Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, USA.
Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Philadelphia, PA, USA.
Biostatistics. 2019 Apr 1;20(2):218-239. doi: 10.1093/biostatistics/kxx068.
Neuroconductor (https://neuroconductor.org) is an open-source platform for rapid testing and dissemination of reproducible computational imaging software. The goals of the project are to: (i) provide a centralized repository of R software dedicated to image analysis, (ii) disseminate software updates quickly, (iii) train a large, diverse community of scientists using detailed tutorials and short courses, (iv) increase software quality via automatic and manual quality controls, and (v) promote reproducibility of image data analysis. Based on the programming language R (https://www.r-project.org/), Neuroconductor starts with 51 inter-operable packages that cover multiple areas of imaging including visualization, data processing and storage, and statistical inference. Neuroconductor accepts new R package submissions, which are subject to a formal review and continuous automated testing. We provide a description of the purpose of Neuroconductor and the user and developer experience.
Neuroconductor（https://neuroconductor.org）是一个用于快速测试和传播可重复计算成像软件的开源平台。该项目的目标是：（i）提供一个专门用于图像分析的 R 软件中央存储库，（ii）快速发布软件更新，（iii）通过详细的教程和短期课程培训大量不同背景的科学家，（iv）通过自动和手动质量控制提高软件质量，以及（v）促进图像数据分析的可重复性。基于编程语言 R（https://www.r-project.org/），Neuroconductor 从 51 个可互操作的软件包开始，涵盖了包括可视化、数据处理和存储以及统计推断在内的多个成像领域。Neuroconductor 接受新的 R 软件包提交，这些提交需要经过正式审查和持续的自动测试。我们提供了 Neuroconductor 的目的以及用户和开发者体验的描述。
