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cytometree: A binary tree algorithm for automatic gating in cytometry analysis.

Daniel Commenges^1,2, Chariff Alkhassim^1,2, Raphael Gottardo³

¹Inserm, Bordeaux Population Health Research Center, UMR 1219, INRIA SISTM, University of Bordeaux, ISPED, 33000, Bordeaux, France.

Cytometry. Part a : the Journal of the International Society for Analytical Cytology

|October 3, 2018

Summary

This summary is machine-generated.

Automated flow cytometry analysis is crucial for complex cell identification. Cytometree, a new unsupervised algorithm, accurately identifies cell populations, outperforming existing methods in speed and precision.

Keywords:

automated gating binary tree flow cytometry mixture of distributions

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Area of Science:

Biotechnology
Computational Biology
Immunology

Background:

Flow cytometry is essential for single-cell protein quantification and immunophenotyping.
Manual analysis of complex flow cytometry data is subjective and time-consuming.
Automated methods are needed to handle increasing experimental complexity.

Purpose of the Study:

To introduce cytometree, a novel unsupervised algorithm for automated cell population identification (gating) in flow cytometry.
To provide an objective and efficient alternative to manual data analysis.

Main Methods:

Cytometree constructs a binary tree where nodes represent cell subpopulations.
Marker distributions at each node are modeled using mixtures of normal distributions.
A model selection procedure based on Akaike information criteria guides node splitting.

Main Results:

Cytometree demonstrated superior performance compared to state-of-the-art unsupervised algorithms on benchmark datasets.
The algorithm outperformed the best open-source alternative on a Human Immunology Project Consortium T-cell panel.
Cytometree achieved the shortest computation time among tested unsupervised algorithms.

Conclusions:

Cytometree offers an accurate and efficient solution for automated flow cytometry data analysis.
The algorithm effectively addresses the challenges posed by complex, high-dimensional cytometry experiments.
Cytometree represents a significant advancement in computational cytometry for immunological research.