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Flow Cytometry01:23

Flow Cytometry

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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
05:12

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

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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.

Plos One
|November 13, 2024
PubMed
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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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.