Data analysis in flow cytometry involves the use of software to interpret the fluorescence intensity data collected from the cells. This process typically includes gating, which involves selecting specific cell populations based on their size, granularity, and marker expression. Advanced analysis techniques, such as high-dimensional data analysis and machine learning, are increasingly being applied to flow cytometry data to uncover complex patterns and relationships.
