A Deeper Dive into Flow Cytometry Data

In recent years, flow cytometry has been advanced by innovations in high-resolution optical analyses of novel fluorochromes. As a result, an increasing number of cellular parameters can now be acquired from limited clinical sample volumes. Various approaches to mining this high-dimensional data are available that extend beyond traditional hierarchical gating and t-distributed stochastic neighbor embedding (t-SNE) to visualize subpopulations. One such approach from AstroLabe, utilizes Multi-dimensional Scaling (MDS) algorithms to identify statistically significant trends across cohorts. FlowMetric is proud to be offering this analytical service to our clients to help maximize the potential of their flow cytometry data.

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