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ENIGMA-Viewer:荟萃分析中用于传达效应量的交互式可视化策略。

ENIGMA-Viewer: interactive visualization strategies for conveying effect sizes in meta-analysis.

作者信息

Zhang Guohao, Kochunov Peter, Hong Elliot, Kelly Sinead, Whelan Christopher, Jahanshad Neda, Thompson Paul, Chen Jian

机构信息

Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, 21250, MD, USA.

Maryland Psychiatric Research Center, University of Maryland, Baltimore, 55 Wade Ave, Baltimore, 21228, MD, USA.

出版信息

BMC Bioinformatics. 2017 Jun 6;18(Suppl 6):253. doi: 10.1186/s12859-017-1634-8.

Abstract

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 ).

摘要

背景

全球范围内的大脑研究合作项目,如ENIGMA(通过元分析增强神经影像遗传学)联盟,开始大量收集数据并使用统一方案进行元分析。在大脑科学家之间有效地交流研究结果具有重要的战略意义。传统的图表无法传达大脑结构的复杂形状,而这些形状对于理解分析结果统计至关重要。使用交互式可视化策略可以解决这些问题,这种策略能够将那些统计数据与大脑结构相联系,以便提供一个更好的界面来理解大脑研究结果。

结果

我们展示了ENIGMA-Viewer,这是一个基于网络的交互式可视化工具,供大脑科学家比较多个研究中关于标准化感兴趣区域(ROI)的元分析结果的效应量等统计数据。该工具融合了诸如聚焦+上下文和视觉数据融合等可视化设计原则,以使用户能够更好地理解大脑结构上的统计数据。通过案例研究讨论了使用近期研究数据的三个示例,以证明该工具的可用性。

结论

ENIGMA-Viewer通过有效的可视化设计支持大脑研究结果的展示和交流。通过将统计数据和结构的可视化相联系,用户能够对所呈现的数据获得更多见解,否则这些见解很难获得。ENIGMA-Viewer是一个开源工具,其源代码和示例数据可通过NITRC网站(http://www.nitrc.org/projects/enigmaviewer_20)公开获取。该工具也可直接在线访问(http://enigma-viewer.org)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aff3/5471941/80b7fca8c231/12859_2017_1634_Fig1_HTML.jpg

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