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Abstract
High-content cytometry is an important technique in clinical research, producing data that is rich and complex to analyze. The resulting clusters of cells must be profiled to determine their role and function, and analyzed to identify changes in cell frequency or marker intensity. The heat map is the most suitable tool for presenting this information in a synthetic way. However, its construction must be adapted to the information and the objective. Here we describe the step-by-step construction of heat maps of marker intensity and cell frequency using Excel, Phantasus or R, including the conversion of numbers to colors and the organization of rows and columns. Researchers who master these steps will be able to correctly interpret heat maps and derive the most benefit from high-content cytometry.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
* https://i-cyto.github.io/build-heatmaps-imp2/
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