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Updated: Jan 23, 2026

Phospho Flow Cytometry with Fluorescent Cell Barcoding for Single Cell Signaling Analysis and Biomarker Discovery
Published on: October 4, 2018
Development, application and computational analysis of high-dimensional fluorescent antibody panels for single-cell
Jolanda Brummelman1, Claudia Haftmann2, Nicolás Gonzalo Núñez2
1Laboratory of Translational Immunology, Humanitas Clinical and Research Center, Rozzano, Milan, Italy.
Insights
This study simplifies 28-color flow cytometry panel design by providing a reference map for fluorescence spreading errors. This advance accelerates high-dimensional single-cell analysis, particularly for immune system characterization.
Area of Science:
- Immunology
- Cell Biology
- Biotechnology
Background:
- Single-cell analysis is revolutionizing biological research, especially immunology.
- Flow cytometry offers high-throughput single-cell analysis and has been extended to 28 colors.
- Limitations of flow cytometry include autofluorescence and spreading error (SE), hindering dim marker detection and panel design.
Purpose of the Study:
- To describe the steps for achieving 28-color flow cytometry measurement capability.
- To provide a reference map of fluorescence spreading errors in a 28-color space.
- To offer detailed computational analysis instructions for complex flow cytometry data.
Main Methods:
- Development of a 28-color antibody panel.
- Creation of a fluorescence spreading error reference map.
- Application of computational algorithms (PhenoGraph, FlowSOM) for data analysis.
Main Results:
- Successful implementation of 28-color flow cytometry.
- A comprehensive reference map simplifying panel design and predicting antibody combination success.
- Detailed computational analysis protocols for high-dimensional data.
Conclusions:
- The described approach facilitates the design and analysis of complex, high-dimensional flow cytometry panels.
- This method streamlines the characterization of the immune system and other biological systems.
- The protocol is efficient, taking only a few days to complete.
Abstract:
The interrogation of single cells is revolutionizing biology, especially our understanding of the immune system. Flow cytometry is still one of the most versatile and high-throughput approaches for single-cell analysis, and its capability has been recently extended to detect up to 28 colors, thus approaching the utility of cytometry by time of flight (CyTOF). However, flow cytometry suffers from autofluorescence and spreading error (SE) generated by errors in the measurement of photons mainly at red and far-red wavelengths, which limit barcoding and the detection of dim markers. Consequently, development of 28-color fluorescent antibody panels for flow cytometry is laborious and time consuming. Here, we describe the steps that are required to successfully achieve 28-color measurement capability. To do this, we provide a reference map of the fluorescence spreading errors in the 28-color space to simplify panel design and predict the success of fluorescent antibody combinations. Finally, we provide detailed instructions for the computational analysis of such complex data by existing, popular algorithms (PhenoGraph and FlowSOM). We exemplify our approach by designing a high-dimensional panel to characterize the immune system, but we anticipate that our approach can be used to design any high-dimensional flow cytometry panel of choice. The full protocol takes a few days to complete, depending on the time spent on panel design and data analysis.
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