Advancing Unmixing Algorithms in Spectral Flow Cytometry 9419

Abstract Description Unlike conventional flow cytometry, which collects only a discrete portion of the emission spectrum using single filters per fluorochrome, spectral flow cytometry captures the full spectrum for all fluorochromes on each cell using multiple detectors. Consequently, spectral flow cytometry requires more complex methods than compensation to distinguish fluorochromes. Spectral flow cytometry employs spectral unmixing—a mathematical technique that separates signals from different fluorochromes, producing an unmixing matrix that estimates the abundance of each fluorochrome on a cell. Achieving accurate results necessitates a good reference control and an understanding of the unmixing algorithm used by the software. The accuracy of the results directly depends on how well the algorithm reflects the underlying physics of signal formation. Here, we will explore the current unmixing algorithms in use and highlight how the CytoFLEX mosaic Spectral Detection Module enhances performance in distinguishing true signals from background noise, which is particularly useful where the signal-to-noise ratio is low. Funding Sources N/A Topic Categories Technological Innovations in Immunology (TECH)