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Flow Cytometry

Flow Cytometry

The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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Related Experiment Video

Updated: Jun 7, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

EasyFlow: An open-source, user-friendly cytometry analyzer with graphic user interface (GUI).

Yitong Ma¹, Inbal Eizenberg-Magar², Yaron Antebi²

¹Department of Bioengineering, Stanford University, Stanford, California, United States of America.

|November 13, 2024

Summary

This summary is machine-generated.

EasyFlow is a new, open-source graphic user interface for flow cytometry analysis. This user-friendly software requires no coding and runs locally on any platform, benefiting both new and advanced researchers.

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Last Updated: Jun 7, 2025

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Area of Science:

Biotechnology
Cell Biology
Immunology

Background:

Flow cytometry is a powerful technique for quantitative single-cell analysis, widely applied in immunology and increasingly in developmental biology, systems biology, and microbiology.
Standardized data exchange is facilitated by the common FCS file format.
Existing flow cytometry analysis software presents limitations, including high cost, complex installation/coding requirements, or scalability issues for large datasets.

Purpose of the Study:

To develop an accessible, open-source graphic user interface (GUI) for flow cytometry data analysis.
To provide a user-friendly tool that does not require prior coding experience.
To offer a customizable platform for both novice and advanced users.

Main Methods:

Development of EasyFlow, an open-source GUI for flow cytometry analysis.
Implementation using Matlab and Python (EasyFlowQ).
Cross-platform compatibility (Windows, MacOS, Linux) for local installation and use.

Main Results:

EasyFlow provides an intuitive interface for flow cytometry data analysis.
The software is installable and runnable locally across major operating systems without coding prerequisites.
The Python version (EasyFlowQ) supports customization and contribution by advanced users via Matplotlib and Qt.

Conclusions:

EasyFlow democratizes flow cytometry data analysis by offering a simple, locally installable, and open-source solution.
The tool caters to users with varying levels of coding expertise, from beginners to advanced researchers.
EasyFlow serves as a valuable, adaptable platform for the broader scientific community.