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An interactive web application for the dissemination of human systems immunology data

BACKGROUND: Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solution...

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Autores principales: Speake, Cate, Presnell, Scott, Domico, Kelly, Zeitner, Brad, Bjork, Anna, Anderson, David, Mason, Michael J., Whalen, Elizabeth, Vargas, Olivia, Popov, Dimitry, Rinchai, Darawan, Jourde-Chiche, Noemie, Chiche, Laurent, Quinn, Charlie, Chaussabel, Damien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474328/
https://www.ncbi.nlm.nih.gov/pubmed/26088622
http://dx.doi.org/10.1186/s12967-015-0541-x
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author Speake, Cate
Presnell, Scott
Domico, Kelly
Zeitner, Brad
Bjork, Anna
Anderson, David
Mason, Michael J.
Whalen, Elizabeth
Vargas, Olivia
Popov, Dimitry
Rinchai, Darawan
Jourde-Chiche, Noemie
Chiche, Laurent
Quinn, Charlie
Chaussabel, Damien
author_facet Speake, Cate
Presnell, Scott
Domico, Kelly
Zeitner, Brad
Bjork, Anna
Anderson, David
Mason, Michael J.
Whalen, Elizabeth
Vargas, Olivia
Popov, Dimitry
Rinchai, Darawan
Jourde-Chiche, Noemie
Chiche, Laurent
Quinn, Charlie
Chaussabel, Damien
author_sort Speake, Cate
collection PubMed
description BACKGROUND: Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators’ interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery. METHODS: State of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples. RESULTS: We provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page (https://gxb.benaroyaresearch.org/dm3/landing.gsp)]. The source code is also available openly [Gene Expression Browser Source Code (https://github.com/BenaroyaResearch/gxbrowser)]. CONCLUSIONS: We have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come.
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spelling pubmed-44743282015-06-20 An interactive web application for the dissemination of human systems immunology data Speake, Cate Presnell, Scott Domico, Kelly Zeitner, Brad Bjork, Anna Anderson, David Mason, Michael J. Whalen, Elizabeth Vargas, Olivia Popov, Dimitry Rinchai, Darawan Jourde-Chiche, Noemie Chiche, Laurent Quinn, Charlie Chaussabel, Damien J Transl Med Research BACKGROUND: Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators’ interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery. METHODS: State of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples. RESULTS: We provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page (https://gxb.benaroyaresearch.org/dm3/landing.gsp)]. The source code is also available openly [Gene Expression Browser Source Code (https://github.com/BenaroyaResearch/gxbrowser)]. CONCLUSIONS: We have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come. BioMed Central 2015-06-19 /pmc/articles/PMC4474328/ /pubmed/26088622 http://dx.doi.org/10.1186/s12967-015-0541-x Text en © Speake et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Speake, Cate
Presnell, Scott
Domico, Kelly
Zeitner, Brad
Bjork, Anna
Anderson, David
Mason, Michael J.
Whalen, Elizabeth
Vargas, Olivia
Popov, Dimitry
Rinchai, Darawan
Jourde-Chiche, Noemie
Chiche, Laurent
Quinn, Charlie
Chaussabel, Damien
An interactive web application for the dissemination of human systems immunology data
title An interactive web application for the dissemination of human systems immunology data
title_full An interactive web application for the dissemination of human systems immunology data
title_fullStr An interactive web application for the dissemination of human systems immunology data
title_full_unstemmed An interactive web application for the dissemination of human systems immunology data
title_short An interactive web application for the dissemination of human systems immunology data
title_sort interactive web application for the dissemination of human systems immunology data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4474328/
https://www.ncbi.nlm.nih.gov/pubmed/26088622
http://dx.doi.org/10.1186/s12967-015-0541-x
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