Improved compensation in flow cytometry by multivariable optimization

Authors

  • István P. Sugár,

    Corresponding author
    1. Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, New York, New York 10029
    • Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, New York, NY 10029
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  • Joanna González-Lergier,

    1. Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, New York, New York 10029
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  • Stuart C. Sealfon

    1. Department of Neurology and Center for Translational Systems Biology, Mount Sinai School of Medicine, New York, New York 10029
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Abstract

Conventional compensation of flow cytometry (FMC) data of an N-stained sample requires additional data sets, of N single-stained control samples, to estimate the spillover coefficients. Single-stained controls however are the least rigorous controls because any of the multi-stained controls are closer to the N-stained sample. In this article, a new, optimization based, compensation method has been developed that is able to use not only single- but also multi-stained controls to improve estimates of the spillover coefficients. The method is demonstrated on a data set from five-stained dentritic cells (DCs) with five single-stained and eight multi-stained controls. This approach is practical and leads to significant improvements in FCM compensation. © 2011 International Society for Advancement of Cytometry

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