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Related Concept Videos

Flow Cytometry01:23

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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Standardization of Transfer across Labs between Flow Cytometers for Detection of Lymphocytes in Japanese Encephalitis Vaccinated Children
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Flow cytometry data standards.

Josef Spidlen1, Parisa Shooshtari, Tobias R Kollmann

  • 1Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada. rbrinkman@bccrc.ca.

BMC Research Notes
|March 10, 2011
PubMed
Summary
This summary is machine-generated.

New flow cytometry data standards complement the existing Flow Cytometry Standard (FCS). These standards, including MIFlowCyt and Gating-ML, improve data sharing and analysis for flow cytometry experiments.

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Area of Science:

  • Biotechnology
  • Bioinformatics
  • Data Science

Background:

  • Flow cytometry is a crucial technique for analyzing cells.
  • The original Flow Cytometry Standard (FCS) has limitations in capturing comprehensive data and metadata.
  • Recent advancements address these shortcomings with new data standards.

Purpose of the Study:

  • To introduce and exemplify recently developed data standards for flow cytometry.
  • To demonstrate how these standards facilitate standardized reporting of FCM data, analysis, and results.

Main Methods:

  • Development of new data standards by the Data Standards Task Force (DSTF) of ISAC.
  • Introduction of Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) for reporting experimental details.
  • Development of Gating-ML for describing data analysis and Classification Results File Format for reporting clustering outcomes.
  • Creation of Archival Cytometry Standard to bundle experimental data and components.

Main Results:

  • MIFlowCyt is being adopted by publishers for manuscript submissions and reviewed for compliance.
  • Gating-ML and Classification Results File Format enable standardized capture of analysis steps and results.
  • The Archival Cytometry Standard integrates data with descriptive components.
  • A practical example is provided showcasing the application of these standards for comprehensive FCM data reporting.

Conclusions:

  • New flow cytometry data standards enhance scientific collaboration and validation.
  • These standards are being integrated into software and repositories, promoting data understanding and reuse.