As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized.
翻译:随着照相像素阵列的扩大和速度的加快,以及光学显微镜技术的改进,常规光显微镜中获取的数据数量急剧增加。 在单分子一级,分析涉及多个步骤,并可能迅速变得计算昂贵,有时在办公室工作站上难以解决。 复杂的简单软件可以给新用户的进入设置高的启动障碍。 在这里, 我们重新开发我们的定量单分子分析程序, 将其发展成最优化和可扩展的 Python 程序, 并配有图形用户和命令线的实施, 以便于本地机器和远程集群使用。 我们显示, 其性能与以前的 MATLAB 执行相同, 但却运行一个更快的量级级。 我们用挑战性数据测试数据, 显示其性能与最新分析平台的状态相当。 我们显示, 代码可以提取单一报告染色分子分子的频强度值, 并且使用这些工具, 估计分子的微缩缩缩缩缩缩图和细胞复制件数, 从而使得我们能够对常规数据进行比较分析。 最后, 我们的常规分析中的数据可以用来分析。