Center for Neural Informatics, Structures & Plasticity, George Mason University, Fairfax, VA, USA.
Allen Institute for Brain Science, Seattle, WA, USA.
Nat Commun. 2023 Nov 16;14(1):7429. doi: 10.1038/s41467-023-42931-x.
Digital reconstructions provide an accurate and reliable way to store, share, model, quantify, and analyze neural morphology. Continuous advances in cellular labeling, tissue processing, microscopic imaging, and automated tracing catalyzed a proliferation of software applications to reconstruct neural morphology. These computer programs typically encode the data in custom file formats. The resulting format heterogeneity severely hampers the interoperability and reusability of these valuable data. Among these many alternatives, the SWC file format has emerged as a popular community choice, coalescing a rich ecosystem of related neuroinformatics resources for tracing, visualization, analysis, and simulation. This report presents a standardized specification of the SWC file format. In addition, we introduce xyz2swc, a free online service that converts all 26 reconstruction formats (and 72 variations) described in the scientific literature into the SWC standard. The xyz2swc service is available open source through a user-friendly browser interface ( https://neuromorpho.org/xyz2swc/ui/ ) and an Application Programming Interface (API).
数字重建为存储、共享、建模、量化和分析神经形态学提供了一种准确可靠的方法。细胞标记、组织处理、显微镜成像和自动跟踪技术的不断进步,推动了神经形态学重建软件应用程序的大量涌现。这些计算机程序通常使用自定义文件格式来编码数据。由此产生的格式异构性严重阻碍了这些有价值数据的互操作性和可重用性。在众多替代方案中,SWC 文件格式已成为一种流行的社区选择,汇聚了丰富的相关神经信息学资源,用于追踪、可视化、分析和模拟。本报告提出了 SWC 文件格式的标准化规范。此外,我们还引入了 xyz2swc,这是一项免费的在线服务,可将科学文献中描述的所有 26 种重建格式(和 72 种变体)转换为 SWC 标准。xyz2swc 服务通过用户友好的浏览器界面(https://neuromorpho.org/xyz2swc/ui/)和应用程序编程接口(API)以开源的方式提供。