Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Escribà-Montagut, Xavier, Marcon, Yannick, Avraam, Demetris, Banerjee, Soumya, Bishop, Tom R P, Burton, Paul, González, Juan R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908040/
http://dx.doi.org/10.1093/ije/dyac201
_version_ 1784884300747898880
author Escribà-Montagut, Xavier
Marcon, Yannick
Avraam, Demetris
Banerjee, Soumya
Bishop, Tom R P
Burton, Paul
González, Juan R
author_facet Escribà-Montagut, Xavier
Marcon, Yannick
Avraam, Demetris
Banerjee, Soumya
Bishop, Tom R P
Burton, Paul
González, Juan R
author_sort Escribà-Montagut, Xavier
collection PubMed
description 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].
format Online
Article
Text
id pubmed-9908040
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-99080402023-02-09 Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies Escribà-Montagut, Xavier Marcon, Yannick Avraam, Demetris Banerjee, Soumya Bishop, Tom R P Burton, Paul González, Juan R Int J Epidemiol Software Application Profile 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]. Oxford University Press 2022-10-27 /pmc/articles/PMC9908040/ http://dx.doi.org/10.1093/ije/dyac201 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. https://creativecommons.org/licenses/by-nc-nd/4.0/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
spellingShingle Software Application Profile
Escribà-Montagut, Xavier
Marcon, Yannick
Avraam, Demetris
Banerjee, Soumya
Bishop, Tom R P
Burton, Paul
González, Juan R
Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title_full Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title_fullStr Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title_full_unstemmed Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title_short Software Application Profile: ShinyDataSHIELD—an R Shiny application to perform federated non-disclosive data analysis in multicohort studies
title_sort software application profile: shinydatashield—an r shiny application to perform federated non-disclosive data analysis in multicohort studies
topic Software Application Profile
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9908040/
http://dx.doi.org/10.1093/ije/dyac201
work_keys_str_mv AT escribamontagutxavier softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT marconyannick softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT avraamdemetris softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT banerjeesoumya softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT bishoptomrp softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT burtonpaul softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies
AT gonzalezjuanr softwareapplicationprofileshinydatashieldanrshinyapplicationtoperformfederatednondisclosivedataanalysisinmulticohortstudies