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Related Concept Videos

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: May 20, 2025

Purification of Specific Cell Population by Fluorescence Activated Cell Sorting FACS
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Purification of Specific Cell Population by Fluorescence Activated Cell Sorting FACS

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Uncertainty Quantification in Flow Cytometry Using a Cell Sorter.

Amudhan Krishnaswamy-Usha1,2, Gregory A Cooksey3, Paul N Patrone1

  • 1Applied and Computational Mathematics Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology
|March 26, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel cytometry experiment to separate instrument noise from biological variation. The method quanties instrument-specific variability without assumptions about noise sources.

Keywords:
FACSbeadsgatingsortinguncertainty quantification

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Area of Science:

  • Flow cytometry
  • Instrumentation
  • Biophysical measurement

Background:

  • Distinguishing instrument noise from population variance is a fundamental challenge in cytometry.
  • Current methods struggle to isolate the precise contribution of instrument variability to total measured variation.
  • The inability to re-measure the same particle multiple times complicates noise assessment.

Purpose of the Study:

  • To develop a method for disentangling instrument-specific variation from population variance in cytometry.
  • To provide a quantitative estimate of cumulative instrument-induced variability.
  • To enable noise estimation on cytometers lacking cell sorting capabilities.

Main Methods:

  • A novel experiment using a cell sorter to isolate and re-measure a subset of particles.
  • Analysis of the distribution of post-sort measurements to estimate instrument variability.
  • Application of 'local affine transformations' to transfer noise estimates to non-sorter cytometers.

Main Results:

  • Demonstrated a method to estimate instrument-specific variation without assumptions on noise sources.
  • Successfully quantified instrument noise across multiple cytometers and bead types.
  • Showcased the transferability of noise estimates to different cytometer platforms.

Conclusions:

  • The proposed experimental approach effectively separates instrument noise from biological variation in cytometry.
  • The method provides a robust estimation of instrument-induced variability, applicable to various cytometers.
  • Understanding and quantifying instrument noise is crucial for optimizing data analysis and classification in flow cytometry.