ViPAR: a software platform for the Virtual Pooling and Analysis of Research Data.
ViPAR: a software platform for the Virtual Pooling and Analysis of Research Data.
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DOI：
10.1093/ije/dyv193
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发表时间：
2016-04
影响因子：
7.7
通讯作者：
International Collaboration for Autism Registry Epidemiology
中科院分区：
文献类型：
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作者：
Carter KW;Francis RW;Carter KW;Francis RW;Bresnahan M;Gissler M;Grønborg TK;Gross R;Gunnes N;Hammond G;Hornig M;Hultman CM;Huttunen J;Langridge A;Leonard H;Newman S;Parner ET;Petersson G;Reichenberg A;Sandin S;Schendel DE;Schalkwyk L;Sourander A;Steadman C;Stoltenberg C;Suominen A;Surén P;Susser E;Sylvester Vethanayagam A;Yusof Z;International Collaboration for Autism Registry Epidemiology
背景：探索疾病决定因素的研究需要足够的统计能力来检测有意义的影响。样本量通常通过集中汇集位于不同位置的数据集来增加，尽管道德，隐私和数据所有权问题通常会阻碍这一过程。因此，迫切需要采取有助于分享研究数据的方法，这些方法既要与这些问题相一致，又要允许进行灵活和详细的统计分析。我们为研究数据的虚拟汇集和分析（ViPAR）创建了一个软件平台，该平台采用免费和开源方法，为研究人员提供一个基于网络的平台，以分析位于不同位置的数据集。 方法：数据库联合允许从中央位置对远程数据集进行受控访问。安全外壳协议允许通过不安全的网络在设备之间安全地交换数据。ViPAR将这些免费技术结合到一个解决方案中，该解决方案促进了“虚拟池”，其中数据可以临时池化到计算机内存中，并可用于分析，而无需永久的中央存储。 结果如下：在ViPAR基础设施中，远程站点在其站点托管的数据库中管理自己的统一研究数据集，而中央服务器托管数据联合组件和安全分析门户。启动分析时，将从每个远程站点检索所请求的数据，并在中心站点虚拟汇集。然后通过统计软件对数据进行分析，分析完成后，将分析结果返回给用户，并从内存中删除虚拟合并的数据。 结论：ViPAR是一个安全、灵活且功能强大的分析平台，基于开源技术，目前被大型国际财团使用，并在[ www.example.com ]公开提供http://bioinformatics.childhealthresearch.org.au/software/vipar/。
Background: Research studies exploring the determinants of disease require sufficient statistical power to detect meaningful effects. Sample size is often increased through centralized pooling of disparately located datasets, though ethical, privacy and data ownership issues can often hamper this process. Methods that facilitate the sharing of research data that are sympathetic with these issues and which allow flexible and detailed statistical analyses are therefore in critical need. We have created a software platform for the Virtual Pooling and Analysis of Research data (ViPAR), which employs free and open source methods to provide researchers with a web-based platform to analyse datasets housed in disparate locations. Methods: Database federation permits controlled access to remotely located datasets from a central location. The Secure Shell protocol allows data to be securely exchanged between devices over an insecure network. ViPAR combines these free technologies into a solution that facilitates ‘virtual pooling’ where data can be temporarily pooled into computer memory and made available for analysis without the need for permanent central storage. Results: Within the ViPAR infrastructure, remote sites manage their own harmonized research dataset in a database hosted at their site, while a central server hosts the data federation component and a secure analysis portal. When an analysis is initiated, requested data are retrieved from each remote site and virtually pooled at the central site. The data are then analysed by statistical software and, on completion, results of the analysis are returned to the user and the virtually pooled data are removed from memory. Conclusions: ViPAR is a secure, flexible and powerful analysis platform built on open source technology that is currently in use by large international consortia, and is made publicly available at [ http://bioinformatics.childhealthresearch.org.au/software/vipar/ ].