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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: Mar 16, 2026

An Automated Method to Perform The In Vitro Micronucleus Assay using Multispectral Imaging Flow Cytometry

An Automated Method to Perform The In Vitro Micronucleus Assay using Multispectral Imaging Flow Cytometry

Published on: May 13, 2019

Novel statistical approach for evaluating flow cytometric in vitro micronucleus data.

J P Wojciechowski¹, C R Gleason², D J Roberts^1,3

¹Drug Safety Evaluation, Department of Genetic Toxicology, Bristol-Myers Squibb Company, New Brunswick, New Jersey.

Environmental and Molecular Mutagenesis

|August 23, 2016

Summary

Traditional statistical tests for in vitro micronucleus data are overly sensitive with large sample sizes from flow cytometry. A new "z' factor" statistic, combined with biological criteria, offers a more meaningful analysis of genotoxicity experiments.

Keywords:

flow cytometric analysis in vitro micronucleus statistical analysis z′ factor

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Area of Science:

Toxicology
Genetics
Biostatistics

Background:

Current statistical methods for in vitro micronucleus data analysis are designed for small sample sizes.
Flow cytometry enables evaluation of significantly larger cell numbers, leading to smaller variance estimates.
Traditional tests applied to large datasets can yield statistically significant results lacking biological relevance.

Purpose of the Study:

To investigate alternative statistical methods for analyzing in vitro micronucleus data from large sample sizes.
To compare the performance of traditional, alternative, and a novel statistical approach (z-score).
To determine a more biologically meaningful method for assessing genotoxicity from high-throughput screening.

Main Methods:

Analysis of 95 in vitro micronucleus experiments conducted between 2011-2013.
Comparison of recommended, widely used, and sample-size independent statistical tests.
Evaluation of the "z-score" (z-factor) as a metric for identifying 'hits' in high-throughput screening.
Integration of the z-score with historical vehicle control data to establish biological meaningfulness.

Main Results:

Traditional and alternative statistical methods resulted in 42-68% of experiments showing statistically significant outcomes (p < 0.05).
The z-score statistic reduced the number of significant calls to 27%.
Combining the z-score with biological criteria restored the original positive frequency of 19%.

Conclusions:

Traditional statistical tests may be overly sensitive for large sample sizes generated by flow cytometry in micronucleus assays.
The z-score offers a more appropriate and less sensitive tool for analyzing large-scale genotoxicity data.
A combination of the z-score and biological relevance criteria is recommended for robust analysis of in vitro micronucleus data.