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Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies

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dc.contributor.author Escribà-Montagut, Xavier
dc.contributor.author Marcon, Yannick
dc.contributor.author Avraam, Demetris
dc.contributor.author Banerjee, Soumya
dc.contributor.author Bishop, Tom
dc.contributor.author Burton, Paul
dc.contributor.author González, Juan Ramón
dc.date.accessioned 2023-07-03T06:00:17Z
dc.date.available 2023-07-03T06:00:17Z
dc.date.issued 2023
dc.identifier.citation Escribà-Montagut X, Marcon Y, Avraam D, Banerjee S, Bishop TRP, Burton P, González JR. Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies. International Journal of Epidemiology. 2023;52(1):315–20. DOI: 10.1093/ije/dyac201
dc.identifier.issn 0300-5771
dc.identifier.uri http://hdl.handle.net/10230/57427
dc.description.abstract Motivation: DataSHIELD is an open-source software infrastructure enabling the analysis of data distributed across multiple databases (federated data) without leaking individuals’ information (non-disclosive). It has applications in many scientific domains, ranging from biosciences to social sciences and including high-throughput genomic studies. R is the language used to interact with (and build) DataSHIELD. This creates difficulties for researchers who do not have experience writing R code or lack the time to learn how to use the DataSHIELD functions. To help new researchers use the DataSHIELD infrastructure and to improve the user-friendliness for experienced researchers, we present ShinyDataSHIELD. Implementation: ShinyDataSHIELD is a web application with an R backend that serves as a graphical user interface (GUI) to the DataSHIELD infrastructure. General features: The version of the application presented here includes modules to perform: (i) exploratory analysis through descriptive summary statistics and graphical representations (scatter plots, histograms, heatmaps and boxplots); (ii) statistical modelling (generalized linear fixed and mixed-effects models, survival analysis through Cox regression); (iii) genome-wide association studies (GWAS); and (iv) omic analysis (transcriptomics, epigenomics and multi-omic integration). Availability: ShinyDataSHIELD is publicly hosted online [https://datashield-demo.obiba.org/], the source code and user guide are deposited on Zenodo DOI 10.5281/zenodo.6500323, freely available to non-commercial users under ‘Commons Clause’ License Condition v1.0. Docker images are also available [https://hub.docker.com/r/brgelab/shiny-data-shield].
dc.description.sponsorship This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No 874583 (ATHLETE) and No 824989 (EUCANConnect); also through Centro de Excelencia Severo Ochoa 2019–2023 Program (CEX2018-000806-S); also has received funding from the project PID2021-122855OB-I00 funded by MCIN /AEI / 10.13039/501100011033 / FEDER, UE; and through the support of the Government of Catalonia's Secretariat for Universities and Research of the Ministry of Economy and Knowledge (2017 SGR 801).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Oxford University Press
dc.relation.ispartof International Journal of Epidemiology. 2023;52(1):315–20
dc.rights © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.title Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1093/ije/dyac201
dc.subject.keyword R Shiny
dc.subject.keyword Federated analysis
dc.subject.keyword Non-disclosive analysis
dc.subject.keyword DataSHIELD
dc.subject.keyword Multicohort studies
dc.subject.keyword Genetic epidemiology
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874583
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/824989
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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