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

Cate Speake (1) , Scott Presnell (1) , Kelly Domico (1) , Brad Zeitner (1) , Anna Bjork (1) , David Anderson (1) , Michael J. Mason (1) , Elizabeth Whalen (1) , Olivia Vargas (1) , Dimitry Popov (1) , Darawan Rinchai (2) , Noemie Jourde-Chiche (3) , Laurent Chiche (4) , Charlie Quinn (1) , Damien Chaussabel (1, 2)

1 Systems Immunology Laboratory
2 Sidra Medical and Research Center
3 AMU - Aix Marseille Université
4 Department of Internal Medicine and Infectious Diseases

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.

Mots clés: Transcriptomics; Software; Immunology; Bioinformatics; TRANSCRIPTIONAL SIGNATURE; EXPRESSION; BIOLOGY; INFLUENZA; CIRCUITS; CELLS; ONSET

Domaines: Sciences du Vivant [q-bio]; Immunologie; Bio-Informatique, Biologie Systémique [q-bio.QM]

Cate Speake, Scott Presnell, Kelly Domico, Brad Zeitner, Anna Bjork, et al.. An interactive web application for the dissemination of human systems immunology data. Journal of Translational Medicine, 2015, ⟨10.1186/s12967-015-0541-x⟩. ⟨hal-01202559⟩