Accurate data analysis in flow cytometry necessitates the identification and removal of events where two or more cells are measured as a single event. These aggregated cells, often referred to as multiplets or doublets, can skew experimental results by presenting artificially inflated signal intensities for various markers. An example of such an occurrence is when two cells, each expressing a moderate level of a particular protein, pass through the laser beam simultaneously, registering as a single event with a high level of protein expression.
The elimination of these composite events is crucial for reliable interpretation of flow cytometric data. Their presence can lead to misrepresentation of cell populations and inaccurate quantification of cellular characteristics. Historically, researchers have employed various techniques to minimize these events, ranging from optimized sample preparation protocols to sophisticated gating strategies. Achieving this exclusion improves the accuracy and reproducibility of experimental outcomes, ultimately bolstering the integrity of scientific findings.
