National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
PLoS One. 2021 Aug 18;16(8):e0250753. doi: 10.1371/journal.pone.0250753. eCollection 2021.
Flow cytometry is commonly used to evaluate the performance of engineered bacteria. With increasing use of high-throughput experimental methods, there is a need for automated analysis methods for flow cytometry data. Here, we describe FlowGateNIST, a Python package for automated analysis of bacterial flow cytometry data. The main components of FlowGateNIST perform automatic gating to differentiate between cells and background events and then between singlet and multiplet events. FlowGateNIST also includes a method for automatic calibration of fluorescence signals using fluorescence calibration beads. FlowGateNIST is open source and freely available with tutorials and example data to facilitate adoption by users with minimal programming experience.
流式细胞术常用于评估工程细菌的性能。随着高通量实验方法的使用越来越多，人们需要自动化分析流式细胞术数据的方法。在这里，我们描述了 FlowGateNIST，这是一个用于自动化分析细菌流式细胞术数据的 Python 包。FlowGateNIST 的主要组件执行自动门控，以区分细胞和背景事件，然后区分单峰和多峰事件。FlowGateNIST 还包括一种使用荧光校准珠自动校准荧光信号的方法。FlowGateNIST 是开源的，可以免费使用，带有教程和示例数据，以方便有最少编程经验的用户采用。
