Software Application Profile: exposomeShiny-a toolbox for exposome data analysis

Motivation: Studying the role of the exposome in human health and its impact on different omic layers requires advanced statistical methods. Many of these methods are implemented in different R and Bioconductor packages, but their use may require strong expertise in R, in writing pipelines and in us...

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Autores: Escriba-Montagut, Xavier, Basagaña Flores, Xavier, Vrijheid, Martine, González, Juan Ramón
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/53201
Acceso en línea:http://hdl.handle.net/10230/53201
http://dx.doi.org/10.1093/ije/dyab220
Access Level:acceso abierto
Palabra clave:Exposome
Shiny
R
Graphical user interface
Toolbox
Epidemiology
ExWAS
Biological insights
Omics-exposures association
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spelling Software Application Profile: exposomeShiny-a toolbox for exposome data analysisEscriba-Montagut, XavierBasagaña Flores, XavierVrijheid, MartineGonzález, Juan RamónExposomeShinyRGraphical user interfaceToolboxEpidemiologyExWASBiological insightsOmics-exposures associationMotivation: Studying the role of the exposome in human health and its impact on different omic layers requires advanced statistical methods. Many of these methods are implemented in different R and Bioconductor packages, but their use may require strong expertise in R, in writing pipelines and in using new R classes which may not be familiar to non-advanced users. ExposomeShiny provides a bridge between researchers and most of the state-of-the-art exposome analysis methodologies, without the need of advanced programming skills. Implementation: ExposomeShiny is a standalone web application implemented in R. It is available as source files and can be installed in any server or computer avoiding problems with data confidentiality. It is executed in RStudio which opens a browser window with the web application. General features: The presented implementation allows the conduct of: (i) data pre-processing: normalization and missing imputation (including limit of detection); (ii) descriptive analysis; (iii) exposome principal component analysis (PCA) and hierarchical clustering; (iv) exposome-wide association studies (ExWAS) and variable selection ExWAS; (v) omic data integration by single association and multi-omic analyses; and (vi) post-exposome data analyses to gain biological insight for the exposures, genes or using the Comparative Toxicogenomics Database (CTD) and pathway analysis. Availability: The exposomeShiny source code is freely available on Github at [https://github.com/isglobal-brge/exposomeShiny], Git tag v1.4. The software is also available as a Docker image [https://hub.docker.com/r/brgelab/exposome-shiny], tag v1.4. A user guide with information about the analysis methodologies as well as information on how to use exposomeShiny is freely hosted at [https://isglobal-brge.github.io/exposome_bookdown/].This research has received funding from: the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 874583 (ATHLETE); the Ministerio de Ciencia, Innovación y Universidades (MICIU), Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional, UE (RTI2018-100789-B-I00) ,also through the ‘Centro de Excelencia Severo Ochoa 2019–2023’ Program (CEX2018-000806-S); and the Catalan Government through the CERCA Program. This article is part of the project VEIS: 001-P-001647 co-financed by the European Regional Development Fund of the European Union in the framework of the Operational Program FEDER of Catalonia 2014–2020 with the support of the Secretaria d'Universitats i Recerca del Departament d'Empresa i Coneixement de la Generalitat de Catalunya.Oxford University Press202220222022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/53201http://dx.doi.org/10.1093/ije/dyab220reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésInternational Journal of Epidemiology. 2022;51(1):18–26info:eu-repo/grantAgreement/EC/H2020/874583© The Author(s) 2021. 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 License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.comhttps://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/532012026-05-29T05:05:01Z
dc.title.none.fl_str_mv Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
title Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
spellingShingle Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
Escriba-Montagut, Xavier
Exposome
Shiny
R
Graphical user interface
Toolbox
Epidemiology
ExWAS
Biological insights
Omics-exposures association
title_short Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
title_full Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
title_fullStr Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
title_full_unstemmed Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
title_sort Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
dc.creator.none.fl_str_mv Escriba-Montagut, Xavier
Basagaña Flores, Xavier
Vrijheid, Martine
González, Juan Ramón
author Escriba-Montagut, Xavier
author_facet Escriba-Montagut, Xavier
Basagaña Flores, Xavier
Vrijheid, Martine
González, Juan Ramón
author_role author
author2 Basagaña Flores, Xavier
Vrijheid, Martine
González, Juan Ramón
author2_role author
author
author
dc.subject.none.fl_str_mv Exposome
Shiny
R
Graphical user interface
Toolbox
Epidemiology
ExWAS
Biological insights
Omics-exposures association
topic Exposome
Shiny
R
Graphical user interface
Toolbox
Epidemiology
ExWAS
Biological insights
Omics-exposures association
description Motivation: Studying the role of the exposome in human health and its impact on different omic layers requires advanced statistical methods. Many of these methods are implemented in different R and Bioconductor packages, but their use may require strong expertise in R, in writing pipelines and in using new R classes which may not be familiar to non-advanced users. ExposomeShiny provides a bridge between researchers and most of the state-of-the-art exposome analysis methodologies, without the need of advanced programming skills. Implementation: ExposomeShiny is a standalone web application implemented in R. It is available as source files and can be installed in any server or computer avoiding problems with data confidentiality. It is executed in RStudio which opens a browser window with the web application. General features: The presented implementation allows the conduct of: (i) data pre-processing: normalization and missing imputation (including limit of detection); (ii) descriptive analysis; (iii) exposome principal component analysis (PCA) and hierarchical clustering; (iv) exposome-wide association studies (ExWAS) and variable selection ExWAS; (v) omic data integration by single association and multi-omic analyses; and (vi) post-exposome data analyses to gain biological insight for the exposures, genes or using the Comparative Toxicogenomics Database (CTD) and pathway analysis. Availability: The exposomeShiny source code is freely available on Github at [https://github.com/isglobal-brge/exposomeShiny], Git tag v1.4. The software is also available as a Docker image [https://hub.docker.com/r/brgelab/exposome-shiny], tag v1.4. A user guide with information about the analysis methodologies as well as information on how to use exposomeShiny is freely hosted at [https://isglobal-brge.github.io/exposome_bookdown/].
publishDate 2022
dc.date.none.fl_str_mv 2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/53201
http://dx.doi.org/10.1093/ije/dyab220
url http://hdl.handle.net/10230/53201
http://dx.doi.org/10.1093/ije/dyab220
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Journal of Epidemiology. 2022;51(1):18–26
info:eu-repo/grantAgreement/EC/H2020/874583
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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