Automated analysis of bacterial flow cytometry data with FlowGateNIST

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.

Automated summary

Flow cytometry is widely used for evaluating engineered bacteria, requiring automated analysis methods. FlowGateNIST, a Python package, offers automatic analysis for bacterial flow cytometry data, including automatic gating and fluorescence signal calibration. This open source tool aims to support users with minimal programming experience.