Abstract
BackgroundSystems 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.MethodsState 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.ResultsWe 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)].ConclusionsWe 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.
Highlights
Systems immunology approaches have proven invaluable in translational research settings
Speake et al J Transl Med (2015) 13:196 example, more than 37,000 microarray or RNAseq studies are available in the NCBI Gene Expression Omnibus (GEO) repository [1], corresponding to more than 800,000 individual transcriptome profiles
These sets were selected from studies currently available in NCBI’s Gene Expression Omnibus (GEO) [26]
Summary
Systems immunology approaches have proven invaluable in translational research settings. Systems studies rely on high throughput profiling technologies to measure the abundance or activity of all the constituents of a given biological system. The data associated with each study, which tend to be underutilized beyond publication of primary results, potentially constitutes an invaluable resource when reinterpreted alongside other related datasets. It can provide context for the interpretation of newly generated data, and when analyzed collectively can yield insights that could not otherwise be obtained from the analysis of individual datasets
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