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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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Updated: Jun 14, 2025

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Published on: June 26, 2018

ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.

Jing Sun¹, Desmond Choy², Nicolas Sompairac²

¹Centre for Inflammation Biology and Cancer Immunology & Peter Gorer Department of Immunobiology, King's College London, London, United Kingdom.

|September 6, 2024

Summary

ImmCellTyper is a new toolkit for analyzing mass cytometry data, simplifying complex immune cell profiling. It uses a semi-supervised clustering tool, BinaryClust, to accurately identify cell types, aiding clinical research.

Keywords:

CyTOF computational biology computational framework human immune profiling immunology inflammation systems biology

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Last Updated: Jun 14, 2025

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Published on: June 26, 2018

Sample Preparation for Mass Cytometry Analysis

Sample Preparation for Mass Cytometry Analysis

Published on: April 29, 2017

Isolation and Staining of Mouse Skin Keratinocytes for Cell Cycle Specific Analysis of Cellular Protein Expression by Mass Cytometry

Isolation and Staining of Mouse Skin Keratinocytes for Cell Cycle Specific Analysis of Cellular Protein Expression by Mass Cytometry

Published on: May 9, 2019

Area of Science:

Immunology
Computational Biology
Bioinformatics

Background:

Mass cytometry (e.g., CyTOF) generates high-dimensional single-cell data for immune monitoring.
Analyzing large cytometry by time-of-flight (CyTOF) datasets presents significant computational challenges.
Existing analytical tools may lack the accuracy or efficiency needed for complex immune profiling.

Purpose of the Study:

To introduce ImmCellTyper, a novel toolkit for comprehensive CyTOF data analysis.
To present BinaryClust, a semi-supervised clustering tool for automated cell type identification.
To provide a user-friendly workflow for quality control, cell characterization, and differential analysis of CyTOF data.

Main Methods:

Development of ImmCellTyper, a toolkit integrating semi-supervised clustering (BinaryClust) and data analysis modules.
Benchmarking BinaryClust against existing tools using large CyTOF datasets (approx. 4 million cells).
Implementation of a five-step workflow: batch correction, QC, cell lineage identification, subset investigation, and differential analysis.

Main Results:

BinaryClust demonstrates superior accuracy and speed compared to other clustering tools.
The performance of BinaryClust matches that of manual gating by human experts.
ImmCellTyper provides a comprehensive suite of tools for various stages of CyTOF data analysis.

Conclusions:

ImmCellTyper offers an effective solution for the analytical challenges posed by high-dimensional CyTOF data.
The toolkit accurately deconvolutes major cell lineages using biological knowledge and semi-supervised learning.
ImmCellTyper facilitates advanced immune profiling by enabling discovery of novel cell subsets and differential analysis.