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

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  • dc.contributor.author Escriba-Montagut, Xavier
  • dc.contributor.author Basagaña Flores, Xavier
  • dc.contributor.author Vrijheid, Martine
  • dc.contributor.author González, Juan Ramón
  • dc.date.accessioned 2022-05-23T06:34:57Z
  • dc.date.available 2022-05-23T06:34:57Z
  • dc.date.issued 2022
  • dc.description.abstract 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/].
  • dc.description.sponsorship 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.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Escriba-Montagut X, Basagaña X, Vrijheid M, Gonzalez JR. Software Application Profile: exposomeShiny-a toolbox for exposome data analysis. International Journal of Epidemiology. 2022;51(1):18–26. DOI: 10.1093/ije/dyab220
  • dc.identifier.doi http://dx.doi.org/10.1093/ije/dyab220
  • dc.identifier.issn 0300-5771
  • dc.identifier.uri http://hdl.handle.net/10230/53201
  • dc.language.iso eng
  • dc.publisher Oxford University Press
  • dc.relation.ispartof International Journal of Epidemiology. 2022;51(1):18–26
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/874583
  • dc.rights © 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.com
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
  • dc.subject.keyword Exposome
  • dc.subject.keyword Shiny
  • dc.subject.keyword R
  • dc.subject.keyword Graphical user interface
  • dc.subject.keyword Toolbox
  • dc.subject.keyword Epidemiology
  • dc.subject.keyword ExWAS
  • dc.subject.keyword Biological insights
  • dc.subject.keyword Omics-exposures association
  • dc.title Software Application Profile: exposomeShiny-a toolbox for exposome data analysis
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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Articles (Barcelona Institute for Global Health (ISGlobal) – Campus Mar)
Articles (Departament de Medicina i Ciències de la Vida)
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