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

被引：0

作者：

Escriba-Montagut, Xavier ^{[1
,2
]}

Marcon, Yannick ^{[3
]}

Anguita-Ruiz, Augusto ^{[1
,2
]}

Avraam, Demetris ^{[4
]}

Urquiza, Jose ^{[1
,2
,5
]}

Morgan, Andrei S. ^{[6
,7
]}

Wilson, Rebecca C. ^{[4
]}

Burton, Paul ^{[8
]}

Gonzalez, Juan R. ^{[1
,2
,5
]}

机构：

[1] Barcelona Inst Global Hlth ISGlobal, Barcelona, Spain

[2] Univ Pompeu Fabra UPF, Barcelona, Spain

[3] Epigeny, St Ouen, France

[4] Univ Liverpool, Dept Publ Hlth Policy & Syst, Liverpool, England

[5] Ctr Invest Biomed Red Epidemiol & Salud Publ CIBER, Barcelona, Spain

[6] Univ Paris Cite, Ctr Res Epidemiol & Stat CRESS, Obstetr Perinatal & Pediat Epidemiol Res Team EPOP, INSERM,INRAE, F-75006 Paris, France

[7] Univ Coll London Hosp, Elizabeth Garrett Anderson Inst Womens Hlth, London, England

[8] Newcastle Univ, Populat Hlth Sci Inst, Newcastle, England

来源：

PLOS COMPUTATIONAL BIOLOGY | 2024年 / 20卷 / 12期

基金：

欧盟地平线“2020”;

关键词：

METAANALYSIS;

D O I：

10.1371/journal.pcbi.1012626

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

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.

引用

页数：22