Biophysics Program, University of Michigan LS&A, Ann Arbor, MI, USA.
Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
Neuroinformatics. 2022 Jul;20(3):755-764. doi: 10.1007/s12021-022-09573-8. Epub 2022 Mar 5.
The study of neuron morphology requires robust and comprehensive methods to quantify the differences between neurons of different subtypes and animal species. Several software packages have been developed for the analysis of neuron tracing results stored in the standard SWC format. The packages, however, provide relatively simple quantifications and their non-extendable architecture prohibit their use for advanced data analysis and visualization. We developed nGauge, a Python toolkit to support the parsing and analysis of neuron morphology data. As an application programming interface (API), nGauge can be referenced by other popular open-source software to create custom informatics analysis pipelines and advanced visualizations. nGauge defines an extendable data structure that handles volumetric constructions (e.g. soma), in addition to the SWC linear reconstructions, while remaining lightweight. This greatly extends nGauge's data compatibility.
神经元形态学的研究需要强大而全面的方法来量化不同亚型和动物物种神经元之间的差异。已经开发了几个软件包用于分析以标准 SWC 格式存储的神经元追踪结果。然而，这些软件包提供的定量分析相对简单，并且其不可扩展的架构限制了它们用于高级数据分析和可视化。我们开发了 nGauge，这是一个支持神经元形态数据分析的 Python 工具包。作为应用程序编程接口 (API)，nGauge 可以被其他流行的开源软件引用，以创建自定义信息学分析管道和高级可视化。nGauge 定义了一个可扩展的数据结构，它可以处理体积构建（例如，胞体），以及 SWC 线性重建，同时保持轻量级。这极大地扩展了 nGauge 的数据兼容性。
