Williams Eleanor, Moore Josh, Li Simon W, Rustici Gabriella, Tarkowska Aleksandra, Chessel Anatole, Leo Simone, Antal Bálint, Ferguson Richard K, Sarkans Ugis, Brazma Alvis, Salas Rafael E Carazo, Swedlow Jason R
Centre for Gene Regulation & Expression & Division of Computational Biology, University of Dundee, Dundee, Scotland, UK.
European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, United Kingdom.
Nat Methods. 2017 Aug;14(8):775-781. doi: 10.1038/nmeth.4326. Epub 2017 Jun 19.
Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links data from several imaging modalities, including high-content screening, super-resolution and time-lapse microscopy, digital pathology, public genetic or chemical databases, and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.
获取原始研究数据对科学进步至关重要。为了扩展社区存储库支持的数据类型,我们构建了一个原型图像数据资源(IDR),它收集并整合了通过多种不同成像方式获取的成像数据。IDR连接来自多种成像方式的数据,包括高内涵筛选、超分辨率和延时显微镜、数字病理学、公共遗传或化学数据库,以及使用受控本体表达的细胞和组织表型。通过这种整合,IDR促进了基因网络分析,并揭示了单个研究无法获得的功能相互作用。为了实现重新分析,我们还基于Jupyter笔记本建立了一个计算资源,允许远程访问整个IDR。IDR也是一个开源平台,其他人可以用它来发布自己的图像数据。因此,IDR既提供了一种新颖的在线资源,也提供了一种促进和扩展科学图像数据发布与重新分析的软件基础设施。