在支持荟萃分析和大型分析，因此它为不同的分析设计提供了广泛的功能。我们展示了一系列用例，说明了该软件如何处理组学数据的实际分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/6afd96941ee8/pcbi.1012626.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/d25a60841255/pcbi.1012626.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/2f7640df5f98/pcbi.1012626.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/618df4b57d24/pcbi.1012626.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/24d2ac1c7b48/pcbi.1012626.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/f99779c1044d/pcbi.1012626.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/3e53593e8202/pcbi.1012626.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/6afd96941ee8/pcbi.1012626.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/d25a60841255/pcbi.1012626.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/2f7640df5f98/pcbi.1012626.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/618df4b57d24/pcbi.1012626.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/24d2ac1c7b48/pcbi.1012626.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/f99779c1044d/pcbi.1012626.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/3e53593e8202/pcbi.1012626.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6876/11658699/6afd96941ee8/pcbi.1012626.g007.jpg

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