Interactive visualization, Meta-analysis, Effect size, Diffusion tensor imaging, Comparative studies.
US National Science Foundation. US National Institutes of Health.
Background: Global scale brain research collaborations such as the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium are beginning to collect data in large quantity and to conduct meta-analyses using uniformed protocols. It becomes strategically important that the results can be communicated among brain scientists effectively. Traditional graphs and charts failed to convey the complex shapes of brain structures which are essential to the understanding of the result statistics from the analyses. These problems could be addressed using interactive visualization strategies that can link those statistics with brain structures in order to provide a better interface to understand brain research results.
Results: We present ENIGMA-Viewer, an interactive web-based visualization tool for brain scientists to compare statistics such as effect sizes from meta-analysis results on standardized ROIs (regions-of-interest) across multiple studies. The tool incorporates visualization design principles such as focus+context and visual data fusion to enable users to better understand the statistics on brain structures. To demonstrate the usability of the tool, three examples using recent research data are discussed via case studies.
Conclusions: ENIGMA-Viewer supports presentations and communications of brain research results through effective visualization designs. By linking visualizations of both statistics and structures, users can gain more insights into the presented data that are otherwise difficult to obtain. ENIGMA-Viewer is an open-source tool, the source code and sample data are publicly accessible through the NITRC website (http://www.nitrc.org/projects/ enigmaviewer_20). The tool can also be directly accessed online (http://enigma-viewer.org).
Zhang G, Kochunov P, Hong E, Kelly S, Whelan C, Jahanshad N, Thompson P, Chen J. ENIGMA-Viewer: interactive visualization strategies for conveying effect sizes in meta-analysis. BMC Bioinformatics. 2017;18(Suppl. 6):253
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